The real cost of disconnected data

When it comes to targeted ads, Meta and Google are good at what they do. But they can only work with the data you give them. If that data is purely digital, you're missing half the picture.

A customer who browses extensively online but converts in-store every time looks, from the platform's perspective, like someone who never buys. And if your ads only target based on clicks and not buys, your customers will keep seeing ads for the stuff they already bought.

They keep seeing your ads. You keep paying for them.

ROAS isn't the full story

Most paid media teams live and die by ROAS. It's a useful metric, but it doesn’t take everything into account.

A high-ROAS customer who regularly returns products in-store may not be as high-value as they look.

This is exactly what Sport 24 discovered. Running Meta campaigns with Facebook's own audiences, they were achieving a ROAS of 17–20 — strong by most standards, and a result most teams would be happy with.

But when they switched to audiences built from their own first-party data — combining online and in-store purchase behaviour to identify buyers who actually kept what they bought — their ROAS jumped to 30–35.

In one campaign, it hit 35.58. That's a 92% improvement, just by making sure you’re spending on the right people.

Read the full SPORT 24 success story here.

3 ways better data improves paid performance

So, what are some things you can do to make sure you’re reaching the right people with your ad spend? Here are 3 ways, all possible with a Customer Data Platform:

1. Build look-alike audiences from your actual best customers.

Not just high spenders, but high CLV customers. These are people who buy often, spend consistently, and don't return their purchases.

The CLV model within Raptor’s CDP segments your customer base exactly this way, so you can identify who your best customers are based on the metrics you choose. This gives you a much better foundation for building look-alike audiences on Meta and Google that are worth targeting.

2. Exclude customers who've already converted — wherever they converted.

Back to our hiker: if she bought the boots in-store on Saturday, she shouldn't be seeing a retargeting ad on Sunday. Connecting your purchase and POS data to your ad platforms means suppressions happen automatically, in real time, across channels.

3. Stop spending on customers who've already left.

If your data tells you a previously loyal customer has gone quiet — no purchases, no engagement, inactivity scores rising — this is not a customer you should target with standard messages any longer.

Either redirect that budget to a reactivation campaign, or suppress them entirely and focus spend where it can still make a difference.