Tracking is targeting: Why your ad performance depends on data accuracy

Remember when you could handpick your audience on Meta? You’d layer interests, tweak demographics, and build lookalikes so precise that it was almost creepy. Those days are long gone.

The controls advertisers once relied on to shape their targeting have been stripped away - replaced by black-box automation and machine learning models that make the calls for you.

In today’s world of Performance Max and Advantage+, you’re no longer in the driver’s seat. Your data is.

The death of manual targeting

Not long ago, marketers could define exactly who they wanted to reach. You could target by interests, behaviours, purchase intent, and even layer in third-party data for added precision.

Since then, privacy changes like iOS 14 and the end of third-party cookies have shifted power away from advertisers, making it impossible to use the level of detail they once depended on. 

At the same time, Meta and Google have intentionally closed the black box, introducing campaign types that automate almost everything - from bidding to creative delivery.

Intelligent campaign types, like Performance Max and Advantage+, are built to learn on their own. They promise simplicity, but what they really demand is trust - trust that the algorithm knows your audience better than you do. And for it to know that, it needs rich, reliable data flowing from your site back into the platform.

Today, audience targeting isn’t something you configure in Ads Manager; it’s something you teach through data. And what informs that data? Signals. 

Tracking is the new targeting

Every customer interaction on your website - a product view, add to cart, checkout, purchase - becomes a signal. Those signals feed back into Meta, Google, and other ad platforms to help them predict who is most likely to convert next.

For example, when someone adds a product to their basket but doesn’t check out, that signal tells the algorithm this person is a warm prospect. When another user scrolls through a product range without adding anything to cart, it flags lower intent. 

Multiply that by thousands of interactions each day, and the platforms begin to map the behavioural patterns that lead to conversion - and find more people who behave the same way.

When it works, it works. But that process is only as strong as the data it’s based on.

The silent killer of paid media performance

If your tracking setup captures rich, consistent and complete event data, the algorithms have the information they need to model your ideal customer accurately. 

But if events are missing (or duplicated), the algorithm starts to optimise in the wrong direction. It wastes budget on the wrong audiences, misreads intent, and loses the ability to distinguish between genuine buyers and casual browsers.

And the problem doesn’t stop at ad delivery. Poor tracking also distorts your analytics and reporting, skewing attribution and making revenue data unreliable. That means you’re making optimisation decisions based on wobbly foundations.

The reality is that every optimisation, every bid, and every piece of targeting logic depends on tracking integrity. When the data feeding your ad and analytics platforms is wrong, everything downstream - from creative decisions to performance insights - is compromised.

Data, data, data

Times have changed. Performance marketing is no longer about clever segmentation or audience layering - it’s about data. 

The accuracy of your conversion tracking decides whether your ad spend drives growth or disappears into the algorithm. So before you scale your next campaign or launch your next creative test, fix your data foundation.

Because the algorithm only knows what you show it - and it’s your data that tells the story.

Get clarity on what’s working (and what isn’t) with a free tracking audit.