How to Make Data-Driven Decisions in a Data-Less World

Inside dmarcianThought Leadership

As part of our ongoing series highlighting dmarcian perspectives, Samantha Thompson speaks to the increasing challenge of navigating an ever-changing internet landscape.

Analytics has never been a rigid, perfectly predictable journey with no attribution drop offs or gaps. Marketing analytics are live, dynamic puzzles, where the pieces evolve and new patterns emerge. And that’s what we love about it, isn’t it? 

Behind every dashboard, chart, and trend line is a human being, and a little peak into human intent. When someone visits a page, hesitates at checkout, searches for a solution, or navigates your website, they are expressing a real-world need. Being a marketer is about being able to understand those needs, often without direct communication. We intertwine actions like clicks and form fills with behaviors like entry points and dwell time to understand the effectiveness of our campaigns. By understanding our audiences’ interests, we aim to improve the journey and experience for them along the way. 

What do we do when many of those insights, those pieces we relied on to form our data stories are obfuscated, missing pieces, or just plain non-existent? 

Over the years, with cross-device journeys, dark social, and multi-touch campaigns, we’ve been moving away from perfect attribution faster than we can run towards it. Some brands hold on to “tried and true” methods to define success, but the way I see it, the new strategy is in adaptability and seeing the bigger picture.

The Rise of Zero Click Search & AI Overviews 

Today, the search landscape is changing and has already transformed into an interactive conversational experience. With LLMs and AI Mode searches, people aren’t browsing through multiple pages on your website anymore after clicking a top-ranking link. Instead, they can ask real questions and gather consensus from multiple sources.

The Dark Funnel Expands

Prospects research our categories, evaluate our solutions, and form strong opinions via AI summaries, private communities, and peer chats where traditional analytics register zero website visits. 

This creates a true turning point for marketing strategies that rely heavily on marketing automation workflows, vanity metrics, ever-so-trendy playbooks for 10x clicks, and pay-to-play gamification campaigns from third parties. 

The bottom line: the KPIs we measured before aren’t independently indicative of true success anymore.

In a world where data is messy and attribution is full of gaps, marketers shouldn’t rely on just one source, but combine many.

The Silver Lining: A New Puzzle and Closer Customer Proximity

While we have lost a lot of our clear attribution paths, and search is changing so much due to machines, an opportunity arises, leading us back to some of the foundations we’ve moved so far from. The human behind the keyboard. Real customer research. First-party attribution asking simple questions to test against other channels.

Perhaps losing some attribution will force us to get closer to our customers and prospects as we need to understand search behavior over keywords, discover consumers’ real questions, and optimize how we speak to a variety of learners. We need to combine the attribution we have with the stories we are told and triangulate our data sets for new patterns of human behavior. This is how our brains naturally process data, isn’t it?

So what do we measure? All of it. 

As attribution becomes harder due to privacy changes and fragmented user journeys, triangulation in marketing analysis—the practice of combining diverse, independent signals rather than relying on any single metric in isolation—is a necessity in order to make sure we are meeting people where they are, providing value, and optimizing for AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization).

By weaving together quantitative pipeline data, conversion quality, direct customer feedback, brand engagement, and self-reported attribution, teams can cross-verify performance and build a much clearer, more reliable picture of what is truly driving results.

Human Centric Marketing Wins

We see new strategies every day for dominating AEO, GEO, and AI answer engines. But while everyone is trying to crack the code, the answer goes right back to the basics. At its core, winning AI search relies heavily on traditional SEO—namely, Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, and Trustworthiness)—with a few extra tweaks for easier machine scanning and readability.

As the guidance changes daily, there is one constant:

In order to be cited by machines, you have to be more human. 

Ironic, isn’t it? AI agents most often cite unique perspectives, and thought leadership that doesn’t sound robotic. Real human perspectives are more important than ever.

In the end, I see the lack of data and shifts in the search landscape as opportunities to get closer to the humans we are trying to help, and to be more human and authentic than ever before. 

Life doesn’t have perfect attribution anyways, and I am okay with that.

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