The Evolution of Digital Analytics: Not a Revolution, But a Revelation

In recent weeks, Adam Greco’s move from Amplitude to Hightouch has reignited a familiar question in our community: “Where is digital analytics headed?” While this career move might not appear newsworthy, it signaled something notable within the digital analytics world.

For context, Greco is a leading voice in a field filled with “influencers”—the acclaimed author of the definitive book on Adobe Analytics and a thought leader whose past role moves often reflected broader industry shifts. His transition from Amplitude (a product analytics platform that has increasingly positioned itself as a marketing analytics solution) to Hightouch (a “Composable CDP” focused on integrating data spanning not just digital sources, but offline) represents more than just one person changing jobs.

This move reflects a larger story about the evolution of digital analytics itself. And it prompts an important question: Is digital analytics truly transforming, or is the broader industry finally catching up to possibilities that practitioners have recognized all along?

The Perception Gap

Digital analytics has always been seen as a necessity—nearly 30 million websites run Google Analytics today according to BuiltWith, a good indication of the global scale of this “necessity” given Google Analytics’ continued market dominance. Yet necessity doesn’t translate to understanding value. At Drumline, we consistently encounter more companies looking to “fix” their web analytics because “the data is wrong” than those happy with their implementations and eager to explore advanced use cases to drive even more business value. We see more sites with basic tracking codes hastily added to their websites than those with properly structured measurement frameworks designed to capture meaningful business context and customer insights.

So the potential value of digital analytics as an integrated source in a broader data ecosystem has seldom been realized, because the present value of digital analytics is not always fully understood or embraced.

For years, this disconnect created a perfect storm where digital analytics remained isolated despite its potential. Four barriers formed a self-reinforcing cycle that prevented integration:

1. Marketers (understandably) lacked time, foresight, and technical knowledge to see integration possibilities
2. Leaders did not allocate resources to this type of data integration because the value was not well understood
3. Consultants and agencies often communicated the opportunity too technically or too abstractly (if they saw it in the first place)
4. Technology lagged because demand wasn’t fully developed

The Siloed Reality

Data isolation was evident in how companies typically engaged with their agencies:

• Advertising agencies shared qualitative and quantitative insights for creative strategy
• Media agencies provided campaign performance via questionably reliable third-party data sources
• CRM teams focused on email and loyalty metrics
• Digital analytics consultancies delivered site performance reports

Rarely were these perspectives brought together to inform overall marketing strategy. Reports were delivered separately, meetings were held individually, and insights remained siloed rather than circulated widely.

At Drumline, we’ve always believed that web analytics is one piece of a larger puzzle. And we were determined to break that self-reinforcing cycle through projects we championed and executed:

• Combining behavioral data with transactional records to drive smarter segmentation
• Connecting web analytics to CRM systems, enabling precise targeting and personalization
• Building flexible, future-proof analytics frameworks that adapt easily to new technologies and data sources

Despite these successes and our embrace of integrated data strategies, it was difficult to break through the barriers for many clients.

The Awakening

Then came the catalysts, to name just a few: CDPs emerged, the cookie apocalypse loomed, walled gardens fortified, and the narrative shifted to first-party data. Marketing leaders, facing potential loss of media efficiency, experienced what I call a “panicked enlightenment”—suddenly recognizing that behavioral data in isolation was underutilized. This wasn’t a revelation for many in the field; it was a validation of what had been advocated for years.

So in a sense, Adam’s move to Hightouch isn’t surprising – it’s logical. His career has consistently anticipated where analytics would evolve next: from writing the book on Adobe Analytics, to evangelizing strategic applications as a consultant, to embracing product analytics when it began expanding into marketing analytics, and now to a CDP focused on data integration. At each stage, he’s positioned himself precisely at the intersection of emerging trends just as the industry begins to embrace them.

The Path Forward

You could say “the awakening” continues to unfold as disruptions—from ongoing privacy changes to emerging AI developments—accelerate the industry’s natural progression. While these forces certainly impact digital analytics, they drive evolution, not revolution. The greatest contribution of these disruptive moments hasn’t been to fundamentally change what digital analytics is, but to illuminate its value within a broader data ecosystem.

While we may not be experiencing a complete transformation in digital analytics itself, there are concrete ways you can transform your organization’s approach to it:

1. Integration is essential: If you’re still viewing behavioral data in isolation, you’re missing its true potential. Connect it with other data sources to unlock transformative insights. (That was a key message in Adam’s Hightouch announcement post)
2. Consistency amid change: While technology evolves rapidly and enhancements enable new possibilities (I’ve avoided mention of AI up to this point), the fundamental purpose and value of digital analytics remains constant. What’s framed as revolutionary is often just the industry catching up to established practices.
3. Design data solutions for business outcomes: Be strategic and deliberate about what you collect and how you intend to use it. Your analytics architecture should directly reflect business priorities rather than following technical capabilities or industry trends. Start with the decisions you need to make, then build measurement frameworks to support them.

Ultimately, the question worth asking isn’t just where digital analytics is headed, but whether your organization is ready to realize its full value in this interconnected landscape.