Afleveringen
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Whatâs up everyone, today we have the pleasure of sitting down with Danielle Balestra, Director of Marketing Technology and Operations at Goodwin.
Summary: Marketing operations power organizational change through deep system understanding. Danielle reveals how strategic operators transform corporate landscapes by mapping intricate human networks, turning complex bureaucracies into adaptive innovation platforms. Her approach reconstructs marketing from a tactical function into a critical strategic driver, where understanding organizational dynamics becomes the primary method of creating meaningful business transformation.
About Danielle
Danielle started her career at a big ad agency in NYC before trying marketing at all sorts of different places like b2b media, financial education and brand reputation intelligenceShe spent time as a Senior consultant at a boutique agency and also freelanced as a Marketo specialistShe became Director of Marketing Ops at one of the top cancer hospitals in the US and later VP of Marketing Ops at CIT Bank where she led a big MAP transformationToday Danielle is Director of Martech and Operations at Goodwin (a global law firm), where she manages of team of 16 that includes web, CRM, Ops, Email and Solution Architect
How to Defeat Enterprise Inertia with Tactical Marketing Ops StrategiesMarketing ops in enterprise moves like molasses compared to SaaS startupsâand Danielle has the battle scars to prove it. After years in consulting, she deliberately jumped into the enterprise arena, not despite its notorious sluggishness but because of the massive internal transformation potential. "The reason I pivoted into large enterprise was because it's an opportunity to sell innovation internally, but also get paid," she explains with refreshing candor.
You face a completely different animal when implementing martech in a 4,000+ employee organization. Your job morphs into part-marketer, part-internal lobbyist:
Finding the hungry change-makers scattered across departments
Building coalitions with colleagues who crave efficiency
Selling the vision repeatedly to overcome institutional inertia
Implementing solutions that feel revolutionary in environments resistant to changeThe satisfaction comes from moving mountains that seemed immovable. Tech startups already expect and fund scaling technologiesâthe path glows with green lights. Enterprise paths bristle with red tape and "we've always done it this way" roadblocks.
Danielle's enterprise journey reads like a marketing ops fairytale gone rogue. "My three enterprises was like Goldilocks," she laughs. Memorial Sloan Kettering, despite its prestigious reputation, crawled at a pace that drove her to distraction. "It took us six months to put a preference center up. This is way too slow." The bed was too soft. CIT offered more speed but lacked investment for sustained growth. The bed was too hard.
Then came Goodwin, where the legal industry's appetite for evolution aligned with her expertise. Fresh leadershipâa new COO and chairman committed to "running business with data and intelligence"âcreated fertile ground for her marketing ops vision. This bed was just right. The transformation feels electric precisely because legal firms typically move at glacial speeds.
You'll recognize the right enterprise fit when leadership actively hungers for data-driven decisions rather than merely talking about them. Words matter less than resource allocation and willingness to disrupt comfortable patterns.
Key takeaway: Map internal influence networks, document wins with leadership-valued metrics, and secure early budget control. Build a six-month roadmap of small victories that advance your larger vision without triggering organizational resistance. Treat internal stakeholders as customers by selling efficiency improvements as competitive advantages.
Why Enterprise Martech Can Be as Fun as Tech StartupsEnterprise martech gets a bad rap for being outdated and slow. "Legacy enterprise tools-ish," as the skeptics call platforms like Microsoft Dynamics and Marketo. But this surface-level dismissal misses what actually happens inside regulated industries. Danielle dismantles this misconception with the calm precision of someone who's lived both worlds. "Being in a healthcare organization, being at a bank, do you really want to put your data out there for anyone to grab?" It's a practical question that trendy martech vendors conveniently sidestep.
> "The banks and even some financial institution clients have had data lakes and orchestration systems in place for over two decades. This is old hat for them and just new for the tech world."
Regulated industries pioneered data intelligence while today's "innovative" startups were still in diapers. "The banks and even some financial institution clients have had data lakes and orchestration systems in place for over two decades," Danielle points out with a hint of amusement. "This is old hat for them and just new for the tech world." The irony stings: what passes for cutting-edge today has been standard operating procedure in banking since before most SaaS companies existed. These industries understood customer behavior, engagement patterns, and product usage long before "customer journey orchestration" became a conference buzzword.
The real enterprise challenge isn't technological capabilityâit's processing time. When vendor onboarding takes nine months and you need a solution in six, you return to established platforms with comprehensive portfolios. Danielle's experience with an event scanner technology purchase illustrates this perfectly: "We started the process in 2019 and ended it in mid-2020. It took us almost a year to process that." During that implementation period, the vendor was acquired by another company! You face two options:
Wait patiently through lengthy security reviews for innovative tools
Expand usage of already-approved enterprise platforms
Accept that this gatekeeping prevents wasteful impulse purchases
Acknowledge that crucial tools still eventually make it throughMicrosoft Dynamics gets unfairly maligned in this "latest and greatest" obsession. Danielle's first experience with the platform revealed unexpected advantages: "Working with an organization that still programs and builds from their own code is pretty awesome." With native integrations, consistent data across systems, and direct connections to BI reporting through Fabric, Dynamics eliminates the integration headaches that consume marketing operations teams. No more asking, "Why is this in Salesforce but not in Marketo?" The data lives in one cohesive environment.
Key takeaway: Master enterprise martech by: (1) Ruthlessly audit system integration points, recognizing each connection as a data vulnerability and maintenance challenge. (2) Distinguish between product limitations and implementation failures by testing workflows across deployments. (3) Create a security-first evaluation matrix scoring tools on compliance, data isolation, and authentication before considering features. Transform security constraints into competitive advantages that protect data and career.
Building Martech Stacks That Solve Actual Business ProblemsEnterprise martech builds differentlyâforget your perfect-world stack exercises. While workshop participants happily connect hypothetical Salesforce instances to Outreach in frictionless diagrams, real enterprise teams face vendor mandates and security roadblocks that crush agility. "You can't really just connect to this," as the stark reality goes. Danielle brings refreshing clarity to this enterprise constraint, flipping perceived limitations into p...
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Whatâs up everyone, today we have the pleasure of sitting down with Rich Waldron, Co-founder and CEO at Tray.ai.
Summary: Marketing ops folks stand at a crossroads where iPaaS platforms and AI agents are colliding in crazy ways. Rich pulls back the curtain on what happens when workflows become agent "skills": Imagine your carefully built automations transformed into autonomous assistants that diagnose tech issues, provision applications, and manage complex Salesforce campaigns without manual intervention. Your marketing stack could suddenly act like a "junior admin" on demand, while you focus on strategy. The explosion of AI features has turned martech leaders into "AI referees" juggling competing vendor tools, yet those who master both fundamentals and experimental curiosity become "10X automation heroes" - the first teammates that are called when problems need solving. As Rich explains, career security comes from momentum, not stability.
About Rich
After University, Rich spent several years building different projects in the UK which included a web agency, a media company and a mobile app for social gatheringsTray was officially founded in 2013, bootstrapped by selling Wellington boots on eBay â the early product idea was email automation but pivoted to enabling less technical people to utilize APIs to integrate their tech stackAlongside his 2 co-founders, they spent the better part of 4 years building the product and raising a seed round in 2015. Between 2018 and 2020, Tray grew from $500k to $20M ARRToday, Tray processes Billions of transactions across the platform every month and theyâve gone all in on the composable AI integration and automation movement
The Rise iPaaS and AI OrchestrationiPaaS exploded because enterprise suites were too slow to open up their integration capabilities. CDPs made similar mistakes with rigid architectures, birthing today's composable alternatives. Every software system eventually faces the same primal challenge: intercommunication. Rich recounts how this pattern also repeats throughout computing history with startling consistency. Monolithic ERPs dominated early landscapes, where engineers cobbled together custom connections between internal components. These hand-built bridges crumbled easily, leaving teams scrambling for standardized frameworks that could withstand daily operational stress.
As specialized software proliferated around these central systems, integration pressure mounted. "We're still not that far through on adopting the cloud," Rich points out, puncturing the tech bubble many of us live in. While cloud technologies feel omnipresent to industry veterans, countless organizations remain firmly planted on physical servers. This reality created distinct evolutionary phases for iPaaS:
On-premise to on-premise connections (the original integration challenge)
On-premise to cloud bridges (MuleSoft's territory)
Cloud-to-cloud orchestration (where Tray focused)Each phase demanded fundamentally different architecture. Cloud applications introduced unique payload structures, execution patterns, and API designs that rendered previous integration approaches obsolete. "Every application now has an API," Rich explains, describing how this technical shift triggered organizational transformation. Marketing departments grew increasingly technical, with marketing ops professionals discovering they could craft custom experiences by tapping into these newly accessible APIs.
> "iPaaS has to evolve because if your iPaaS was built purely for an era when AI wasn't a consideration and your customers are now suddenly saying, 'We're looking at how we infuse AI in these processes,' the requirements have changed again."
You've likely witnessed this evolution in your own organization. Remember when connecting two systems required an IT ticket and weeks of waiting? Now your marketing team builds automations while the sales team creates their own customer journey orchestrations. Technical power diffused across departments, democratizing integration capabilities previously locked behind developer expertise.
Today's iPaaS platforms face their greatest evolutionary pressure yet: AI integration. Rich describes how existing processes built on traditional platforms now crumble under AI's weight. Semantic analysis, novel reasoning models, and entirely new integration approaches have rewritten the rules. iPaaS vendors who built for the pre-AI era now race to adapt as customers demand intelligent workflows. The platforms that flourish will embrace AI as a core architectural principle rather than a bolted-on feature.
Key takeaway: Evaluate your integration platform based on whether it was (re)designed for today's AI-centric landscape or simply patched to accommodate it. The most effective iPaaS solutions evolve alongside major architectural shifts rather than struggling to catch up after they've occurred.
What Makes an Agent Truly "Agentic" Beyond the Marketing HypeThe AI agent landscape is blurring with contradictions and wild claims and itâs only going to get crazier. While vendors plaster "agent" labels on everything with an algorithm, Rich isnât worried about definition. The terminology matters far less than what these systems actually do.
> "The AI isn't just reasoning over a set of data, but it's actually going and taking action on a user's behalf... I've done the response for you and I've handled the follow up and I've gone and filed this over here, and it's actually carrying out a series of actions based on the reasoning that occurred in the first place."
AI agents take autonomous action. They handle support tickets end-to-end. They file documents. They complete multi-step processes without human intervention. They execute rather than suggest.
Tray's team experienced genuine goosebump moments when they combined their connector infrastructure with LLM reasoning. You could almost hear the click as puzzle pieces fell into place. Their ten-year vision suddenly materialized before their eyes:
Semi-technical staff performing complex cross-organizational tasks
Teams breaking free from application limitations
Workers escaping data accessibility problems
AI executing the best next steps, not just recommending themThis capability triggered an immediate "holy shit" reaction during internal testing. Everything changed in that moment. The strategic implications struck like lightning: adapt or die. Many category leaders fail exactly here, at this precipice of change, clinging to outdated paradigms while disruptive innovation rewrites the rules.
The adoption curve is also likely to be shockingly steep. Century-old enterprises with conservative DNA are already running AI workloads in production using Tray. Some skipped entire technological generations, leapfrogging directly into AI implementation. They've dumped their data into databases, layered AI analysis on top, and built reactive systems around the outputs. The comfort level with these technologies has accelerated across industries at a pace that defies conventional adoption timelines.
When Tray rebranded from tray.io to tray.ai, they acknowledged that connection alone provides insufficient value in this new world. The platforms that enable autonomous action through AI will dominate the future landscape. The rest will fade into technological obscurity, remembered only as stepping stones.
Key takeaway: The future competitive advantage in your martech stack is going to come from AI that acts on your behalf, not just analyzes and recommends. When you implement systems where AI executes complex workflows based on reasoning, you empower your teams to achieve broader impact with fewer technic...
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Whatâs up everyone, today we have the pleasure of sitting down with Angela Rueda, Director of Business Martech at Meta.
Summary: Angela walked into Meta's engineering-first culture, discovering a sprawling mess of DIY custom martech solutions, and leading the organization through a fundamental mindset shift about build vs. buy decisions. She brings us through the technical and emotional journey of aligning more than 150 stakeholders ultimately forcing them to embrace a hybrid build-and-buy approach during a pivotal merger. Angela shares an honest look at what it means to lead big changes at a company like Meta, showing what really works when you're trying to transform how marketing and technology work together.
About Angela
Angela started her career in the agency world before moving over to the financial services sector at Capital Group She took a break from the corporate world and co-founded a lifestyle product company for moms and babiesShe later returned to finance and joined Citibank where she would spend the next 8 years growing into a Director of Marketing Capabilities roleToday Angela is Head of Business Martech at Meta where sheâs building a new team of data and performance marketers
Build vs Buy: Metaâs Transformation to a Hybrid Martech StackBuilding custom marketing technology sounds like a tech leader's dream: unlimited resources, world-class engineers, and total control over the final product. Angela walked into Meta with stars in her eyes, ready to architect a marketing infrastructure that would reach 200 million global businesses. The mandate sparkled with possibility - create something truly custom, uniquely Meta, uniquely powerful.
Then reality hit. Meta's growth had spawned a sprawling organism of marketing tools, each piece stitched onto the next as urgent needs arose. What looked like a blank canvas from the outside turned out to be a complex tapestry of tactical solutions, each thread woven tight to solve an immediate problem. The engineering team kept adding features:
Custom targeting modules for specific campaigns
Program-specific deployment tools
Siloed analytics systems
Fragmented automation workflowsFor that first year, Angela doubled down on the in-house vision. Meta's engineering DNA made external tools feel almost taboo. The team kept building, feature by feature, convinced they could craft the perfect solution. You might recognize this mindset - when you're surrounded by brilliant engineers, buying off-the-shelf software feels like admitting defeat.
A major organizational shift cracked the foundation of this thinking. Business marketing teams merged, exposing a stark reality: half the company used internal tools while the other half relied on third-party platforms. Maintaining multiple stacks drained resources and created confusion. The breaking point arrived organically - continue forcing an internal-only approach, or step back and reimagine the entire stack?
This constraint sparked the creative breakthrough Angela had dreamed of, just not in the way she expected. The pressure to consolidate forced hard questions about build versus buy decisions. The team had to examine their assumptions about custom development and weigh them against business needs. That original blank canvas materialized after all, painted with the colors of experience rather than theory.
What makes Meta's story feel universal is that enterprise teams everywhere build tech kingdoms in isolation, theyâre all racing toward their own goals with blinders firmly in place. Marketing squads assembling custom tools and processes at breakneck speed, treating enterprise-wide alignment as a distant luxury and a future-team problem. Then all of a sudden, organizational shifts take place. Restructures, mergers, leadership overhauls⊠they generate enough force to crack these silos open. When the dust settles and processes collide, teams finally see the cost of their fragmented systems.
Key takeaway: Build a hybrid Martech approach: identify core functions that need customization, integrate best-in-class tools for standard operations, and focus engineering resources on unique competitive advantages. Track implementation time and team satisfaction to measure impact.
Why Meta Ultimately Ditched Their DIY Martech StackMeta's engineering culture practically demanded they build everything in-house. You could feel it in every meeting: the subtle eye rolls when someone mentioned third-party tools, the reflexive reach for custom solutions, the collective pride in crafting bespoke technology. Their homegrown marketing stack embodied this philosophy, sprouting feature after feature until it required a small army of PhDs just to create basic audience segments.
Angela walked into this technical labyrinth with a mandate to reach 200 million global businesses. The existing tools scattered across Meta's landscape told a story of rapid growth and tactical thinking:
Data lived in isolated kingdoms, making it impossible to identify true marketable audiences
Campaign targeting required advanced degrees and dedicated data science teams
Channel activation cobbled together "omnichannel" experiences through manual patches
Sales and marketing data existed in parallel universes, never quite connectingThen came the organizational earthquake: a massive merger that exposed half the company running on internal tools while the other half relied on external platforms. The duplicate systems drained resources faster than a leaky pipeline. This crisis created a rare moment of organizational clarity, pushing Angela's team to step back and question their build-everything DNA.
The evaluation process sparked intense emotions. Engineers who poured years into custom solutions defended their work with spreadsheets and scoring frameworks that mysteriously always ended in perfect ties. You could see the internal struggle written across faces in every meeting: let go of years of custom development or double down on the DIY approach? The breakthrough came through radical simplicity. Meta chose to build where they held unique advantages (their data foundation) and buy proven solutions for standard capabilities. This hybrid model gave both the engineering perfectionists and practical business stakeholders something to embrace.
Key takeaway: Start with ruthless problem definition before touching tools. Map your unique challenges, build organizational alignment around those problems, then evaluate build versus buy decisions through that lens. Your best solution might combine internal strengths with external innovation, creating a practical path forward that serves both technical excellence and business reality.
Build vs Buy Was Really Privacy Control vs Speed to MarketEngineering pride runs deep at Meta. Their developers wield a particular swagger, architecting some of the world's most sophisticated social platforms. So when Angela's team questioned whether to keep building marketing tools in-house, the debates turned fierce. The war room crackled with strong opinions about resource allocation, privacy constraints, and the true cost of maintaining bespoke systems.
The arguments for building centered around three thorny challenges:
Privacy requirements demanded granular control over data handling
Data transfer costs between systems could balloon into millions
Complex account mapping for B2B marketing defied off-the-shelf solutionsYet the buy advocates painted a compelling picture: Meta's elite engineers could focus on revenue-generating products instead of reinventing marketing wheels. Angela watched the back-and-forth intensify as both camps dug in their heels. One side...
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Whatâs up everyone, today we have the pleasure of sitting down with Mac Reddin, Founder and CEO of Commsor.
Summary: Mac treks through the Jurassic wilderness of modern sales, where outbound campaigns cannibalize themselves while AI-powered sequences are degrading response quality by the day. Real marketing power flows through human networks, forward-thinking companies are transforming their SDR teams into relationship architects who measure success through network depth and authentic engagement. Be the team that does better. Your competitive edge lives in human connections that no algorithm can replicate, requiring a complete rethinking of how we incentivize and measure revenue team success.
About Mac
Mac is a career-long entrepreneur, his first business was a gaming network built on top of Minecraft which peaked at 150k users per dayHe went on to create various bootstrapped businesses over the course of 5 yearsHe created a substack newsletter for the community space which eventually evolved into an actual community of over 10k people One day he took part in a no-code hackathon and the idea of Commsor was born, initially a community reporting and metrics platformToday Commsor is a 40-person company focused on curated introductions and building the go-to-network movement
The Origin of the Dinosaur Brand Came From a TypoA misspelled tweet transformed Commsor's brand identity forever. Someone wrote "Commsaur" instead of "Commsor" on Twitter, sparking an organic evolution that proves how authentic brand moments outperform manufactured marketing strategies.
The story unfolds with raw honesty from Mac: "It became an inside joke, then our internal branding, and eventually our entire visual identity." No marketing committees. No focus groups. No desperate attempts to retrofit meaning into the accident. The team simply recognized the genuine enthusiasm building around their accidental dinosaur mascot and rolled with it.
Consider these organic moments that cemented the dinosaur's place in Commsor's DNA:
* A casual Slack screenshot sparked employee excitement
* Internal conversations naturally incorporated dinosaur references
* Team members added dinosaur emojis to their social profiles
* Customers started associating the brand with its prehistoric mascotThe business impact materialized in unexpected ways. One prospect lost Commsor's name but remembered the dinosaur. They scoured LinkedIn for employees with dinosaur emojis in their profiles, found the company again, and booked a demo. This kind of brand recall demonstrates how authentic visual elements create deeper connections than carefully crafted corporate identities.
Mac's experience teaches a powerful lesson about modern branding: manufactured meaning falls flat. When the team needed a new logo, they faced zero resistance to the dinosaur concept because it already represented their culture. You can't engineer this kind of organic brand evolution in a marketing workshop or through trend analysis.
Key takeaway: Authentic brand moments emerge from genuine team interactions and customer connections. A typo-inspired dinosaur logo drives more business value than countless hours of strategic brand planning because it represents something real: a company culture that embraces creativity, humor, and happy accidents.
Why Your Mass Outbound Strategy Cannibalizes ItselfMass outbound marketing operates like a ravenous snake devouring its own tail. Every blast campaign you send erodes response rates across the entire ecosystem, forcing you to send even more emails to hit your targets. Mac draws on the ancient Ouroboros symbol to illustrate this self-destructive pattern playing out in marketing departments worldwide.
You feel the tension daily: outbound outreach serves essential business functions. Your team needs to:
* Connect with potential podcast guests
* Build strategic partnerships
* Source vendor relationships
* Develop sales opportunities
* Nurture industry relationshipsYet the industrialization of this process through purchased contact lists and templated messages has created a toxic environment. Response rates plummet while marketing teams double down on volume, hoping quantity will save them. The math gets uglier each quarter: 10,000 emails become 20,000, then 50,000, as engagement metrics spiral downward. Your carefully crafted messages drown in an ocean of automated noise.
Mac points to the last two years as a breaking point. Marketing teams hurtle toward catastrophe like Thelma and Louise, eyes locked on the dashboard metrics instead of the cliff ahead. The cognitive dissonance feels suffocating - everyone privately acknowledges the broken system while publicly defending increasingly desperate tactics. AI tools threaten to accelerate this race to the bottom by making it even easier to flood inboxes with personalized-but-soulless outreach.
Your outbound strategy needs a reset focused on human connection. Replace mass automation with careful curation. Send fewer messages with deeper personalization. Study your target accounts' actual needs before reaching out. The marketers who thrive will build systems around quality interactions, not maximum velocity. This shift feels counterintuitive when every internal metric pushes for more volume, but the alternative leads off a cliff.
Key takeaway: Break the cycle of mass outbound marketing by prioritizing quality over quantity. Build genuine connections through carefully researched, personalized outreach that demonstrates real value to your recipients. The future belongs to marketers who choose meaningful engagement over maximum velocity.
The Brutal Math Behind Why Your Sales Outreach Dies UnreadB2B buyers now receive 500% more cold outreach than three years ago. The math becomes brutal: every sales message you craft competes with hundreds of others in an attention economy that's hitting its breaking point. Your thoughtfully personalized email drowns in the same inbox flood as automated spam blasts and LinkedIn form messages.
Think of outbound sales channels like a public park destroyed by overuse. Each individual visitor might leave only a small trace, but multiply that impact by thousands. That's what's happening to email, phone, and social outreach. Even when you craft the perfect message, your prospects have already built defensive walls:
* Automated email filters that quarantine anything resembling sales language
* Phone settings that send unknown numbers straight to voicemail
* Browser extensions that block LinkedIn connection requests
* Calendar apps that require "approved sender" statusA recent conversation with a frustrated sales leader crystallized this reality. He argued that CEOs who ignore cold outreach risk missing game-changing opportunities. But flip that logic: as a CEO of a small company, Mac sees hundreds of pitches monthly. Each one demands attention, evaluation, and response time. For leaders at larger organizations, that number multiplies exponentially. The brutal reality is that most prospects physically lack the hours needed to evaluate your message, no matter how brilliant.
The psychology of modern buyers reflects this overwhelm. When you receive 50+ sales messages daily, pattern recognition kicks in. Your brain builds shortcuts, filing anything that looks like outbound into the "deal with later" folder (which really means never). Sales teams chase prospects through an ever-shrinking window of attention, while buyers fortify their defenses against the growing assault on their time.
Key takeaway: The outbound sales crisis stems from pure mathematics: too many messages chase too...
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Whatâs up everyone, today we have the pleasure of sitting down with Ana MourĂŁo, CRM, Customer Data and CDP Advisor.
About Ana
Ana started her career in the financial services sector before moving to field marketing and ecomm partnershipsShe then spent 5 years as a Marketing leader at 3MShe created the Experimental Marketer framework to help marketers take ownership of martech Today Ana is CRM, Customer Data and CDP Advisor working with Fortune 500 customers advising on data architecture, digital engagement and customer journeys
Martech Leaders Must Become Systems ArchitectsIn theory, we all understand that martech has the potential to shape customer experiences, transform internal processes, and drive business growth. But mastering individual tools offers limited value. Ana's experimental marketer framework proposes an interesting ideat: martech professionals must evolve into systems architects who orchestrate intricate technological ecosystems while maintaining laser focus on business outcomes.
The framework, born from Ana's battlefield experience, advocates for marketers to embrace technology as a force multiplier. You already understand how martech drives conversions and engagement. Now imagine wielding that same power to revolutionize marketing operations, break down departmental barriers, and create seamless workflows that amplify team performance. This systems-level thinking separates strategic leaders from tactical operators.
Marketing technologists possess unique insights into customer engagement processes, campaign execution, and performance optimization. The framework pushes you to leverage this knowledge beyond traditional boundaries. Step into cross-functional conversations with authority. Guide IT and operations teams toward solutions that serve marketing's mission while improving organizational efficiency. Your perspective proves invaluable in bridging the gap between technical capabilities and business objectives.
Consider the ripple effects of your technology decisions. Each tool implementation, integration choice, and process automation creates waves that impact multiple teams and workflows. By viewing martech as an interconnected system rather than isolated solutions, you'll spot optimization opportunities invisible to those stuck in departmental silos. This elevated perspective transforms you from a tool specialist into a strategic architect of marketing operations.
Some practical applications Ana recommends:
Map your martech ecosystem to identify connection points and dependenciesDocument cross-functional workflows to pinpoint friction and improvement opportunities Facilitate regular discussions between marketing, IT, and ops teamsEvaluate new tools based on their system-wide impact, not just feature listsBuild processes that scale across teams and technologies
Key takeaway: The future demands marketing technologists who think in systems, not silos. Build your strategic value by understanding how technologies interconnect, impact multiple stakeholders, and drive both customer engagement and operational excellence. Your ability to architect comprehensive solutions while maintaining big-picture perspective will determine your success in this increasingly complex landscape.
Lessons from Stanley Black & Decker's Data TemplateMarketing technology demands ruthless precision in system design. When tools operate in isolation, data fragments and teams falter. Ana examines how Stanley Black & Decker, the worldâs largest industrial tool company, architected a unified martech ecosystem that transformed scattered tools into an integrated engine of market intelligence.
Strategic Foundation & Business Context
Most B2B companies operate with dangerous blind spots between their distribution channels and end users. Ana shares how Stanley Black & Decker dismantled these barriers by architecting an integrated martech system across emerging markets. Their goal transcended basic data collection; they sought to reshape product development and go-to-market strategies through direct end-user intelligence.The system's strategic architecture spanned Latin America, Asia, Middle East, and Africa, deliberately excluding mature markets to focus on high-growth regions. This geographic scope demanded sophisticated balance between centralized control and local market agility. Rather than imposing rigid global templates, the architecture provided regional teams with dynamic frameworks for market-specific adaptation while maintaining brand integrity.
Local empowerment emerged through granular control mechanisms. Teams gained the ability to modify email templates, adjust campaign elements, and launch market-specific promotions without technical dependencies. This operational autonomy accelerated time-to-market while reducing vendor reliance. A promotion in the Philippines could launch within hours instead of weeks, using pre-approved templates that maintained brand standards while accommodating local market conditions.
The Tech Stack Evolution and Adding a CDP
Marketing automation tools give your stack lightning-fast reflexes. They'll send emails, trigger workflows, and chase leads across channels with robotic precision. But Ana's work with Stanley Black & Decker exposed an uncomfortable truth: pure automation creates mindless action without strategic intelligence. You need a brain, not just a nervous system.
The team's marketing automation platform fired off messages like clockwork. Yet it remained blind to the deeper patterns hiding in plain sight. User behaviors painted intricate stories: Anna gravitating toward e-commerce content while ignoring product launches, segments showing distinct engagement rhythms across markets. These crucial signals vanished into the void between automation triggers.
The Customer Data Platform (CDP) entered as the cognitive center, not another mechanical add-on. This neural hub absorbed data streams from every market, brand, and channel. It learned to recognize behavior patterns, predict engagement paths, and surface hidden user affinities. The stack evolved from a collection of reflexes into an intelligent system capable of adapting to market-specific needs while maintaining coherent user understanding.
Data Governance Through a Data Template
Data governance rarely sparks joy. Yet Ana's work at Stanley Black & Decker proved that operational elegance hides in unexpected places. A data template, speaking the CDP's native language, transformed scattered global operations into a synchronized intelligence network without strangling regional teams in process.
The system worked through elegant behavioral design, not brute-force mandates. Forms matching the template's structure flowed seamlessly into unified customer profiles within 36 hours. Non-compliant data languished in digital limbo, requiring manual resurrection through tedious cross-departmental coordination. This natural selection pressure rapidly evolved team behavior from template resistance to passionate advocacy.
Market dynamics morphed at quantum speed. Regional teams caught form errors before deployment. Landing pages multiplied perfectly across continents. Data streamed automatically into unified profiles while teams slept. New requirements integrated organically without breaking existing flows. Most critically, cross-market performance comparison transformed from weeks of reconciliation hell into instant insight generation.
The template's adaptive properties challenged conventional governance wisdom. It maintained rigid standards while enabling local flexibility....
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Whatâs up everyone, today we have the pleasure of sitting down with Jeffrey Lee, Lifecycle Marketing Technical Lead at Calm.
About Jeff
Jeff started his career as an IT specialist at IBM He then joined Merchant Circle as a FE Web dev and eventually ended up managing a team of web developers He later joined Flipboard â a popular social magazine app â where he spent 5 years embedded into email development and marketing operations. He built and grew their email capability to sending over 400M emails per monthToday Jeff is Lifecycle Marketing Tech Lead at Calm where he architected their adoption of push notifications as a messaging channel; they now send over 300M push notifications and 2B emails per year
Building Engineering-Marketing Partnerships With a Technical and Emotional BlueprintProduct collaboration is the cornerstone of impactful marketing initiatives, yet many organizations struggle with this crucial partnership. Jeff's unconventional journey from engineering to marketing reveals a powerful framework for building authentic cross-team relationships that deliver both immediate results and long-term value.
The Technical Foundation
Most marketing teams fall into the trap of overwhelming engineering with urgent requests, only to face a wall of indifference. Jeff's engineering background helped him recognize that technical credibility forms the bedrock of successful collaboration. Rather than making desperate pleas for resources, he leveraged his technical expertise to create working prototypes that demonstrated clear business impact.
His subscription management project exemplifies this approach. By bootstrapping a solution achieving 90% accuracy in promotional targeting, he transformed abstract marketing concepts into concrete engineering challenges. The remaining optimization represented pure customer experience enhancement and operational efficiency â metrics that resonated deeply with the engineering mindset.
Building Emotional Capital
The impact extends beyond technical competency into the realm of emotional intelligence and operational empathy. Engineers particularly value colleagues who demonstrate respect for their workflows and time constraints. Jeff's approach of presenting production-ready queries and implementation frameworks eliminated the typical friction of translating marketing requirements into technical specifications.
This combination of technical fluency and operational understanding creates a powerful multiplier effect. When marketing teams blend technical capability with genuine empathy for engineering processes, they evolve from being perceived as an external burden to becoming a valued strategic partner. Each successful collaboration reinforces credibility and builds momentum for future innovations.
Creating Sustainable Partnerships
The formula for lasting engineering-marketing collaboration emerges from this dual focus on technical excellence and emotional intelligence:
1. Start with working prototypes that prove business value before requesting engineering resources
2. Present technically sound solutions in engineering-ready formats that respect existing workflows
3. Build credibility through consistent delivery of measurable impact
4. Demonstrate genuine understanding and respect for engineering priorities
5. Leverage initial wins to create natural advocacy for future marketing technology initiativesThe result is a partnership model that transcends traditional departmental divisions, creating sustainable value for both teams. By approaching collaboration through both technical and emotional lenses, marketing teams can transform skepticism into enthusiasm for projects that deliver meaningful impact across the organization.
This framework provides a blueprint for marketing teams looking to build authentic engineering partnerships that drive innovation and results. The key lies in demonstrating both technical competence and operational empathy â proving value through tangible outcomes while building emotional capital through genuine understanding and respect for engineering workflows.
Key takeaway: Win engineering trust by showing, not telling. Build working prototypes that demonstrate clear value, then present solutions in engineers' technical language while respecting their workflows. This combination of proven results and operational empathy transforms marketing from a burden into a valued partner, creating momentum for future collaboration.
Why it Took 3 Years to Convince the Product Team at Calm to Implement Push NotificationsWhether itâs product, martech or channels, sometimes decisions masquerade as data-driven choices but are actually running on raw emotion and bias. At Calm, adding push notifications sparked a three-year battle that exposed how deeply personal experiences shape enterprise product strategy. Through their struggle to balance user psychology with organizational resistance, we uncover essential principles for building sustainable engagement in mobile products.
The Psychology Behind Product Resistance
Product teams operate on gut reactions and personal biases more often than anyone wants to admit. At Calm, Jeff discovered this reality when a straightforward push notification feature turned into a three-year battle, exposing how deeply personal experiences shape product decisions at the highest levels.
The resistance stemmed from visceral reactions to notification overload. Product leaders, scarred by their own encounters with aggressive casino apps and notification spam, projected these experiences onto Calm's notification strategy. Their instinct to protect the product from becoming "one of those apps" created a powerful organizational inertia, even in the face of compelling engagement data.
The turning point arrived through an unexpected avenue: leadership turnover. A new Chief Product Officer, armed with positive experiences from previous roles, transformed the three-year roadmap struggle into a six-week sprint. This shift illuminates the stark reality of enterprise decision-making; technical complexity often plays second fiddle to personal conviction and past experiences.
Jeff's evolution from email skeptic to engagement advocate mirrors this journey. His own transformation from viewing email as "the scammiest thing" to recognizing its profound impact on user engagement adds a layer of irony to his push notification crusade. Small-scale pilots proved ineffective at winning support because they failed to demonstrate the compound effects that emerge over time. Like SEO, the true power of these engagement channels only becomes apparent through sustained, systematic implementation.
Industry-Standard Functionalities is More Important Than Competitive Dynamics
Competitive pressure normally drives product decisions, except when you're number one in the market. Jeff experienced this paradox at Calm, where their market leadership position actually worked against the adoption of push notifications. The common rationale? "We're number one. We don't need to do what others are doing to catch up."
This mentality exposes a fascinating blind spot in product strategy. While lagging competitors enthusiastically embrace proven engagement channels, market leaders sometimes cocoon themselves in a false sense of security. Their position at the top becomes a psychological barrier to adopting industry-standard features, creating vulnerability to more nimble competitors.
The definitive proof of push notifications' value emerged through an accidental experiment. When discussing hypothetical scenarios about turning off push n...
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Whatâs up everyone, today we have the pleasure of sitting down with Sandy Mangat, Head of Marketing at Pocus.
Summary: AI and outbound prospecting has flooded our inboxes with poorly personalized, irrelevant, and frankly lame template attempts at human connection. But some teams are seeing the light⊠the purple light. Sandy takes us inside the dimly lit fortune telling parlor of Pocus where we gaze into the swirling galaxies of the crystal ball of modern sales. We travel through visions of product-led sales, network referrals, signal correlation and AI agents all swirling together to fill pipelines.
About Sandy
Sandy is based in beautiful Vancouver BC, she got her start at GE Digital in Product MarketingShe later moved on to ThoughtWire, a tech company specializing in smart buildingShe then joined Charli AI, a multidimensional AI company specializing in the finance sectorToday Sandy is Head of Marketing at Pocus, an AI-native prospecting platform trusted by high growth companies like Asana, Monday, Canva, and Miro
Outbound Needs a Cold Hard ResetThe blunt reality about outbound sales is that automation obsession and meeting quotas have created a wasteland of deleted emails and blocked LinkedIn profiles. Sales teams continue spraying prospects with templated messages, while response rates plummet to new lows. Yet leadership keeps pushing for higher volumes, creating a self-destructive cycle that poisons potential customer relationships before they begin.
This mess stems from sales organizations fundamentally misunderstanding what drives genuine business relationships. Sales leaders chase efficiency through automation, treating prospects like data points rather than future partners. The result? Inboxes overflow with desperate attempts at "personalization" that read like they were written by a caffeinated robot trying to sound human. Meanwhile, genuinely interested prospects have built fortress-like defenses against the daily barrage of cookie-cutter outreach.
Consider how actual business relationships form: through authentic interactions, shared understanding, and carefully built trust. Successful outbound motions mirror this natural process, whether through thoughtful event networking, well-researched phone conversations, or precisely targeted digital outreach. Even companies swimming in inbound leads eventually require strategic outbound capabilities, especially when expanding into new markets or launching products that demand fresh customer conversations.
The path forward demands embracing what experienced sales professionals already know: shortcuts and automation cannot replace genuine human connection. Sales organizations must rebuild their outbound approach from the ground up, focusing on quality interactions over vanity metrics. This means investing serious time in prospect research, crafting genuinely personalized messages, and showing patience as relationships develop organically.
Key takeaway: Sales teams have to abandon the lame industrial approach to outbound prospecting and return to building relationships and human-centered selling. Ditch your batch and blast automation addiction, focus on qual over quant, and giving sales professionals the time and tools to build authentic relationships rather than chasing arbitrary activity and volume metrics.
Building Sales Teams for Product Led Growth CompaniesProduct-led growth companies harbor a poorly kept secret: they all run sales teams. The idealistic vision of products that "sell themselves" crashes into market realities faster than venture capitalists can say "negative churn." Companies like Miro, Asana, and Canva discovered that relying solely on product-driven acquisition limits their growth potential, especially when expanding into new markets or use cases.
The evolution of PLG sales teams reflects a sophisticated marriage between product usage data and human-driven outreach. These teams capitalize on product signals that indicate expansion potential, creating what Sandy calls "warm outbound" opportunities. When users demonstrate specific engagement patterns or hit usage thresholds, sales professionals step in to guide them toward broader adoption or premium offerings. This approach transforms traditional cold outreach into data-informed conversations with already-engaged users.
Yet even these PLG darlings recognize the strategic value of traditional outbound sales. They approach their go-to-market strategy like a diversified investment portfolio, using cold outreach to hedge against the limitations of product-led acquisition. This hybrid model proves particularly valuable when testing new markets, launching products, or exploring different use cases. The rapid feedback loop from direct sales conversations provides invaluable insights that pure product analytics might miss.
The WordPress.com experience illustrates this evolution perfectly. Despite massive organic traffic and brand recognition, they eventually built a sales team to capture enterprise opportunities and service-based revenue. This mirrors the broader industry pattern where even the most product-centric companies discover that sustainable growth requires a balanced approach combining automated product experiences with strategic human intervention.
Key takeaway: Successful PLG companies build sales teams that leverage both product usage signals and traditional outbound tactics. Rather than choosing between product-led or sales-led growth, organizations should create a balanced strategy that uses product data to inform outreach while maintaining direct sales capabilities for market expansion and enterprise opportunities.
How Product Led Sales Teams Time Their Customer OutreachThese days every SaaS company wants the magic of product-led growth: minimal sales headcount, viral expansion, and revenue that scales without an army of account executives. Yet behind the glossy investor decks and growth charts lurks an uncomfortable reality about human intervention in the sales process. Even the most automated, product-led companies scramble to hire sales teams the moment enterprise deals enter the picture.
The data tells a ruthlessly practical story: throwing sales resources at every free trial wastes everyone's time while ignoring high-value accounts costs serious money. Smart companies obsess over usage patterns, tracking signals that indicate when a prospect needs human guidance versus automated nurturing. They build sophisticated scoring models to spot accounts teetering between self-service success and quiet abandonment, timing their outreach to tip the scales toward expansion.
Sandy points out how divergent growth patterns demand radically different playbooks. Some products drive natural expansion through viral team adoption but struggle with initial activation. Others convert early users easily yet hit a wall when trying to expand across departments. These distinct patterns create clear intervention points where human touch generates outsized returns, whether that means helping a complex enterprise implementation succeed or guiding teams toward advanced features that unlock real value.
The reality of product-led sales revolves around mapping your market's actual behavior, not following someone else's playbook. Enterprise deals often demand early sales involvement due to security requirements and complex buying processes. Other segments thrive on automated expansion until they hit specific technical or organizational barriers. Companies who understand these patterns build flexible systems that deploy sales resources at precise moments of maximum leverage rather than burning cycles on low-value outreach.
Key takeaway: Map your actual user b...
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Whatâs up everyone, today we have the pleasure of sitting down with Chris Golec, Founder & CEO at Channel99.
Summary: The Godfather of ABM takes us through his humble beginnings in Detroit's industrial trenches to category creation and entrepreneurial expeditions. His journey spans building magnetic company cultures, cracking the code on remote work, sharing candid hiring wisdom, and transforming marketing failures into fuel for growth. Now building Channel99, he's rewriting attribution with a touch of AI engineering, predicting marketing ROI, using a white box approach.
About Chris
Chris started his career in the manufacturing world, working at DuPont and then GE where he moved from Engineering, Sales and Marketing rolesThe first startup he co-founded was a supply chain enterprise software where he also had the role of VP of Marketing, He grew the company to 75 people and raised $10M in VC. After only 6 years he sold to i2 Technologies for $380M A few years after his exit, Chris started his next company, Demandbase, the well known ABM platform. Along a 13 year journey as CEO he would create and lead the category of ABM software, hiring more than 1,000 people and crossing the elusive 200M in revenueToday Chris is on his 3rd company, Channel99, an AI powered attribution platform for B2B marketers
From Industrial Paint Lines to Silicon ValleyChemical engineering graduates in Detroit followed a well-worn path: automotive paint lines, waste treatment facilities, and methodical career progression through established industry giants. The conventional trajectory promised stability but offered minimal room for pioneering new ground. This reality sparked Chris's pivotal decision to pursue innovation beyond Motor City's industrial confines.
DuPont's Delaware operations presented an intriguing opportunity to spearhead European manufacturing technology adoption in the US market. The role demanded technical expertise while cultivating strategic thinking, setting the stage for an unorthodox career evolution. Engineering polymer sales, though seemingly mundane, opened doors to Boston's dynamic business landscape, where GE recognized potential in this chemical engineer turned sales strategist.
The 1990s tech boom transformed the West Coast into a crucible of innovation. As GE's industry marketing lead for high-tech materials, Chris orchestrated global deals with Apple and HP, bridging the gap between traditional manufacturing and Silicon Valley's emerging titans. The experience revealed a stark reality: technical expertise alone created opportunities, but market understanding determined success. In 1995, this insight drove Chris and fellow GE engineers to launch Supply Base, despite their complete unfamiliarity with software development.
Supply Base embodied Silicon Valley's audacious spirit. A team of engineers, armed with industrial experience but zero software knowledge, secured funding through sheer determination. The venture grew into a profitable enterprise, culminating in an exit that coincided precisely with the market peak on March 13, 2000. Yet amid this success, frustration brewed. B2B marketing remained technologically underserved, a gap that became increasingly apparent as Supply Base scaled. This observation planted seeds for future innovations in marketing technology, proving that sometimes the most valuable insights emerge from professional pain points.
Key takeaway: Career evolution thrives on identifying market gaps and embracing unconventional paths. Chris's journey demonstrates how technical expertise combined with market understanding creates opportunities for innovation, especially when traditional industry boundaries blur in the face of technological advancement.
Why Top Talent Gravitates to Companies with Purpose-Led CultureCreating genuine company culture runs deeper than the usual corporate playbook suggests. Demandbase's remarkable journey illuminates how sustained, intentional investment in organizational DNA attracts and retains exceptional talent. Chris discovered through years of leadership that authenticity, transparency, and meaningful impact serve as the bedrock of thriving workplace environments, transcending typical office perks or superficial initiatives.
Demandbase's cultural investment materialized into tangible recognition, propelling them to the tenth spot among 500,000 companies on Glassdoor by 2016. The achievement reflected genuine employee satisfaction measured through independent surveys rather than manufactured accolades. This momentum persisted as the company consistently earned "Best Places to Work" distinctions throughout the Bay Area, validating their approach to fostering genuine workplace connections.
The company's distinctive approach integrated philanthropy seamlessly into their organizational fabric. A partnership with Stop Hunger Now transformed from an office-wide meal-packaging initiative into a stadium-scale operation at their annual customer conference. This resonated profoundly with their marketing-focused clientele, spawning similar programs across multiple organizations. Additional initiatives supporting women's education and the Challenge Athlete Foundation enabled employees to contribute meaningfully beyond their B2B software focus, creating ripple effects throughout the industry.
Cultural development demands attention from inception, though its manifestation evolves with company growth. While Series A funding often marks the formal introduction of HR functions and recruitment strategies, companies under 20 employees thrive when leadership directly shapes and nurtures cultural foundations. The rise of remote work introduces new challenges, requiring deliberate effort to maintain community through strategic in-person gatherings and shared experiences that transcend virtual boundaries.
Key takeaway: Purpose-driven culture requires deliberate cultivation from day one. Organizations that prioritize authentic connections, maintain radical transparency, and create opportunities for meaningful impact naturally attract and retain exceptional talent. This foundation enables sustainable growth while fostering genuine employee satisfaction and engagement.
Why Remote Work Fails Junior Employees (And Soars for Veterans)Remote work demands a brutally honest examination beyond the standard flexibility narrative. The stark reality reveals a complex equation where career stage, personality type, and organizational DNA collide to determine distributed success. During a pre-pandemic executive assessment at Demandbase, the remote work preference split tracked perfectly along introvert-extrovert lines, foreshadowing the fundamental role of personality in distributed work effectiveness.
Career stage emerges as the make-or-break factor in remote work dynamics. Fresh graduates and early-career professionals require an apprenticeship period that Zoom simply cannot replicate. The professional polish developed through observing seasoned colleagues handle meetings, presentations, and workplace politics creates an invisible foundation for later career success. Close CRM's remote-first model crystallizes this reality; they exclusively hire veteran professionals with 10+ years of experience, acknowledging that virtual environments demand battle-tested practitioners who learned their craft in the trenches of traditional offices.
The SDR experience at Demandbase's New York office illustrates this principle in vivid detail. Post-pandemic, a group of SDRs met face-to-face for the first time, creating an impromptu laboratory for examining remote work's limitations. Physical proximity unlocked a treasure trove of professional development opportuniti...
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Whatâs up everyone, today we have the pleasure of sitting down with Meg Gowell, Director of Growth Marketing at Typeform.
Summary: Marketing leadership in 2025 is a wild time. After years of learning martech and technical concepts to become a full stack marketer, you finally land that dream director gig... only to watch your hard-earned tech skills collect dust while you drown in meetings. Megan helps us see the way forward. She takes us on a ride that covers marketing measurement, experimentation and building brand momentum, all while having tons of fun. We get into how data warehouses are not so quietly changing the martech universe while most teams are still stuffing everything they can in their CRM. Welcome to the wild world of modern marketing leadership â where you somehow need to be both a tech wizard and a strategy genius just to keep up. And weâre here to guide ya.
About Meg
Meg started her career in wedding planning while she was in college, she also started a luxury branding business for high-end weddingsShe then worked at a marketing agency for 4 years where she focused on social media, paid media and budget managementShe switched over to a boutique agency where she got a breath of experience across all facets of marketing including web design, conversion rate optimization, project management and also got to lead a team of marketersShe then moved over to a real estate startup â which was one of her former clients â as VP of Marketing and automation where she helped grow the company from $9MM to $22MM in less than a yearShe then moved over to B2B SaaS at Appcues as Director of Growth marketing where she led funnel optimization, experimentation strategy and execution, event sponsorships, biz dev and moreToday Meg is Director of Growth Marketing at Typeform where she oversees paid, web/site, lifecycle, partner marketing and campaigns
How Full Stack Marketers Drive Marketing ExcellenceFull stack marketing capabilities command premium compensation in today's market, mirroring the pattern seen with full stack engineers who rank among the highest-paid technical professionals. The comparison raises interesting questions about the relationship between full stack and T-shaped marketing skill sets, particularly regarding depth versus breadth of expertise.
The distinction between full stack and T-shaped marketers centers on the distribution of knowledge and capabilities across different marketing disciplines. While T-shaped marketers typically possess deep expertise in one area complemented by broader surface-level knowledge, full stack marketers maintain substantial working knowledge across multiple marketing domains. This broader distribution of skills enables them to engage meaningfully with specialists and make informed decisions across the marketing spectrum.
A critical advantage of the full stack marketing approach lies in its impact on team building and hiring decisions. When marketing leaders possess comprehensive knowledge across various disciplines, they can better evaluate potential hires and identify genuine experts in specialized roles. This knowledge framework helps prevent the common pitfall of making poor hiring decisions due to limited understanding of specific marketing functions or technologies.
The full stack marketer's broad knowledge base serves as a foundation for effective collaboration and decision-making. Rather than requiring mastery in every area, the key is maintaining sufficient expertise to ask incisive questions, recognize genuine talent, and understand the interconnections between different marketing functions. This comprehensive perspective enables better strategic planning and more efficient resource allocation.
Key takeaway: Full stack marketers need sufficient knowledge across marketing disciplines to recognize expertise, make informed hiring decisions, and drive strategic initiatives. Success in this role doesn't require mastery of every area but rather the ability to understand key concepts, ask relevant questions, and identify genuine expertise when building and managing teams.
Balancing Technical Proficiency and Leadership in Marketing Teams
Remember getting that dream marketing leadership role? Corner office, eager team, the works. But then reality hits - you're spending more time in strategy meetings than actually doing the hands-on work you love.
It's a weird spot to be in. The higher you climb, the further you get from the technical skills that got you there. Take Megan's story - she was crushing it at AppCues, deep in the technical weeds while leading cross-functional teams. Now at Typeform, she's managing 10 people and her calendar is packed with meetings while her technical skills collect dust.
Here's the thing - you can't fake technical knowledge. Real understanding comes from getting your hands dirty - tweaking platforms, figuring out complex filters, and really getting how things work under the hood. The best marketing leaders are like chefs who still know their way around the kitchen, not just writing menus. Your team can smell it a mile away if you've lost touch with the technical side. The real magic happens when you can switch between big-picture thinking and nuts-and-bolts knowledge. It's like being bilingual in both strategy and technical speak.
Some leaders live in the strategy clouds, others get lost in the details. The sweet spot? Knowing when to zoom in and when to step back. When you ask about campaign metrics or question technical decisions, your team knows if you're genuinely curious or just micromanaging. Feedback is a delicate art, you have to ask yourself if your input makes something better versus just different. Sometimes we suggest changes based on personal preference rather than what actually works. The key is knowing when to speak up and when to let your team run with it.
Takeaways: Your technical skills got you the leadership role. Now they need to evolve, not evaporate. The future belongs to marketing leaders who keep one foot in the code and one in the boardroom â masters of both the how and the why.
Trusting Your Gut vs Measuring All Of The Things
The marketing metrics obsession has gone too far. While CFOs salivate over spreadsheets demanding ROI calculations for every LinkedIn post and email blast, they're missing a crucial reality check: humans are gloriously unpredictable creatures who refuse to follow our carefully crafted attribution models. The digital advertising revolution sold us a compelling fantasy of perfect measurement, but reality stubbornly refuses to play along.
After the "growth at all costs" party ended with a nasty hangover, companies sobered up and started demanding receipts for every marketing dollar spent. Logical? Sure. Realistic? Not even close. This myopic fixation on measurable channels creates a dangerous illusion of control. Paid search might give you beautiful conversion tracking, but try building a billion-dollar brand on Google Ads alone. Spoiler alert: it won't work. Real growth demands embracing the uncomfortable truth that some of your most powerful marketing moves will resist neat ROI calculations.
Modern marketing success requires omnipresence, not just optimization. Your target audience bounces between platforms like a caffeinated pinball, interacting with your brand across countless touchpoints. Social media, influencer collaborations, and content marketing often defy precise attribution, yet they create the vital ambient awareness that drives long-term growth. The magic happens in the messy middle, where multiple channels work together in ways that no attribution model can fully capture.
Getting leadership buy-in for this reality requi...
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Whatâs up everyone, today we have the pleasure of sitting down with the lads from We're not marketers.
Summary: When did everyone on LinkedIn suddenly become a GTM expert? The misfits from âWe're Not Marketersâ dive into this chaos, explaining why Go-to-Market strategy has become the most misused term in marketing. They share product marketing stories about rigid product launches, cross-functional chaos, and small test groups. They open up about their love and admiration for marketing operations folks, similar cross functional translators between tech and marketing and how martech can support message testing. We explore the debate of who should have final word on messaging, PMMs or the channel SMEs. Join us for the laughs, stick around for the love between PMMs and martech.
About the 3 Misfits
All 3 of these gentlemen work for themselves as fractional PMMsGab Bujold (Bu-jo) is based in Quebec city, Canada. Heâs a messaging expert and also a marketing advisor for early-stage startups, heâs a former product marketer and 4-time solo marketer at various different brands and sports an incredible mustacheAlso joining us today is Zach Roberts is based in California, he worked in B2B SaaS sales for half a decade before pivoting to product marketing with a focus on enablement, heâs worked at big names like Dropbox, LinkedIn and Google. Heâs a 2x recognized Product Marketing Influencer by PMALast but certainly not least, weâre also joined by Eric Holland whoâs based in Pennsylvania, heâs a product-led content pro also runs a retail apparel startup and is a recovering in-house product marketer. Heâs the mastermind behind the creative AI skullies artwork of their podcast
Why Go to Market Strategy Has Become a BuzzwordThe concept of go-to-market (GTM) strategy has entered peak buzzword territory in recent years. What was once a product marketing-specific term focused on launching new products or features has been hijacked by nearly every department under the sun. These days, everyone from sales and marketing ops to customer success is suddenly a "GTM expert" on LinkedIn. The term has become so diluted that it's starting to lose its meaning entirely.
The transformation of GTM into a catch-all phrase stems largely from corporate politics and self-preservation. Teams across organizations are scrambling to attach themselves to GTM initiatives, fearing that being left out might signal their irrelevance. As Zach points out, there's an underlying anxiety that not being involved in GTM somehow makes a team dispensable, leading to a kind of organizational FOMO that has stretched the term beyond recognition.
The reality is that successful GTM execution has always required coordinated effort across multiple teams. Product marketing traditionally orchestrates these initiatives, but they can't execute alone. It takes sales for implementation, product teams for development, and marketing for awareness. The problem isn't collaboration; it's the current trend of every team claiming to be the primary GTM driver, creating confusion about who actually owns the strategy.
Eric makes a crucial distinction between "going to market" and "go-to-market strategy" that cuts through some of the noise. While the strategy might come from product marketing or revenue leadership, the execution involves multiple teams working together. The challenge is maintaining clear ownership of the strategy while preventing it from becoming another meaningless corporate buzzword that everyone claims expertise in.
Key takeaway: Organizations need to stop the free-for-all claiming of GTM expertise and return to clearly defined roles within the GTM process. Success depends on having centralized strategic ownership while enabling individual teams to excel in their specific GTM responsibilities, not turning every department into self-proclaimed GTM experts.
Who is Responsible for Operationalizing GTMPicture a chill Broadway production: everyone from lighting to sound plays a crucial role, but someone needs to direct the show. Product Marketing's role in GTM execution presents a fascinating operational challenge. While multiple teams claim ownership over GTM initiatives, the real question isn't about territorial control but about orchestrating complex product launches effectively.
The operational reality of GTM involves intricate coordination across specialized teams. Marketing and sales ops teams manage the technical infrastructure, configuring everything from CRM workflows to marketing automation. Lifecycle marketing teams often gatekeep new feature and product notification announcements and balance that with existing messages. Product marketing develops the strategy and messaging, while sales teams handle direct customer engagement. Each group brings essential expertise to the table, making territorial claims over "GTM Ops" not just unnecessary but counterproductive.
Gab's makes a really good point that Product Marketing Managers excel at running small-scale experiments, gathering feedback, and iteratively refining go-to-market approaches. This methodology allows teams to validate strategies before full-scale deployment, reducing risk and improving outcomes. It's not about owning GTM ops; it's about facilitating successful product launches through methodical testing and collaboration.
You should view GTM operations as a collaborative framework rather than a power structure. PMMs serve as strategic conductors, coordinating efforts across teams while respecting each group's expertise. When campaigns underperform, the root cause typically traces back to poor coordination or unclear direction, not technical execution. Success requires letting each team excel in their domain while maintaining a unified strategic vision.
Key takeaway: Focus on establishing clear operational frameworks where Product Marketing Managers guide strategy and testing, while specialized ops teams manage technical implementation. Success comes from collaboration and respect for expertise, not from claiming ownership over the entire GTM process.
Prioritizing Product Marketing Requests vs Martech RoadmapsThereâs often a natural tension between PMMs who think every feature deserves a big email to everyone in the database and the martech or marketing ops team who has an existing roadmap and existing comms in place. New GTM initiatives donât get to market on certain channels without the SME team converting words into code and automation. This creates a complex decision making process that often requires somewhat lame but important evaluation of business impact and strategic alignment.
Strategic prioritization requires product marketers to approach each situation with an analytical mindset focused on identifying the most pressing business needs. As Eric explains, the process resembles assessing multiple issues requiring attention but having limited resources to address them all simultaneously. The key becomes determining which initiative will deliver the most significant impact toward established organizational goals and objectives.
The reality of product marketing involves making difficult trade-offs between seemingly equally important initiatives. While new product launches naturally generate excitement and momentum, they must be weighed against the potential impact of operational improvements that are already on the martech roadmap like enhanced product analytics or refined lead scoring mechanisms. These behind the scenes projects often create foundational improvements that enable better execution of future go to market activities.
At the end of the day, most product launches have flexible timing - what's critical is identifying the few relea...
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Whatâs up everyone, today we have the pleasure of sitting down with Sundar Swaminathan, author of the experiMENTAL newsletter and part time Marketing and Data science advisor?
Summary: After leading Uber's Marketing Data Science teams, Sundar shares insights that work for both tech giants and startups. Beyond uncovering that Meta ads generated zero incremental value (saving $30 million annually), they mastered measuring brand impact through geo testing and predicting LTV through first-week behaviors. Small companies can adapt these methods through strategic A/B testing and simplified attribution models, even with limited sample sizes. Building data science teams that embrace business impact over technical complexity, and maintaining curiosity, like when direct driver engagement revealed that recommending Saturday afternoon starts over Friday peak hours improved retention.
About Sundar
Sundar started his career as a software developer at Bloomberg before managing $19 Trillion at the US Treasury as a Debt ManagerHe pivoted to growth marketing and data science consulting where he worked with DirectTV and an ed-tech AI startupHe then made the mega move to Uber where he spent 5 years building Brand, Performance, and Lifecycle Marketing Data Science teamsHe moved over to a travel tech startup and helped them go from $0 to $100K MRRToday, Sundar is a marketing and data science advisor, he helps B2C founders and marketers Heâs also working on an upcoming podcast and has a newsletter where he shares frameworks, how-to guides to help B2C marketers
Marketing Incrementality Testing Reveals Meta Ads Ineffective at UberPerformance marketing often reveals surprising truths about channel effectiveness, as demonstrated by a fascinating case study from Uber's marketing operations. When confronted with unstable customer acquisition costs (CAC) that fluctuated 10-20% week over week despite consistent ad spend on Meta platforms, Uber's performance marketing team, led by Sundar, decided to investigate the underlying causes.
The investigation began when the team noticed significant volatility in signup rates despite maintaining steady advertising investments. This inconsistency prompted a deeper analysis of Meta's effectiveness as a primary performance marketing channel. The timing of this analysis was particularly relevant, as Uber had already achieved substantial market penetration eight years after its launch, especially in major urban markets where awareness wasn't the primary barrier to adoption.
Through rigorous data analysis, the team implemented a three-month incrementality test to measure Meta's true impact on user acquisition. The test utilized a classic A/B testing methodology, comparing a control group receiving no paid ads against a treatment group exposed to Meta advertising. The results were striking: Meta advertising showed virtually no incremental value in driving new user acquisition, a finding that was validated by Meta's own data science team.
The outcome of this experiment led to a significant strategic shift, resulting in annual savings of approximately $30 million in the U.S. market alone. While this figure might seem modest for a company of Uber's scale, its implications were far-reaching when considered across global markets. The success of this experiment also highlighted the importance of data-driven decision-making and the willingness to challenge assumptions about established marketing channels.
Key takeaway: Established marketing channels should never be exempt from rigorous effectiveness testing. Regular incrementality testing can reveal unexpected insights about channel performance and lead to substantial cost savings. Marketing teams should prioritize data-driven decision-making over assumptions about channel effectiveness, even for seemingly essential platforms.
How to Run Marketing Experiments With Limited DataMost companies donât have the volume of signups or users that an Uber does. Marketing experiments require a mindset shift when working with small data samples. While A/B testing remains the gold standard for measuring marketing effectiveness, Sunday thinks that companies with limited data can still validate their marketing efforts through strategic pre-post testing approaches.
Pre-post testing, when properly implemented, serves as a valuable tool for measuring marketing impact. The key lies in isolation: controlling variables and measuring the impact of a single change. For instance, a marketplace company successfully conducted a pre-post test on branded search keywords in France by isolating specific terms in a defined region. This focused approach provided reliable insights despite not having the massive data volumes typically associated with incrementality testing.
That being said, Sundar adds that early-stage companies should prioritize high-impact experiments capable of delivering substantial results vs testing tiny changes that will barely have detectable effects. With small sample sizes, tests should target minimum detectable effects (MDE) of 30-40%. These larger effect sizes become measurable even with limited data, making them ideal for fundamental changes such as exploring new ideal customer profiles (ICPs) or revamping core value propositions, rather than pursuing minor optimizations.
An example that Sundar recalls while working at a travel tech startup demonstrated the value of running A/B tests even with limited data. Despite having only 100-200 weekly signups, they detected a 40% conversion drop after modifying their onboarding flow. While the test might have been considered "poorly powered" by strict statistical standards, it successfully prevented a significant negative impact on the business. This illustrates how even small-scale testing can provide crucial insights; it's better to have 60% confidence in a positive change than to miss a catastrophic drop with 95% confidence.
The confidence level in marketing experiments operates on a spectrum, with A/B tests providing the highest confidence and pre-post tests offering valuable but less definitive insights. Success depends on maintaining experimental discipline, carefully controlling variables, and understanding the tradeoffs between confidence levels and the humbling reality of practical constraints. Marketing teams must balance their confidence requirements against their risk tolerance when designing and interpreting tests.
Key takeaway: Companies with limited data should focus on measuring high-impact marketing changes through carefully controlled pre-post tests. Success comes from isolating variables, targeting substantial effect sizes, and maintaining experimental discipline. This approach enables meaningful measurement while acknowledging the practical constraints of smaller data sets.
The Difference Between AB Testing and Incrementality TestingMarketing experimentation terminology often creates unnecessary complexity in what should be straightforward concepts. The fundamental structure of both A/B testing and incrementality testing follows the same principle: comparing outcomes between groups that receive different treatments.
Statistical analysis remains consistent across both testing approaches. Whether using Bayesian or frequentist methods, the underlying comparison examines differences between groups, regardless of what those groups receive. The statistical calculations remain indifferent to whether one group receives no treatment (as in incrementality tests) or a variation of the treatment (as in traditional A/B tests).
Incrementality testing extends beyond simple presence versus absence comparisons. For example, marketers can test spending increm...
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Whatâs up everyone, today we have the pleasure of sitting down with Sarah Krasnik Bedell, Director, Growth Marketing at Prefect.
Summary: What happens when a data engineer with an obsession for truth-testing crashes into marketing's sacred cows? Sarah's journey from code to campaigns unfolds like a detective story, where she picks apart marketing myths and rebuilds them with an engineer's precision. Her fresh take transforms marketing tools from black boxes into purposeful instruments, while her approach to AI echoes "Limitless" - it's not about letting machines take the wheel, but supercharging human creativity. Whether you're wrestling with developer outreach or trying to get sales and marketing teams to actually talk to each other, Sarah's technical-meets-tactical perspective offers a compelling roadmap for modern marketing that actually works.
About Sarah
Sarah studied math and cognitive science before completing a masters in data scienceShe started her career at Amsted working on data aggregation and machine learning models and eventually moved to a customer-centric role where she helped engineer data architecture for supply chain optimizationsShe had short stints in financial forecasting and company-wide data architectureShe then joined Perpay as a data engineer focused on product analytics as well as reverse-ETL for their marketing team. She was eventually promoted to Lead data eng, managing the full team of data engineers Sheâs an Analytics and GTM Advisor for devtoolsToday sheâs Director of Growth Marketing at Prefect, a workflow orchestration tool for data and ML engineers
Unconventional Paths From Data Engineering to Marketing LeadershipThe traditional career trajectory rarely follows a straight line, particularly in Sarah's fascinating pivot from data engineering to marketing. While leading the data engineering team at Perpay, she found herself knee-deep in an Iterable implementation project that would unknowingly alter her professional DNA. This wasn't just another technical integration; it was a complex orchestration of customer data streams, product catalogs, and audience segmentation capabilities that secretly doubled as an apprenticeship in modern marketing mechanics.
Marketing technology projects have a peculiar way of revealing their true nature over time. What begins as lines of code and data pipelines often transforms into something far more intriguing: a window into the soul of marketing operations. Sarah discovered that while her peers remained captivated by the elegance of their code, she found herself increasingly magnetized by the downstream impact of these technical solutions. This subtle shift in perspective proved transformative, compelling her to venture beyond the comfortable confines of engineering meetings and into the dynamic world of marketing strategy sessions.
The pandemic's isolation birthed unexpected opportunities, as Sarah's technical writing began attracting attention in the data community. What started as casual documentation of her engineering adventures morphed into paid writing engagements, creating a surprising bridge between technical expertise and marketing communications. This organic evolution suggested something more profound lurking beneath the surface, a hidden pathway connecting the precision of data engineering with the artistry of marketing strategy.
The final pieces of her transition fell into place through a combination of hands-on consulting work, mentorship from industry veterans, and immersion in marketing literature. Her participation in the Reforge community added structured learning to her toolkit, while her unique perspective as a former technical buyer provided invaluable insights into marketing dynamics. This multifaceted approach to learning, mixing practical experience with theoretical knowledge, transformed what might have seemed like an improbable leap into a natural progression.
Key takeaway: Career transitions in technology rarely require formal education; they thrive on practical experience and curiosity. The most valuable skills often develop through side projects, technical writing, and a willingness to understand the business impact of your work. For those considering a similar path, start by documenting your technical experiences, engaging with cross-functional teams, and focusing on how your current role impacts business outcomes rather than just technical implementations.
First Principles Marketing Against Best PracticesMarketing orthodoxy often goes unchallenged, with practitioners blindly following conventional wisdom without questioning its validity. Sarah brings a refreshing perspective to this dilemma, approaching marketing strategies with an engineer's skepticism and a commitment to first principles thinking. This natural inclination to question established norms stems from her background in data engineering, where decisions require rigorous validation rather than mere acceptance of industry standards.
The notion that Tuesday morning at 8 AM represents the optimal time for email sends exemplifies the kind of unexamined marketing wisdom that pervades the industry. Rather than accepting such practices at face value, Sarah advocates for a two-pronged approach: first envisioning the ideal outcome, then assessing what's practically achievable within existing constraints. This methodology creates space for innovation while maintaining pragmatic boundaries, allowing marketers to challenge assumptions without losing sight of business objectives.
The parallel between architectural decisions in software engineering and strategic choices in marketing reveals an interesting pattern. Just as engineers must carefully consider system architecture before writing code, marketers benefit from establishing solid strategic foundations before diving into tactical execution. This shift in focus from immediate implementation to thoughtful strategy design represents a more sophisticated approach to marketing operations, one that prioritizes intentional decision-making over reflexive adoption of industry practices.
In the context of accelerating AI adoption, this first-principles approach becomes even more crucial. Rather than immediately jumping to content creation or campaign execution, successful marketing strategies begin with fundamental questions about audience selection, engagement methods, and value proposition. This methodical approach ensures that technological tools serve strategic objectives rather than dictating them, maintaining human judgment at the core of marketing decisions.
Key takeaway: Transform your marketing approach by questioning established practices and applying first-principles thinking. Start by clearly defining your ideal outcome, then work backward to create practical strategies that challenge conventional wisdom. This method often reveals more effective approaches than blindly following industry "best practices." When evaluating any marketing tactic, ask yourself: "What problem are we really trying to solve, and is this truly the most effective solution?"
Systems Thinking Applications For Marketing AnalyticsSystems thinking represents the essential bridge between marketing and data engineering, offering a framework for understanding how data flows through modern marketing operations. The ability to visualize and architect data pathways across platforms separates proficient marketing technologists from those merely executing tactical campaigns. This foundational skill proves invaluable when orchestrating the complex dance of customer data across marketing systems.
Consider the journey of a single lead signal as it traverses through various marketing platforms. The ...
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Whatâs up everyone, welcome to our first episode of 2025 â today we have the pleasure of sitting down with Austin Hay, Co-Founder and Co-CEO at Clarify and Martech Teacher at Reforge.
Summary: Something extraordinary is brewing in the world of martech. In the near future, Austin thinks AI agents will turn into an omniscient digital butler, anticipating your needs with uncanny precision while vanishing into the background of your workday. But the real revolution unfolds in the seemingly mundane machinery of marketing operations, where innovative companies are transforming their spaghetti mess of data pipes and platforms into something approaching digital poetry. The fundamental building blocks of our systems aren't disappearing, they're gaining superpowers. Hear it from one of our industry's most thoughtful builders.
About Austin
Austin started his career at Accenture but he left the Fortune 500 world to join a startup called Branch where he became the 4th employeeAustin then created his own boutique mobile growth engineering consultancy. He grew the practice to 1.5M with big names like Walmart, Jet, Airbnb, Foursquare and more.His consulting practice was aqui-hired by mParticle â a leading CDP solution where he would eventually become VP of Growth He later joined Runway as VP of Business OperationsHe also started building The Marketing Technology Academy â an online learning center for martech which he would eventually sell to Reforge and become the Instructor for the new Martech courseHe was also Head of Martech at Ramp, a fintech startupLast year, Austin strapped on his jetpack and became a product founder at Clarify conquering SF and Hubspot and building the first flexible, intelligent CRM that people actually enjoy using.
AI Agents and the Hidden Promise of Ambient ComputingLet's face it, manually feeding context to AI feels a bit like teaching a fish to ride a bicycle. Current AI systems, brilliant as they may be at crunching numbers and crafting responses, still stumble around our digital workspaces like a tourist without a map. Sure, they can write a decent blog post or solve complex equations, but they're essentially working with one hand tied behind their virtual back.
Now, imagine your AI assistant as more of a digital detective, quietly observing and understanding everything happening on your screen. No more copying and pasting chunks of text or explaining what's in your Notion workspace for the hundredth time. Picture having a conversation with your computer while it maintains an almost supernatural awareness of your digital environment, from those buried Slack threads to that spreadsheet you've been avoiding. Recent demonstrations, like Kieran Flanagan's adventure with Gemini's screen reader, hint at this future, even if current versions move with all the grace of a sleepy sloth.
The real magic kicks in when we start thinking about operating system-level integration. Platform-specific AI agents are like horses wearing blinders; they can only see what's directly in front of them. But desktop applications from companies like GPT and Anthropic are pushing toward something far more interesting: AI that can understand your entire digital world, not just a tiny slice of it. It's the difference between having a personal assistant who can only help you in the kitchen versus one who can manage your entire house.
Here's where things get particularly juicy: this isn't some far-off sci-fi fantasy. We're looking at a five-year horizon where the clunky, permission-asking AI of today evolves into something far more sophisticated. The transformation won't happen overnight (sorry, instant gratification seekers), but when it does, we're talking about a 10x boost in productivity that makes current productivity hacks look like using a butter knife to cut down a forest.
Key takeaway: While today's AI assistants feel like overeager interns requiring constant supervision, the next five years will usher in truly ambient AI that seamlessly integrates with our operating systems. The future isn't about teaching AI to understand us; it's about AI that already knows what we need, when we need it, across our entire digital landscape.
The Limitations of AI Agent MarketplacesThe AI marketplace concept raises important questions about automation's role in our daily work. While downloading specialized AI agents for every task might sound appealing, reality suggests a different path forward. Current marketplace models mirror the Chrome extension ecosystem, where tools often remain peripheral rather than becoming essential to core workflows.
Austin frames the central debate in venture capital circles clearly: will we depend on AI agents that require explicit commands, or will we embrace ambient intelligence that works proactively in the background? Looking at the CRM space, Austin points out a crucial consideration that many futurists overlook. You can't simply discard two decades of sales methodology and expect professionals to embrace a completely alien interface. Instead, sellers need familiar elements: contacts, companies, opportunities, and tasks, all presented in recognizable formats that align with established workflows.
The intersection of traditional software and AI becomes particularly interesting when Austin discusses CDP platforms. Users expect certain fundamentals, like accessing persona views and tracking customer behavior. The innovation opportunity lies not in replacing these elements but in enhancing them through intelligent automation. Austin suggests that the key difference emerges in how these agents operate: will users actively assign tasks, or will agents run continuously in the background, performing expected functions without explicit direction?
While some platforms champion what Austin calls the "jack of all trades" approach with Notion-style customizable workflows, he makes a compelling case for specialized, industry-specific solutions. This focused approach, where AI agents operate autonomously within well-defined parameters, might prove more valuable than a marketplace full of generic tools. Austin emphasizes that the more specialized you are in understanding user needs, the more effective your agentic experience can be, particularly when it runs seamlessly in the background without requiring constant configuration.
The reality likely lies somewhere in between these two extremes. Certain straightforward tasks, like data enrichment for new records or basic categorization, seem well-suited for autonomous AI agents. However, more complex decisions involving customer lifecycle management, timing of promotional offers, or predictive modeling for next-best-action recommendations require deeper integration with historical data and sophisticated propensity models. The key to success may not be choosing between marketplace agents or integrated solutions, but rather understanding which approach best suits specific use cases and organizational needs.
Key takeaway: Success in AI automation won't come from marketplace-driven point solutions but through deeply integrated, industry-specific AI that enhances existing workflows while maintaining familiar interfaces. Austin's insights suggest focusing on building AI that complements rather than replaces established business processes, creating tools that feel natural rather than revolutionary.
The Core Primitives of Martech and the Path to Self-Designing APIsEver tried explaining Bitcoin to your grandparents? That's roughly how it feels watching companies try to skip straight to AI automation without understanding their data foundations. Austin breaks down the concept of primitives in martech, those fun...
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Whatâs up everyone, today is our last episode of the year and if you paid attention to the intro, Iâm excited to officially welcome Darrell Alfonso as the newest co-host of the podcast!
Summary: The Humans of Martech enters an exciting new chapter with Darrell Alfonso joining as co-host, bringing fresh energy and insights to the show. As a long-time listener and new dad, Darrell offers relatable stories of juggling work, family, and community while sharing bold predictions like the shift to warehouse-native architectures in martech, which promise to streamline data operations for enterprises. With AI poised to handle executional tasks, Darrell emphasizes the evolving role of marketers as strategic thinkers guiding AI with emotional intelligence and ethical oversight. As the podcast heads into 2025, it remains committed to delivering actionable insights, thought-provoking predictions, and a fresh perspective for the martech community.
Welcoming a New Co-Host and Celebrating Baby Milestones
Darrellâs journey to becoming a co-host on the podcast came full circle, blending mentorship, passion, and personal milestones. He shared how one of his mentees suggested the idea, sparking an opportunity he immediately embraced. As an early listener of the show, Darrell highlighted his admiration for its unfiltered and geeky deep dives, calling it his favorite podcastâa sentiment that fueled his excitement for the road ahead.
On a personal note, Darrell and his wife recently welcomed their baby boy, just eight weeks ago. Parenthood, he admitted, has been a whirlwind of sleepless nights and steep learning curves. As ambitious and organized as he and his wife are, theyâve quickly discovered that babies donât operate on predictable timelines. Moments of progressâlike better sleepâoften take a step back as developmental leaps shake up routines. While the lack of rest is taxing, Darrellâs outlook reflects a blend of exhaustion and gratitude.
Balancing professional life with a newborn is no small feat. Darrell recounted a whirlwind day of delivering a keynote, driving home, and immediately diving into baby duties. He joked about the unpredictability of these moments while acknowledging the personal growth they inspire. Virtual support groups like Maven have also helped him navigate the early stages of parenthood, offering both guidance and camaraderie with other new parents.
For all the challenges that come with parenthood, I always like to emphasize gratitude. Reflecting on the struggles my family faced in our journey to parenthood (and how many other couples have it much harder), we need to emphasize the importance of cherishing even the tough parts. The joy and fulfillment of finally welcoming our child outweigh the sleepless nights and ever-changing routines.
Key takeaway: Parenthood is a mix of exhaustion, growth, and gratitude. Embracing the ups and downs, leaning on community support, and focusing on the meaningful moments can help navigate this transformative stage of life.
Marketing Tools Without DatabasesOkay⊠enough baby talk haha.
Darrell predicts that in 5 years, most marketing tools will no longer rely on databases. At first glance, this concept might seem shockingâafter all, marketing automation platforms, CRMs, and CDPs are fundamentally built on relational databases. But Darrell suggests this assumption is rooted in tradition, not necessity, and outlines a shift toward a warehouse-native or zero-copy data architecture that could redefine how tools operate.
To illustrate this point, he draws a simple analogy. Consider apps like Yelp or Google Places. When you share a restaurant with a friend, the app doesnât create a duplicate of your contacts database; it accesses the data on-demand. Contrast this with the typical marketing stack, where almost every tool replicates contact data, creating endless updates, sync errors, and manual fixes. Darrell estimates that more than 80% of a teamâs data work revolves around ensuring consistency across these copied datasetsâa cumbersome and inefficient process.
The inefficiency extends beyond wasted effort. Darrell shares examples of bi-directional sync loops that occur when two systems endlessly update each other, introducing a frustrating complexity to even the simplest workflows. These scenarios highlight how deeply ingrained data copying is within current systems and how much time is spent combating its limitations.
Shifting to a zero-copy model, Darrell argues, could eliminate these inefficiencies. A warehouse-native approach would enable tools to work directly from a centralized data warehouse, bypassing the need for constant synchronization. This not only streamlines operations but also reduces the risk of errors. Itâs a radical departure from the status quo but one he believes is inevitable as teams demand greater agility and accuracy in their tools.
Key takeaway: The future of marketing tools lies in a warehouse-native approach, eliminating the inefficiencies of duplicated data. By moving beyond traditional databases, teams can reduce errors, streamline processes, and focus their energy on strategic initiatives rather than endless data synchronization.
Preparing for a Warehouse Native FutureI think the shift toward a warehouse-native approach for marketing tools feels inevitable, but its timeline remains uncertain. While this approach wonât entirely replace APIs, it will change how tools interact. Instead of passing data back and forth through integrations, tools will increasingly work directly from a centralized data warehouse, eliminating inefficiencies tied to duplication and synchronization.
This prediction, often misunderstood as futuristic, is already shaping current tools. Vendors like MessageGears and Castle.io are leading the charge, offering solutions that bypass traditional database structures and avoid charging based on record counts. Despite their innovations, the challenge lies in industry adoption. Many teams are accustomed to older models, making this transition as much about change management as it is about technology.
A critical insight from my past research and conversations with experts on the podcast highlights the importance of internal readiness. Tools can only perform as well as the data they rely on. High-quality, structured data is the foundation for warehouse-native success. Teams must focus on improving internal processes now, rather than waiting for the perfect tool to arrive. This means investing in data hygiene, organization, and strategy to prepare for the opportunities that a warehouse-native architecture will bring.
However, the path forward isnât without challenges. Many companies are still immature in their data strategies, making widespread adoption a longer process than anticipated. Whether this shift takes five years or more, the direction is clear: vendors and teams must align their operations with the possibilities of a warehouse-first world.
Key takeaway: Warehouse-native tools represent a significant step forward in reducing inefficiencies and modernizing operations. Teams can prepare for this shift by prioritizing high-quality, well-structured data. The strength of these tools lies in how they interact with clean, organized data, making internal readiness the best first step for embracing this future.
Understanding When Warehouse Native Tools MatterDarrell explains that the value of warehouse-native tools becomes clear especially when dealing with large volumes of data. For small and mid-sized companies, the classic setupâa CRM, marketing automation platform, and a few connected toolsâworks perfectly fine. He notes that for organizations with 500 employees or fewer, traditional data architectures remain suff...
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Whatâs up everyone, today we have the pleasure of sitting down with Kacie Jenkins, SVP Marketing at Sendoso.
Summary: Marketing isnât about cramming creativity into a spreadsheet, and Kacieâs journey proves it. She took on last-touch attribution, broke free from narrow metrics, and built a system that told the whole story, one where sales and marketing actually worked together. It wasnât flashy; it was months of unsexy foundational work that led to record-breaking results. Kacieâs advice is to stop obsessing over proving your worth with perfect data. Focus on collaboration, long-term strategies, and building something so good it proves itself.
About Kacie
Kacie started her career as a recording artist for 6 years where she recorded and released 2 top 30âs singles on country radioShe transitioned to FANDOM as Marketing Manager where she helped build and scale entertainment and gaming communitiesShe then shifted to consumer tech and worked at Roku where she helped take their streaming stick to marketShe later joined Fastly when they were still a tiny startup and was eventually promoted to VP of Marketing while helping them scale to $200M in ARR and a massive IPOShe moved on to a few other VP of marketing stints at Ace Hotel and then SourcegraphToday Kacie is Senior Vice President of Marketing at Sendoso, the top gifting and direct mail platform for revenue teamsWhy Marketing Needs to Break Free from Last Touch Attribution
Kacie has strong opinions about last touch attribution and its role in marketing, calling it both misguided and overused. She recounts a memorable example where a companyâs finance team mandated that every marketing touchpoint be unique, forbidding multiple efforts for a single account. The result was a fragmented strategy, with marketing forced to isolate efforts rather than integrate themâa scenario she describes as fundamentally broken. This, she says, reflects a wider misunderstanding of marketingâs role in driving success.
In her experience, marketing is often held to an unrealistic standard that no other department faces. âNo one questions whether a sales team should exist,â Kacie points out, yet marketers are repeatedly asked to prove their value in isolation. This obsession with single-point attributionâwhether first or last touchâreduces complex buyer journeys to simplistic, unrealistic models. She likens it to sports, where success is measured by the contributions of the entire team, not just the final goal or play. In marketing, the same principle applies: campaigns succeed when brand, product, sales, and customer experience work cohesively.
Kacie highlights how marketers often agree to flawed measurement practices under intense job pressure. Many leaders, she notes, demand immediate, trackable results and dismiss longer-term investments like brand building. When these short-sighted strategies fail, the blame lands on the marketing team, perpetuating a destructive cycle. This became especially apparent during the pandemic, when companies slashed budgets for brand and integrated marketing, only to see their performance suffer months later.
At its core, the problem stems from a demand to quantify marketing in ways that are convenient rather than meaningful. Kacie insists that attribution models like last touch can provide insights but have been misused to force marketing into a demand capture role that undervalues its broader impact. Effective marketing, she argues, cannot succeed in a vacuumâit depends on the health and alignment of the entire organization.
Key takeaway: Attribution models like last touch offer insights but become problematic when used in isolation. Marketing thrives on collaboration across teams, long-term investments, and integrated strategies. Simplistic measurement frameworks undermine this by reducing success to isolated metrics, which fail to capture the bigger picture. Focus on fostering collaboration and investing in holistic strategies rather than chasing immediate, trackable wins.
Whatâs the Best Way to Prove What Drives Revenue in Marketing?Kacieâs candid take on the challenges of attribution didnât stop there. She explains that board members and leadership often seek simple answers, asking, âWhat drove the most revenue?â This, she notes, is rarely a question with a singular answer, and it certainly doesnât lie solely in the last touchpoint.
Her approach combines every available data point, UTMs, self-reported attribution, and multi-touch models, to create a comprehensive picture. This isnât about assigning credit to one channel or tactic but understanding the collective influence of all touchpoints. For instance, at Sendoso, Kacie leveraged this holistic perspective to reinvigorate outbound sales. By investing in trust-building, strong branding, and thoughtful partnerships, the team shifted outbound calls from cold to warm, creating an environment where sales and marketing aligned seamlessly. The results were tangible, but proving causality required a deeper story, not just a simple report.
She recalls challenging her finance teamâs reliance on last-touch data. When presenting a report that suggested âmore direct trafficâ as the solution, she asked bluntly, âWhat does that even mean?â This moment underscored how reductive metrics fail to capture the true impact of marketing efforts. By shifting the focus to sales-qualified opportunities and long-term patterns, she built trust with stakeholders and steered conversations toward what truly drives growth.
Kacie emphasizes that this broader view isnât fast or easy, and it requires fighting against short-term thinking. Marketers must advocate for strategies that donât immediately show up in last-touch reports but are essential for sustainable growth. She also draws from B2C insights, where buying decisions often happen long before measurable touchpoints, reminding us that customersâ journeys rarely follow a predictable path.
Key takeaway: Attribution isnât about isolating success to one channel or tactic. By combining multiple data sources and focusing on long-term causality, marketers can tell a more accurate story. This approach builds trust with leadership, aligns teams, and justifies investments that might not show immediate ROI but are crucial for sustainable success.
How to Convince Leadership to Rethink MeasurementKacie explains that driving change in marketing attribution and measurement requires aligning cross-functional teams and proving value over time. When she joined Sendoso, the disconnect between sales and marketing created distrust, and outdated metrics like MQLs dominated conversations. To address this, she set clear expectations with leadership: changes would be foundational, require significant investment, and take time to show results. This up-front agreement ensured her efforts had initial backing, though challenges arose as the process unfolded.
A crucial part of the transformation was bridging the gap between marketing and finance. Kacie worked with a finance partner who embraced curiosity, seeking to understand marketingâs perspective by educating himself through webinars and discussions. This mutual respect and collaboration were essential for aligning goals and building trust. She demonstrated that her approach wasnât about gaming numbers or securing credit but about laying a foundation for sustainable growth.
Despite initial alignment, skepticism crept in as foundational workâcleaning up Salesforce fields, rethinking sales stages, and redefining metricsâtook longer to yield visible results. Kacie emphasizes the importance of perseverance during this phase. Companies often lack the patience for foundational changes, cutting le...
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Whatâs up everyone, today we have the pleasure of sitting down with Stephen Stouffer, Director of Automation Solutions at Tray.ai and the first ever returning guest. We had Stephen on earlier in the year in episode 112 where we unpacked the practical wonders of combining AI tools with iPaaS solutions.
Summary: AI can transform your marketing without overwhelming you. Start with one use case. Watch the results, and go from there. You donât need to master data science to add AI value, but you need to be willing to experiment, keep what works, and let the tech do the heavy lifting.
Customer Journey Mapping EssentialsCustomer journey mapping, as Stephen puts it, is best approached as a clear, structured framework. For marketers, this often starts by examining the visitor's first few seconds on a website. Stephenâs âthree, five, seven ruleâ is a useful guide: three seconds to capture attention, five to build engagement, and seven to prompt action. Reviewing homepage or landing page performance through this lens keeps the focus on essentials. Are calls-to-action (CTAs) clear and accessible? Does the page guide users toward the intended outcome effectively?
Stephen further notes the importance of every element âabove the fold.â Content here needs to be concise, visually appealing, and should naturally lead users to the next step. A well-placed CTA, such as a prominent button, encourages forward motion, while a hidden or confusing one can derail the journey. Each interaction should be straightforward and intuitive.
Beyond landing pages, Stephen highlights the journey before a visitor even arrives. Campaign managers, for instance, should ensure that ad copy and visuals align with the landing page, creating a smooth transition from ad to action. Consistency here reduces friction and keeps the experience cohesive.
For advanced mapping, Stephen recommends storyboarding different customer personas and their digital pathways. By tuning each stage to fit these profiles, marketers can craft a journey that feels relevant and trustworthy, engaging each segment from the very first interaction.
Key takeaway: Use the "three, five, seven rule" to evaluate each customer touchpoint on your homepage or landing pages. This approach helps ensure your content captures attention, fosters engagement, and prompts actionâall within a few seconds.
AIâs Role in Automating Personalized Emails
Stephen recently demonstrated how AI automates personalized emails with just a first name, last name, and email. AI uses data from sources like LinkedIn, company details, and job history to craft messages that feel genuinely tailored to each recipient, far beyond typical generic responses.
This level of automation doesn't just boost engagement; it saves significant time. Instead of setting up complex variable fields or spending 15-20 minutes per email on manual research, AI handles it all in seconds. Stephen notes that marketing teams can skip intricate field configurations, while sales teams gain back valuable time to focus on high-impact tasks.
AI also serves as a replacement for traditional enrichment tools, pulling in dynamic contact details without third-party data providers. For sales, it means delivering relevant, personalized content effortlessly. AI does the heavy lifting, creating an email that feels custom-built for the recipientâno manual assembly required.
Key takeaway: AI enables efficient, data-rich personalization for customer outreach, saving marketing and sales teams time and resources while boosting the quality of each touchpoint.
Automating Personalized Outreach with AI AgentsAI agents are redefining how teams approach personalized outreach, offering new ways to automate highly customized interactions. Stephen explains how Tray.ai leverages a powerful combination of APIsâOpenAI, Google, LinkedIn, and moreâto build out complex automation processes directly within its platform. Each AI agent is designed to use the best tool for the task at hand. Given the right context and instructions, these agents can gather relevant data from press releases, Crunchbase, LinkedIn profiles, blog posts, and other sources to craft an email that feels genuinely tailored.
Imagine a marketing email generated entirely by an AI agent. With the recipientâs email, role, and other contextual clues, the AI might produce a message like, âHey, congratulations on your recent speaking slot at AntiCon in London. Hope you had a safe journey back!â This level of personalization would usually require about 15 minutes of research by a BDR or ISR. Now, it can be fully automated, freeing up sales and marketing teams to focus on strategy and high-priority tasks rather than time-consuming data gathering and crafting.
Stephen points out that the true power of AI agents comes from implementing them in real, tangible ways. For instance, rather than abstract promises of efficiency, Tray.ai demonstrates AIâs impact with practical use cases like this automated email personalization, which resonates more directly with the people using it. By creating a functional demo that allows teams to see this technology in action, Tray.ai bridges the gap between AI's potential and its practical application.
For anyone curious to test it out, Stephen offers a live demo of the personalized email automation. This hands-on approach helps users understand the realistic possibilities AI agents bring to customer engagement and outreach, transforming the process from concept to actionable, impactful workflows.
Key takeaway: AI agents streamline personalized outreach, combining data sources and automation tools to generate highly customized emails without manual research. By automating these tasks, teams can focus on high-impact activities while still delivering meaningful, individualized interactions.
Challenges in Implementing AI-Driven Customer Journey MappingImplementing AI-driven customer journey mapping and personalization comes with its share of challenges. Stephen highlights three primary obstacles teams face: complexity, connectivity and compliance.
The technologyâs complexity. Even technical professionals sometimes struggle to understand the nuts and bolts of AI integrations, making it difficult for organizations to determine how to effectively deploy these tools. The ambiguity around building and customizing AI solutions internally often becomes a barrier to adoption.The challenge of data connectivity. For AI agents to deliver relevant outputs, they need access to comprehensive data across systems. Whether itâs a CRM, sales records, or product usage data, these inputs provide the context for AI to make useful recommendations. While crafting a prompt might sound straightforward, gathering and linking all the necessary data to inform that prompt is anything but simple. Stephen explains that AI can only be as effective as the information itâs fed, making seamless data integration a top priority for effective personalization.Perhaps most daunting, the challenge is compliance. When feeding sensitive data into large language models, teams must navigate a maze of security requirements like SOC 2, HIPAA, and GDPR compliance. Many organizations hesitate to dive into AI because of the fear of regulatory risks. Legal teams often step in, concerned abo... -
Whatâs up everyone, today we have the pleasure of sitting down with Nataly Kelly, CMO at Zappi.
Summary: Global expansion is a wild process that connects brands to the unique vibe of each market, itâs not just creating a website or translating content. Every market brings its own needs, from how audiences navigate sites to what resonates visually and emotionally. Moving into international territories means showing up prepared, with a localization strategy thatâs flexible and has a ton of local insight. Marketing Ops and RevOps both play a key role in localization as a strategic partner, organizing data and decision-making to fuel growth across departments.
About Nataly
Nataly started her career as an interpreter at AT&T and later co-founded a research and consulting company which was acqui-hired by her biggest customer where she would serve as Director of Product DevelopmentShe later held Chief Research Officer and VP of Market Development titles at a market research firm and a translation and localization companyNataly then made the mega move to HubSpot as VP of Marketing where she would spend nearly 8 years â involved in all aspects of full-funnel marketing globally, including International Ops and LocalizationShe then moved to Rebrandly as Chief Growth Officer leading sales, marketing and product Natalyâs also an author, sheâs published 3 books and 1 coming out next year, she has a Newsletter called âMaking Global WorkâToday, Natalyâs moved into her 4th SaaS marketing leadership role as CMO at Zappiâthe leading consumer insights platform
Why LinkedIn Works for Building a NewsletterNataly decided on LinkedIn for her newsletter with one primary goal: reaching more people, fast. In marketing, there's always talk of âowning your audience,â but for Nataly, the built-in reach LinkedIn offers outweighed the usual risks. Sure, LinkedIn could shift its algorithm or start favoring video, but Nataly isnât fazed. She believes adaptability is more valuable than control. âIf LinkedIn ever moves entirely to video, I might reconsider,â she says. âBut for now, itâs a writerâs platform, and Iâm a writer.â
What really sold her, though, is LinkedInâs âtriple playâ effect. Each time she publishes a newsletter, her audience doesnât just see it onceâthey get three reminders. The content appears in their feed, triggers a platform notification, and even lands in their email inbox. This multi-touchpoint delivery isnât just convenient; it significantly boosts her visibility. In a crowded digital space, those three nudges are powerful. And the best part? It doesnât take any extra work on her end. For Nataly, this setup is gold: âIf I can reach my audience in three different ways without doing three times the work, Iâm in.â
On top of that, LinkedInâs algorithm has started indexing her posts for keywords, so they pop up in search results long after she hits âpublish.â Nataly likes this longevity. Sheâs seen her posts gather momentum over time, which reassures her that LinkedIn isnât likely to abandon text-based content anytime soon. This layered exposure works in her favor, especially since sheâs already built a solid following on LinkedIn. Her audience is naturally expanding, without any additional ad spend or email list management.
This approach ties back to a guiding principle Nataly picked up at HubSpot: follow the growth. When a channel shows traction, commit fully and ride the momentum. LinkedInâs growth trajectory fits perfectly with her goals, allowing her to spend her time effectivelyâengaging with followers, creating relevant content, and letting the platform do the heavy lifting. âI see LinkedIn growing, and Iâm here for the ride,â she says.
While email newsletters and other platforms might come into play in the future, right now, LinkedIn is her sweet spot. Itâs a low-maintenance option that lets her connect with her community directly, on the platform where sheâs already active. Sheâs writing for the sake of sharing knowledge, and LinkedIn offers a direct, hassle-free way to reach a broad audience without splitting her focus across multiple channels.
Key takeaway: For marketers aiming to maximize reach, LinkedInâs multi-touchpoint setup and organic audience growth make it an ideal platform. When traction is the goal, LinkedInâs notification, email, and feed distribution offer valuable, low-effort exposureâperfect for those who want to focus on content, not channel management.
Understanding the Nuances of Going GlobalNataly makes a clear distinction between "going global" and "going local," a distinction that goes beyond simply putting content online for everyone to see. Launching a website, or even setting up a LinkedIn profile, can technically connect a person to a global audience. But creating an intentional, local connection demands a specific approach, one that carefully considers language, cultural context, and user experience. For Nataly, globalization isnât just about reaching people across bordersâitâs about meeting those audiences where they are, with language and content that resonate.
Her insights stem from years of experience, including her work at HubSpot, where she developed a practical framework to explain these concepts to teams across the company. She found that simplifying these ideas into one-word definitions helped cut through the confusion. For example, âinternationalizationâ is about adapting the technical side, like making code accessible to different languages and regions. This step ensures the foundational structure can support localized content, but itâs just the beginning.
Translation, Nataly explains, isnât about directly swapping words. True translation involves adapting the message itself. For one audience, a particular phrase might evoke excitement; for another, it might fall flat or even offend. Nataly emphasizes that effective translation reaches beyond literal words to convey a message that feels native to each audience, maintaining intent, tone, and cultural relevance.
Localization goes further, adapting the entire user experience for specific markets. It's not just about making text comprehensible but ensuring every interactionâfrom navigation to designâfeels intuitive for users in diverse regions. For instance, a website optimized for American users may assume all visitors speak English, but this model doesnât apply universally. In countries like Canada, India, or across the EU, multi-language realities complicate navigation. This level of adaptation requires deep cultural and technical knowledge to avoid common pitfalls and create a seamless experience.
Globalization, however, is the ultimate adaptation, demanding a complete rethinking of the framework itself. Nataly notes that one of the biggest challenges is getting teams to shift from a single-market mindset to a truly global perspective. A platform initially designed for one language or culture may struggle when stretched to fit a multilingual or multicultural user base. Globalization requires a build-it-right-from-the-start approach, anticipating diverse user needs and ensuring the platform can expand without limitations.
Key takeaway: Successful globalization is about more than just reaching an international audience; it requires intentionally adapting every layerâfrom code to experienceâto create content that resonates locally while remaining accessible globally.
Strategic Timing for Going GlobalWhen HubSpot considered expanding internationally, it wasnât about leaping into new markets; it was about waiting until the timing and resources aligned. Nataly recalls that CEO Brian Halligan was deliberate, even drafting a Harvard Business Review piece outlining Hu...
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Whatâs up everyone, today we have the pleasure of sitting down with Jim Williams, CMO at Uptempo.
Summary: Forget version control spreadsheets and stale budgets, Jimâs take on marketing planning is about putting purpose behind every dollar. Instead of throwing darts at a board, focus on creating a blueprint that connects goals to actual business impact. For him, goals shouldnât be handed down from the top like a royal decree but hammered out together with practitioners so theyâre ambitious⊠but you know, grounded in reality. Marketing Ops pros are the unsung heroes, bringing sanity to the madness with data and KPIs that keep every piece aligned. Plus, AIâs set to take over the boring bitsâupdating data, tracking budgets, making sure no dollar gets lostâleaving marketers free to do what they do best: make real magic happen.
About Jim
Jim started his career in PR and Product Marketing before spending 7 years at Eloqua as Sr Dir of Product Marketing and helping the company rise from 15M ARR to 92M and IPO. He later moved on to Influitive â the popular advocate marketing platform â as VP of Marketing where he helped grow the company from pre revenue to 12M in ARRHe then moved over to the DNS world as Snr VP of Marketing at BlueCat where he led all facets of marketingHe then became CMO at BrandMaker which has since rebranded to Uptempo, the leading enterprise marketing operations software that helps marketers plan better, spend smarter and execute with confidence.
What Is a Marketing PlanJim dispels the idea that marketing planning should be like âthrowing darts at a dartboard.â A marketing plan isnât a guessing game; itâs a strategic framework for how teams tackle the future. One of the most common mistakes Jim sees? Dusting off last yearâs plan and rebranding it for the new year. This tactic, he argues, is the quickest way to stay stuck. In a world that demands fresh thinking, relying on past strategies doesnât cut it.
The old-school concept of a âpivotâ has taken on a new life in marketing. Itâs no longer about just one big strategy shift but about building in constant adaptability. Jim suggests that, unlike traditional yearly plans, todayâs marketing requires continuous recalibration. The best teams arenât just agile onceâtheyâre agile all the time. That flexibility to assess, pivot, and refine isnât a luxury; itâs the core of modern marketing planning.
Another common pitfall Jim highlights is the habit of dividing up the budget before solidifying a game plan. For too many teams, budget allocation is seen as the end goal rather than just a piece of the puzzle. Getting the numbers in place is just step one, not the entire strategy. A plan isnât simply a breakdown of costs; itâs the strategic âwhyâ and âhowâ behind each dollar spent. Without defining the intended outcomes, budgets lose meaning.
Jim makes an essential distinction: budgets support the mission, but plans set the course. The budget tells you whatâs possible financially, but the plan clarifies what needs to be achieved. This separation between resources and goals keeps marketing teams focused, providing a framework to measure success rather than just track expenses. With a clear strategy in place, budgets go from static numbers to dynamic assets driving real outcomes.
Key takeaway: A budget is just a set of numbers; a marketing plan is the vision behind those numbers. By keeping intent at the forefront, teams can transform budget allocations into impactful actions, staying adaptable and ready for whateverâs next.
Building a Marketing Plan That Aligns Top-Down and Bottom-Up GoalsJim dives into the complexities of planning in a large organization, pointing out that itâs not a matter of simply setting goals at an offsite retreat. At the enterprise level, planning is a detailed, phased, six to nine-month process. Yet, he notes that surprisingly few accessible resources break down this method. For many marketers, planning seems shrouded in mysteryâa skill theyâre expected to learn on the job, often after theyâve already taken on leadership responsibilities.
Jim explains that marketing planning often starts with annual, top-down forecasts. This approach provides broad company objectives, which interlock with a bottoms-up plan in later stages. Rather than seeing top-down and bottom-up planning as opposing methods, Jim views them as stages in a coordinated approach. At Optempo, theyâve formalized this method in a seven-step âblueprint for marketing planningâ to guide teams through each phase. This blueprint begins with setting overarching company objectivesâdetermining whether the focus is on market expansion, product launches, margin improvements, or even mergers and acquisitions. Until these objectives are set, marketing teams canât start defining specific growth tactics.
Once top-level objectives are clear, Jim explains that the marketing team distills them into a focused âplan on a page,â a roadmap outlining how marketing will support each objective. This document serves as a communication tool, clarifying what marketing intends to achieve and aligning these goals with company-wide expectations. According to Jim, defining these specific objectivesâwhether they involve selling to new buyers, entering fresh markets, or optimizing existing processesâis foundational for cohesive planning.
Jim also breaks down the budget allocation process, which directly follows the plan on a page. This is where marketing teams work with finance to divide funds, categorizing costs into programmatic and non-programmatic expenses, as well as campaign-based and non-campaign-based spending. By grouping expenses into clear, high-level âbuckets,â Jim explains, teams ensure their budgets align with strategic priorities and company-wide financial targets.
Key takeaway: A successful marketing plan balances top-down objectives with bottom-up execution. Begin with high-level company goals, then translate them into actionable steps and align budget allocations accordingly. This approach ensures that both strategy and resources are directed toward achieving meaningful impact.
Why Marketing Goals Need to Be a Two-Way ConversationJim counters the misconception that company goals are simply handed down from a closed-door board meeting, with marketers then left scrambling to hit those targets. He clarifies that in most forward-thinking companies, the setting of financial objectives isnât a secretive, top-down affair. Instead, itâs a dialogue involving senior leadership across all departmentsâincluding marketing. When the ownership of a business, be it public shareholders or private investors, establishes financial ambitions, these arenât randomly assigned numbers; theyâre set with input from an executive team that includes the CMO or head of marketing.
Jim explains that technology companies, for example, often focus on maximizing valuation. The board or ownership group typically benchmarks these goals using standards like the âRule of 40ââa common framework in SaaS that blends growth rate and profitability. But these objectives are usually part of a larger, multi-year vision, not just a single-year target. Once these broad metrics are set, the board works backward to define the current yearâs objectives. From there, itâs up to the executive team, including marketing leadership, to devise the most effective strategies to meet these targets.
Jim emphasizes that marketing isnât just a passive recipient of goals. Marketing leadership works closely with other executives to determine how marketing can help hit specific benchmarks. Itâs at this stage that the conversation turns practical. For instance, if a company needs a particular level of market penetr...
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Whatâs up everyone, today we have the pleasure of sitting down with Barbara Galiza, Growth and Marketing Analytics Consultant.
Summary: Attribution is a bit like navigating Amsterdamâs canals: mesmerizing but full of hidden turns that donât always make sense. You donât need to chart every twistâjust focus on finding the direction that moves you forward. Instead of obsessing over every click, use attribution like a compass, not a GPS. Multi-touch attribution (MTA) gives you some of the story, but often misses those quiet yet powerful nudges that drive real decisions. Layering in rule-based or incrementality testing can fill the gaps, giving a clearer picture of whatâs driving your wins. For startups, itâs even simpler: stick to whatâs working and forget complex attributionâqualitative feedback is often the best guide in the early days. Data doesnât need to be perfect, just practical, and sometimes trusting that a strategy is working is enough to keep pushing it.
About Barbara
Barbara was an early employee at Her (YC), the biggest platform for LGBTQ women where she would eventually become Head of GrowthShe was also Head of Growth at different startups like Pariti and HomerunShe worked at an agency where she led data and analytics for Microsoft EMEABarbara then went out on her own as a GTM and Analytics consultant for various companies like Gitpod, WeTransfer, Sidekick and dbt LabsShe has a newsletter on marketing data: 021 newsletter.She produces content for data brands (dbt, Mixpanel, Amplitude) like case studies and webinars
Building Data Literacy Through SQLData literacy is essential for modern marketers, but it doesn't have to be intimidating. Barbaraâs advice is simple: learn SQL. While marketers today are surrounded by user-friendly tools and drag-and-drop interfaces, those who want to truly grasp their data should get comfortable with SQL. Itâs not about becoming a data engineer but about understanding how the numbers you rely on every day are built. SQL helps you see how data connects, how itâs organized, and how you can group it to make sense of whatâs happening in your campaigns.
Whatâs great is that you donât need to dive into formal classes or certifications. Start where you are. Most companies are sitting on a goldmine of structured marketing data, whether itâs Google Analytics data in BigQuery or Amplitude events stored in a data warehouse. The next time youâre building a report, try using SQL for a small part of the process. Itâs a skill that compounds over time. Once you get familiar with the basics, youâll start to see data in a different way, and youâll be able to spot insights faster.
Barbara also points out a crucial, often overlooked skill: understanding why your tools give credit to certain campaigns. Why does one Facebook ad outperform others in your reports? Why does Google Analytics attribute more conversions to certain sources? Getting to the bottom of these questions puts you in a much stronger position as a marketer. If you can explain how attribution models work and why certain data points appear, you're already ahead of most.
At the end of the day, itâs about making smarter decisions. Barbara believes that marketers who can confidently say, âI know why these numbers look the way they do,â are in the top 10% of data-driven marketers. Itâs not just about collecting data; itâs about making sense of it and using it to steer your strategies.
Key takeaway: Learning SQL gives marketers the power to truly understand their data. Starting small, even with basic queries, can unlock a deeper understanding of how marketing data is structured and why campaigns perform the way they do. The key is to build practical skills that help you make more informed decisions.
Rethinking Attribution and Understanding Its Role in MeasurementBarbara brings clarity to two commonly conflated concepts: attribution and measurement. While many marketers default to thinking of attribution as purely click-based or multi-touch attribution (MTA), Barbara challenges this view. She argues that attribution goes beyond just tracking clicks and touches throughout a customerâs journey. Itâs about understanding the overall impact of marketing effortsâwhether through incrementality tests, media mix modeling (MMM), or holdout groups. Attribution is meant to explain how marketing drives results, but itâs not the only tool for assessing campaign success.
MTA, particularly click-based models, excels at measuring bottom-funnel actions like search marketing, where high-intent users click on an ad and then convert. This method works well for campaigns that rely on clicks to move the needle. However, Barbara notes that it has its limitations, especially when it comes to non-click-based channels like video or display. MTA often over-credits search campaigns because thatâs where the conversion is tracked, but it misses the broader influence of awareness-building efforts. In essence, MTA can tell you what happened after the click, but not what inspired it in the first placeâbe it a podcast mention or an engaging piece of content seen days before.
On a broader level, Barbara explains that attribution is not the same as measurement. Attribution focuses specifically on tying marketing efforts to business results, such as leads or revenue. Measurement, on the other hand, casts a wider net. It includes performance across various metrics, not just conversions. For instance, measuring how well different messaging resonates with audiences is crucial, but it doesnât always directly lead to immediate sales. Measurement can inform future strategies by offering insights into engagement, customer preferences, and channel effectiveness.
As Barbara sees it, attribution is a subset of measurement. Itâs a tool for understanding what drives business outcomes, but it shouldnât be the only tool marketers rely on. For example, MTA has its place but should be used alongside other models like MMM to paint a fuller picture. Measurement, meanwhile, helps marketers assess the effectiveness of everything from messaging to customer touchpoints, beyond just the end goal of conversion.
Key takeaway: Attribution is one piece of the measurement puzzle, focusing on business outcomes, while measurement encompasses a broader range of insights. Marketers should use a mix of attribution models to understand their campaigns and apply measurement tools to gain a holistic view of performance.
Limitations of Multi-Touch Attribution in Credit DistributionMulti-touch attribution (MTA) is often seen as a way to distribute credit across different customer touchpoints, but Barbara questions its effectiveness in this role. She argues that MTA is inherently limited because it only attributes credit to interactions that involve a click. This creates a skewed view of the customer journey, where only click-driven strategiesâlike search adsâare recognized, leaving other key touchpoints, like connected TV (CTV) or social media, out of the equation. The result is a narrow perspective that doesn't capture the full influence of various channels.
Barbara points out that for marketers to make better decisions, MTA needs more than just click data. One alternative she suggests is pairing MTA with rule-based attribution models, where data from "How did you hear about us?" surveys are integrated into the analysis. This way, marketers can capture insights from channels that donât typically generate clicks but still play a crucial role in driving awareness or consideration. By adding this type of first-party data, businesses get a broader understanding of whatâs really influencing their customers.
Some data agencies are also experimenting with es...
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Whatâs up everyone, today we have the pleasure of sitting down with Steven Aldrich, Co-CEO and Co-Founder at Ragnarok NYC.
Summary: Like the aftermath of Ragnarök according to Norse mythology, the martech world is emerging stronger, more focused, and ripe with potential. Rather than being overwhelmed by the chaos, marketers should use this time to rethink how to evaluate technology choices through the lens of business value. Prioritize platforms that drive real-world impact and avoid getting lured by features that blaze brightly for a moment, only to be swallowed by the tide of irrelevance.
About Steven
Stevenâs first job out of business school was a customs broker in Colombia, before his Visa ran out and he was forced to return to the US He started his marketing career as a Marketing and Comms Associate at a market research firm where he discovered the wonders of HTML, email development and Adobe dreamweaverWhile continuing his full time in-house career working in email and CRM roles for different industries, Steven and his co-founder Spencer launched Ragnarok, first as a side hustle where they spent their evenings moonlighting as marketing technology consultantsIn 2017, both co-founders decided to take the leap and go all in on their agencyToday Ragnarok is a 50+ person full service martech agency thatâs helped well known brands like zapier, dropbox, asana, adobe and many more!
The Evolution of Martech and the Impact of ConsolidationWhen asked about the future of martech, Steven immediately highlighted the ongoing consolidation in the industry. He pointed to acquisitions like Twilio snapping up Segment and Salesforce expanding its Customer Data Platform (CDP) offerings as clear signals. According to Steven, these moves indicate that weâre in the midst of a reshuffling phaseâone that will shape how martech platforms are built and used over the next decade.
However, itâs not just about merging and acquisitions. Steven sees the next wave of growth stemming from generative AI. This technology, while still in its infancy for many organizations, will soon be as fundamental as marketing automation tools were a decade ago. Platforms are experimenting with Gen AI features like automated content creation, but theyâre still scratching the surface. âRight now, a marketer isnât likely to sit down and have their AI tool write an entire creative brief,â Steven noted. âBut once the tech reaches a level where itâs drafting briefs and campaign strategies, itâll fundamentally change what marketers do day-to-day.â
He also predicts that the next few years will separate the genuine innovators from the rest. Startups focusing on AI-powered automation and advanced integrations will emerge as key players. Those that fail to embrace this trend will struggle to maintain relevance. Steven pointed to companies like Castle.io as an exampleâa newer entrant that has managed to make a name for itself by rethinking traditional automation and going all-in on a warehouse-first approach.
Looking ahead, Steven envisions a future where marketers become more like strategic curators rather than operators. Instead of creating every campaign element manually, marketers will outline goals and high-level structures, and let the tools figure out the rest. âThink of a platform where you set your conversion goals, outline your audience, and the tool builds the journey for you,â he explained. Some companies are testing these capabilities internally, but weâre still far from a world where itâs the norm. To reach that stage, platforms need to overcome significant technical challenges and gain marketer trust.
Ultimately, Steven believes that by the ten-year mark, the martech industry will look entirely different. The focus will shift away from basic integrations and automation to more complex AI-driven orchestration. Platforms will evolve into decision-making engines, allowing marketers to focus on strategy, creativity, and innovation, leaving the grunt work to the machines.
Key takeaway: The martech industry is undergoing a consolidation phase as it readies itself for the next wave of innovation: generative AI. Startups that embrace AI-driven automation will emerge stronger, while legacy platforms must integrate these new capabilities or risk becoming obsolete. In the next decade, marketers will transition from hands-on campaign execution to strategic oversight, as tools handle more of the complex work autonomously.
Blending Automation with Human Spark for Smarter Martech StrategiesWhen it comes to AI and automation in martech, thereâs a spectrum of opinions. On one end, some marketers insist that only a human can truly understand and engage their audience. On the other end, thereâs a growing camp eager to hand over the repetitive tasks to machines and focus on strategy. Steven pointed out that the real value lies in finding a balance between the two extremes, especially for industries with strict compliance requirements like FinTech and health tech.
Steven used abandoned cart programs as a foundational example of automationâs role in marketing. Not long ago, these campaigns were inconsistent and cumbersome. Companies like Klaviyo and Shopify stepped in, making abandoned cart emails table stakes for eCommerce. Now, if you abandon your cart, you can almost predict when youâll receive that follow-up email offering a discount or reminder. âItâs just expected,â Steven explained. He believes this kind of automated functionality has become the baseline for what customers and marketers alike view as the norm.
But not every industry can afford to automate at that level. With sectors like finance or healthcare, thereâs a need for humans to review and validate messages for compliance. âA legal person is at the end of every review,â Steven said. âItâs frustrating and time-consuming, but the cost of sending the wrong message at the wrong time is just too high.â He sees these industries gradually adopting AI where they canâincremental optimization, message testingâbut keeping a human in the loop for quality assurance.
The evolution of martech, in Stevenâs view, will be about advancing beyond these early stages. He predicts that the future will bring a seamless integration where humans set high-level goals, and AI takes care of execution. The role of the marketer shifts from managing individual campaigns to curating experiences and setting strategic parameters. Some platforms are already testing these capabilities, but theyâre far from ready for mainstream adoption. âImagine a future where marketers simply set their audience, goals, and content, and the tool builds the entire journey for them,â Steven envisioned. This approach would redefine what it means to be a marketing operator, giving professionals more time to think strategically rather than tactically.
Ultimately, Steven sees the evolution of martech as an interplay between speed and quality. Some companies will succeed by automating faster, launching multiple initiatives, and iterating based on outcomes. Others will opt for a more deliberate approach, spending more time crafting the perfect message. âThere isnât one clear winner,â Steven concluded. âItâs about choosing the right tool for the job and understanding whatâs at stake when the human element is minimized.â
Key takeaway: Martechâs future lies in balancing automation with human oversight. While some industries can embrace full-scale automation, others need humans in the loop to maintain compliance and quality. Marketers must choose tools that fit their strategic goalsâwhether thatâs rapid iteration or precision crafting.
The Value of Data Science in Martech OptimizationWhen asked about the role of data science in marketing operations, Steven was quick to point out the di...
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