Humans of Martech

What’s up everyone, today we have the pleasure of sitting down with Adam Greco, Field CTO / Product Evangelist at Amplitude.

Summary: Adam is a leading voice in digital analytics and he unpacks event-based analytics and how it’s transformed how marketers interact with data. Data tools are complicating the martech landscape with overlapping functionality and confusing terminology so Adam breaks down the nuanced difference between product analytics, customer data infrastructure and ETL. Adam also walks us through how his team combines marketing, product, and experience analytics getting a fuller view that informs smarter, more effective strategies. We also cover the shift to interactive dashboards as well as warehouse native martech and what it means for marketers. Marketers need to work closely with data teams to ensure these new tools are practical without being overwhelmingly complex, allowing them to lead confidently in their industries.

About Adam

• Adam is one of the leading voices in digital analytics
• He’s managed marketing and customer success teams at enterprise companies and consulting firms
• He’s been Senior Director of Marketing and Analytics at Salesforce
• He spent nearly a decade as a Senior Partner at one of the best-known analytics consultancies in Analytics Demystified where he’s advised hundreds of organizations on analytics best practices
• He’s been a Board Advisor at various well-known startups, analytics associations, capital funds and universities
• He’s authored over 300 blogs and one book related to analytics
• He’s a frequent speaker at big-name analytics conferences
• Today he’s Field CTO at Amplitude, where he focuses on providing content, education, and strategic advice on how to build better products

Understanding Event Based Analytics

Adam unpacks the shift towards event-based analytics, a concept that may seem confusing to those accustomed to traditional digital analytics. He explains that back when the internet was simpler and mostly about websites, tracking was straightforward: look at pageviews and sessions and hope for conversions. But as technology evolved—think smartphones and apps—the old methods became less effective.

Mobile apps changed the game. Interactions on these platforms are brief and frequent, shifting the focus from long sessions to brief, meaningful interactions, each marked as an event. Adam points out that his company, Amplitude, was at the forefront of adopting this approach, realizing that tracking every tap and swipe gave a clearer picture of user engagement than the traditional methods.

As both websites and apps became integral to user experience, the analytics field faced a choice: stick with the old or adapt to the new. The answer was overwhelmingly in favor of event-based analytics. Major players like Google and Adobe redefined sessions as just another event, creating a unified model that could track interactions across platforms, be they digital or physical, like visiting a store or calling customer support.

This evolution means marketers can now see a fuller, more dynamic view of how users engage across different platforms. Understanding that a session is a collection of events, rather than a fixed time slot, offers a richer, more nuanced understanding of user behavior.

Key takeaway: Embracing event-based analytics allows marketers to capture the full spectrum of customer interactions, offering a granular view that is vital for crafting targeted, effective marketing strategies. This approach not only keeps pace with the evolving tech landscape but also provides the insights needed to enhance customer engagement and satisfaction.

Product Analytics vs Customer Data Infrastructure vs ETL

Adam explains the evolving landscape of martech tools, focusing on how they intersect and differ, simplifying a topic that can be quite bewildering for even experienced marketers. Initially, the task for marketers was to employ simple tools provided by companies like Google or Adobe, which handled data collection via embedded codes on websites or apps. These tools offered convenience but at the cost of flexibility and depth in data manipulation.

With the advent of more specialized tools, the dynamics changed. Customer Data Infrastructure (CDI) tools like Jitsu, MetaRouter, and Rudderstack focus mainly on collecting first-party data from apps and websites, pushing this information directly into data warehouses. They don’t delve into analytics but excel at gathering clean, structured data.

On the other hand, Extract, Transform, Load (ETL) tools such as Airbyte and Fivetran specialize in integrating data from various third-party tools into a central warehouse. They transform the data during this process to ensure it fits well within the existing structures and sc...

What’s up everyone, today is our last episode of the year and if you paid attention to the intro, I’m 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

Darrell’s 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 podcast—a 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, they’ve quickly discovered that babies don’t operate on predictable timelines. Moments of progress—like better sleep—often take a step back as developmental leaps shake up routines. While the lack of rest is taxing, Darrell’s 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 Databases

Okay... 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 shocking—after 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 doesn’t 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 team’s data work revolves around ensuring consistency across these copied datasets—a 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. It’s a radical departure from the status quo but one he believes is inevitable as teams demand greater agility and accu...

What’s up folks. We’ve got a fun episode today. If you’re a regular listener, you’ve heard me mention an article that’s been living rent free in my head for a while now.

Casey Winters, the former CPO at Eventbrite and an Instructor at Reforge, wrote an article titled “The Problems With Martech, and Why Martech is Actually for Engineers”. I’ve asked a lot of recent guests what their thoughts were on some of the arguments raised in the article. So today we’re going to respond to his claims.

Summary: Should you buy a 3rd party martech solution or build your own in-house tool, the answer is almost always buy. Let your in-house engineers focus on product and data while leveraging the cutting-edge solutions and support offered by specialized martech vendors. Unless you’re planning on building a martech company, leave the martech to the experts. Homegrown tools aren’t appealing to marketers, they’re hard to scale, most have a shitty UI and it’s not a recognisable martech tool you can add to your resume. Not only are homegrown martech tools not appealing to marketers, they are even less appealing to engineers. Engineers can’t stand the chaos of marketing and effective martech implementation requires collaboration between engineers and marketers, highlighting the need for cross-functional translators and disproving the claim that martech is actually only for engineers.

Martech Has Continued to Explode as a Category

So the article we’re debating was written in 2019, that’s 5 years ago. That’s a boatload of time in martech so we can’t fault the author too much and I respect his bold claims. He starts off by stating:

“I hate martech, and think martech will decline as a category, and most martech businesses will not be very successful.”

Now we could spend a whole episode disproving this prediction... but obviously we have 5 years of hindsight.

But it is worth mentioning that he made this prediction on the year (2019) where the martech landscape exploded past 7,000 tools. Pretty bold to claim that it will decline as a category given the meteoric rise of tools up from only 350 in 2012. Scott Brinker recently released the state of martech in 2024 report which his team says they’ve seen the “largest number of new apps added to the martech landscape in the 13 years they’ve been curating it: net new growth of approximately 3,000 new tools.”

We’ve crossed 13,000 tools, nearly doubling the landscape from 2019 when Casey made his “bold prediction” that martech will decline as a category.

Number of tools isn’t the only way to evaluate whether martech has declined or not.

I’m not a big fan of Gartner reports but if that’s a more trusted source for you, they reported that in 2023 client organizations spent over 1/4 of their marketing budgets on technology. In terms of VC investments, LUMA reported a steady rise in martech acquisitions in Q3 of 2023, averaging over 40 per quarter, alongside substantial capital inflows into new ventures. This financial backing underscores confidence in the industry's future​​.

Okay... so Casey was wrong about martech declining as a category. But he did have some interesting arguments about why.

His main thesis is that: Martech faces decline due to in-house engineers who are increasingly handling tailored solutions in-house, and the success of vendors hinges primarily on serving those engineers, not marketers.

I’ve asked 8 recent guests on the podcast to read Casey’s article and share their thoughts.

What’s your take on this? Is martech actually for engineers?

Homegrown Marketing Technology Isn’t Attractive for Marketers or Engineers

Martech Just Isn’t that Appealing for Most Engineers

Vish Gupta, Marketing Operations Manager at Databricks shared her perspective on whether martech is truly designed for engineers, challenging pretty much every single one of Casey’s viewpoints.

She started by expressing her disagreement with the idea that martech will decline due to competition from in-house engineers and platform limitations. "I don't think martech is the sexiest thing for an engineer to do," she noted. Vish argued that talented engineers building martech are more likely to work for CRM companies to enhance their products rather than find in-house martech development appealing.

Vish explained that building a CRM in-house is often not the best approach. She emphasized that knowing popular systems like Customerio, Marketo, and HubSpot adds more value. She questioned the practicality of finding the right talent for in-house solutions, given the complexities and specialized skills required.

Regarding the idea that successful martech companies cater primarily to engineers, Vish disagreed. "Martech teams are actually part engineer, part product marketer, part IT person, part biz ops," she said. She believes ...

What’s up everyone, today we have the pleasure of sitting down with Jared DeLuca, Director of Operations at Appcues.

Summary: Jared takes us inside the mad but amazing world of martech at Appcues – the top product adoption SaaS on the planet. We cover his transition from demand gen to ops, how he’s integrated demo bookings within the product using RevenueHero, the difference between ops and revops. We also cover a ton of ground on AI topics for marketers like machine learning lifecycle management, how to QA AI-driven messages and how to leverage AI to uncover incremental lifts in your campaigns.

About Jared

• Jared started his career with a few internships in PR before joining a Market Research firm
• That firm was later acquired by a UK based marketing data and analytics company where he worked his way up to Marketing Manager
• He then had a brief detour from SaaS at Keurig Dr Pepper in IoT Marketing Automation and Connected Panel Ops
• Finally Jared landed at Appcues, first in Demand Gen then Senior Martech and Ops Manager
• Today Jared is Director of Operations at Appcues

Moving from Demand Gen to Front-End Development

Jared’s shift from demand generation to front-end development was a mix of opportunity and curiosity. When his team’s operations lead left, he stepped in naturally. As the demand gen guy who relied heavily on those systems, Jared was the most logical choice. It wasn’t a calculated career move—it was about filling a gap. That’s how things go in startups, where you often find yourself doing a bit of everything.

His transition into front-end development had a different spark. Budgets were tight, and they didn’t have the luxury of hiring contractors. With years of HTML and CSS experience under his belt from working on emails and landing pages, Jared figured he could handle some of the coding work. AppCue supported the idea, allowing him to stretch into JavaScript. For small teams, having someone in-house with a broad skill set is invaluable, and Jared was more than willing to step up.

What made this shift special was Jared’s personal interest in coding. He enjoyed it. Coding wasn’t just a job; it was something fun to experiment with. One evening, while watching TV, he built a lead-gen magnet prototype in just an hour. It was born from a simple idea pitched by the content team, but Jared’s ability to quickly turn that into a working model showed the kind of spontaneous creativity that startups thrive on. The prototype may soon go live on their website.

Jared’s experience highlights the unpredictable nature of roles in smaller companies. You often find yourself taking on responsibilities you never planned for, and those unexpected opportunities can lead to new skills and career growth. For him, it wasn’t about following a clear path—it was about being adaptable and ready to learn.

Key takeaway: In a startup, being adaptable and willing to learn new skills can lead to unexpected career opportunities. It's less about having a perfect plan and more about being open to filling gaps when they appear.

How AI Tools Are Shaping HTML and CSS Learning

When asked if tools like ChatGPT make learning HTML and CSS easier today, Jared didn’t hesitate to agree. He pointed out how much simpler it is for anyone looking to pick up coding now compared to when he started. Back then, you had to figure things out manually, while now, AI tools can assist with the heavy lifting. However, there’s a caveat—knowing what to ask for is still crucial.

Jared challenged the idea that AI is replacing developers. Instead, he emphasized that understanding the underlying structure of HTML and CSS is still key. Tools like ChatGPT can help speed up the process, but without knowledge of where to apply that code, the benefits are limited. AI can’t tell you how to structure a website; it can only help fill in the blanks once you know what you need.

He highlighted that while AI can handle repetitive keystrokes, the real value comes when you already know what you're aiming for. It’s not about AI replacing junior developers—it’s about leveraging these tools to work more efficiently. If someone understands the basics of coding and web structure, AI can cut down the time it takes to implement those tasks significantly.

For Jared, the most significant takeaway is how much time he saves. What used to take him hours can now be done in minutes with AI. The difference is in the efficiency, not the replacement of skill. If you know what you're doing, ChatGPT and similar tools become an incredible resource for improving speed and output, but they don’t replace the need for foundational knowledge.

Key takeaway: AI tools can dramatically speed up coding tasks, but the real advantage comes when you already understand the basics of HTML and CSS. It’s not...

What’s up everyone, today we have the pleasure of sitting down with Lourenço Mello, Product Marketing Lead at Snowflake.

Summary: Lourenço drops us straight into the gravity well of martech, where Snowflake’s latest report pulls in the tools that really matter, letting the fluff float away. It’s all about data gravity, bringing the applications to the data instead of wasting energy shuttling data around. This shift is redefining what’s possible, streamlining operations, and giving marketers a new superpower to harness the forces of AI and analytics. With composability blurring boundaries and AI breaking down silos, the takeaway is crystal clear: master data quality and you’ll have the gravitational pull to outpace the competition.

About Lourenço

• Lourenço started his career at an enterprise telecom company based in Portugal where he dabbled in competitive analysis, pricing and biz dev
• He later completed his MBA at UCLA and then spent 5 years at Microsoft as a Senior PMM focused on Azure and their data business
• Today, Lourenço is Product Marketing Lead for the Solutions team at Snowflake

Understanding the Marketing Data Stack Report Methodology

Lourenço’s perspective on Snowflake’s Marketing Data Stack Report centers around a fundamental commitment to objective analysis. Rather than focusing on internal partnerships or pushing favored solutions, Snowflake’s report leverages comprehensive telemetry data to identify which tools are truly gaining traction among its 8,000+ customers. This approach enables them to deliver a more impartial view of the martech landscape.

The methodology starts by categorizing the landscape according to current trends and customer adoption. Snowflake first identifies the relevant categories that its customers are using for marketing use cases, based on a snapshot of the industry. Lourenço emphasized that the analysis isn’t limited to tools with direct business relationships or joint ventures but looks holistically at the adoption metrics across the board. This objectivity sets the report apart, as it can spotlight tools that Snowflake hasn’t actively partnered with—yet are clearly valuable to their customers.

Two primary metrics guide the analysis: breadth of adoption and depth of adoption. Breadth measures how many customers are using a particular tool or solution, offering an initial view of popularity. However, without understanding how deeply those tools are being utilized, breadth alone can be misleading. Lourenço highlighted that a platform may have thousands of users but very minimal actual engagement. Thus, the second metric—depth of adoption—assesses how sophisticated the usage is within each customer’s implementation, revealing the true stickiness and impact of the tool.

By indexing both breadth and depth of adoption, Snowflake is able to create a ranked list of tools and platforms within each category. This process ensures that the final report is rooted in genuine customer behavior and preference, rather than internal biases. As Lourenço puts it, “the cool thing about this and really what's been so fun to be a part of is really the objectivity of the analysis.” The report not only highlights tools that are already well-integrated but also uncovers opportunities to build relationships with platforms that customers have independently gravitated towards.

This level of transparency ultimately fosters stronger collaboration between Snowflake and its partners. By showing where their customers are seeing success, the report opens the door for potential go-to-market initiatives that were previously unexplored. In a martech landscape often clouded by promotional bias, this approach offers a rare glimpse into which technologies are truly making a difference.

Key takeaway: The core strength of Snowflake’s Marketing Data Stack Report lies in its objectivity. By focusing on customer adoption metrics and removing subjective biases, the report provides a clearer view of the tools that are genuinely resonating with the market. This methodology enables Snowflake to support its customers with data-driven insights, and it paves the way for more meaningful partnerships with emerging leaders in the field.

Key Shifts Defining Martech and AdTech Today

When asked about the notable shifts between 2023 and 2024, Lourenço from Snowflake made it clear—what were once considered trends are now fundamental changes that have reshaped marketing. Last year’s report pointed to themes like the convergence of AdTech and martech, data privacy, generative AI, and the pursuit of a single source of truth. This year, these aren’t just trends—they’re seismic shifts that have permanently altered how the industry operates.

Instead of being temporary developments, Lourenço emphasized that these themes are “not going away,” likening them to the foundation ...