From report cards to real-time results: 5 smarter ways to use data

Everyone’s obsessed with optimization and for good reason. But have you ever wondered if all those impressions actually moved the needle or just filled a report?

The truth is that most brands haven’t evolved how they use data. Privacy laws, signal loss and fragmented IDs have forced us to gather different data, but not necessarily better insights. The good news? The next wave of growth won’t come from more data. It’ll come from using the data we already have in five smarter, underused ways.

Funnel mapping: Who’s really moving through it

Why do clicks still dominate how success is measured when the people clicking rarely match those who actually buy products? Funnel mapping, once you get used to it, is a game changer. By examining the attributes of those who engage at each stage, with characteristics like age, income, affinities, life stage, etc., marketers can see exactly where spend is wasted.

Insights you’re missing now snap into sharp focus. For example, if the top people clicking skew younger, but the people converting are mid-career professionals with families, you have a targeting mismatch. Instead of optimizing for clicks that go nowhere, you can optimize for conversion composition.

The most sophisticated teams don’t just track funnel performance; they track who is in the funnel and whether that audience aligns with business outcomes.

Data doesn’t have to be a perfect GPS, just a good-enough compass

In markets where privacy laws limit data application at the impression level, marketers tend to freeze. What if we’re not in compliance? And if we are, how can we manage when there’s so little precision?

Your data doesn’t have to be perfect to be useful. Your data can still be an incredibly effective strategic compass, guiding creative, sequencing and channel investment even if it can’t tag every ad.

You might not be able to retarget a user directly, but you can still use audience insights to decide what story to tell first and where it resonates best. Remember that perfection, even if you had it, still wouldn’t be perfect.

Directional intelligence is more than good enough to drive real results.

Growth cohorts: The evolution of segmentation

After decades of pushing segmentation to its limits, marketers have learned that not all segments are growth drivers. The next evolution is identifying “growth cohorts”: high-intent audiences with distinct motivations and minimal overlap.

Let’s say a luxury brand serves both “status-seekers” and “practical buyers.” Each group may buy the same product, but for different reasons. Growth comes from understanding those reasons and tailoring both creative and experiences accordingly.

Here’s the trick: Before activation, validate that these cohorts don’t heavily overlap. This will ensure that each media dollar will work to attract new value, not the same customer twice.

Seed to scale: Amplify small but mighty signals

Some of the richest data sits in small, often-ignored sources like influencer engagement, survey responses, social chatter or event RSVPs.

I get it — on their own, these signals don’t scale. But don’t ignore the tools at your disposal. When you combine these small signals with machine learning or probabilistic modeling, they can become powerful lookalike audiences across CTV, programmatic, digital out-of-home and live experiences.

For instance, a brand might start with a small group of micro-influencer followers who demonstrate high purchase intent. Those behaviors and characteristics can seed larger campaigns that retain authenticity while scaling reach. In a signal-challenged world, small data amplified correctly often outperforms big data used blindly.

AI acceleration: From reporting lag to real-time learning

Historically, marketing insights have lagged behind action. Campaigns run, data trickles in, and six weeks later, someone updates a slide deck. AI can collapse that cycle to hours.

AI isn’t just about automation. It’s about acceleration.

It can detect new audience correlations faster than humans, flag anomalies in performance data and suggest creative swaps after major cultural moments or tentpoles. The key is giving AI the right training data. I’m not talking about only clickstream metrics. AI needs enriched, ethically sourced behavioral and contextual signals.

When paired with human oversight, AI can become a turbocharger for curiosity and iteration.

From measurement to meaning

In the mass media era, people were trained to use data as a scoreboard: impressions, reach, engagement. We’re in an entirely different media universe now.

Data needs to be a mirror that reflects why people act, not just that they did. The marketers winning in 2026 won’t be the ones with the most data; they’ll be the ones using it most creatively.

To get there, stop treating data as a post-campaign audit. Use it as a pre- and mid-term advantage to plan, predict and optimize. Start small: Map your funnel participants, rethink your growth cohorts, test seed-to-scale insights and bring AI into optimization loops.

When data stops being a report card and starts being a real-time feedback loop, marketing becomes what it was always meant to be — a conversation, not a calculation.

When thinking about data, it pays to set aside what you “know” and stay open to what’s possible. Curiosity, not certainty, is always the right approach.

This op-ed represents the views and opinions of the author and not of The Current, a division of The Trade Desk, or The Trade Desk. The appearance of the op-ed on The Current does not constitute an endorsement by The Current or The Trade Desk.