Exploring Methodology Behind the Marketing Data Stack Report

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 of the industry itself. The report identifies three key forces driving transformation: data privacy, data gravity, and generative AI. These forces influence everything from how companies measure performance to how they monetize and manage first-party data. One of the more interesting dynamics highlighted this year is the emergence of commerce media, where industries traditionally characterized by thin margins—like retail and travel—are leveraging their vast pools of first-party data to unlock new revenue streams and drive higher profitability.

Data gravity, in particular, is a crucial concept. It describes how data is increasingly becoming the central point for both martech and AdTech activities. As Lourenço points out, brands are now using the same data source for real-time bidding on the AdTech side and for personalized experiences on the martech side. This convergence is made possible by advancements in data infrastructure, such as Snowflake’s native app framework. By allowing applications to run where the data resides, brands eliminate the need to move data back and forth, reducing latency and improving privacy. An example Lourenço shared involved identity resolution, where an eight-day process to reconcile identity data is now achievable in mere hours, sometimes even minutes, thanks to this infrastructure shift.

Another powerful change mentioned was how companies are transforming their roles—from being purely ad buyers to becoming ad sellers. This shift, Lourenço explains, is a direct consequence of organizations capitalizing on the value of their first-party data, looking to move up the value chain by creating new revenue channels through data monetization. Meanwhile, customers are increasingly interested in Marketing Mix Modeling (MMM) and other approaches to understand and optimize their media investment in light of these shifts.

The takeaway is clear: these are not passing trends but fundamental changes in how the industry functions. Snowflake’s position at the intersection of martech and AdTech provides a unique vantage point to observe these developments, and Lourenço’s insights offer a glimpse into the future of data-driven marketing.

Key takeaway: The convergence of data privacy, data gravity, and generative AI are not just fleeting trends—they’re transformative forces that are redefining the marketing landscape. Brands that align their strategy with these shifts can unlock new revenue streams, capitalize on efficiency gains, and strengthen data security, ensuring they stay ahead of the curve.

The Concept of Data Gravity in Modern Data Architecture

When Lourenço introduced the idea of data gravity, it wasn’t just about centralizing data; it was about rethinking how applications interact with it. The term itself evokes a sense of drawing everything—data, applications, and processes—toward a unified center. But in a broader sense, Lourenço emphasized that it’...