🔎 Programmatic: What is the "incremental targeting" strategy?

The other day, I was talking with a media trader, who told in me: "Data, sometimes, is a bit disappointing. You pay €1 for a 'sports interest' segment... and in the end, you realize that 2/3 of your delivery happens on sports websites."
And he was right.

Why?

Because "interest" segments are often built based on individuals' browsing behavior on the sites they visit. And logically, a sports fan consumes a lot of... sports content!

But here's the trap:

💸 We pay a premium for data targeting... when we could have bought the same ad impressions at no extra cost through targeting based on:

• An affinity site whitelist: free in some tools like Google categories in DV360 or IAB categorizations in Equativ Curator.
• Semantic tech: costs on average 2x to 10x less than audience targeting (via players like illuma, PEER39, for example).

🎯 The solution to optimize your investments: The incremental targeting strategy.

A technique inspired by the "Alpha-Beta" strategy in SEA: to lower purchase prices, experienced searchers implement prioritization strategies between exact/phrase/broad targeting thanks to an exclusion system 🚫.
This forces the buying tool to always favor the most profitable targeting.

And we can apply the same logic in programmatic:

• 1 line targeting a [sports whitelist] → free
• 1 line targeting [sports interest] audiences but excluding the [sports whitelist] 🚫.

This way, we prioritize the strategy with the lowest targeting fees, and we only pay for data where it provides real added value 🤩

Results:

✅ More Reach
✅ Lower final CPM for the advertiser

And spoiler alert: this also works with cross-targeting strategies (e.g., [Sports interest] & [Male]): It makes the Media Trader's setup more complex, but it is remarkably effective for maximizing ROI 💵💵

Effective targeting isn't necessarily more expensive targeting... Above all, it's smarter targeting!

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