You can activate on an audience saved with your 1st party data via retargeting or look-alike modeling. We recommending first using a Retargeting delivery method for activating your 1st party data. If you don't see enough scale, then you can come back and do a Look-alike delivery.
- Select Retargeting when you want to deliver to people in your 1st party data set.
- Look-Alike Modeling is a better choice if you're looking to target people similar to your selected audience. This model considers the aggregate behavioral footprint of users that match your audience and ranks them in order of importance. If you select LAM, you have to define your match rate. The lower the rate is, the less different the LAM audience is going to be from your audience. Consequently, the lower the rate is, the smaller the audience size is going to be. 30% is the highest possible match rate for credible results. Setting the slider at 5% means we will set aside the highest 5% of closest matches. Setting the slider at 30% is less stringent, we will set aside the highest 30% of closest matches. Since the LAM pool is capped around 200 million devices as well as ranking varies from 1-30%, it means up to 60 million devices can be activated against.
Activating via look-alike modeling helps you scale your 1st party audiences by finding more people who look like your best customers. This helps combat challenges with low sample size when activating 1st party data.
You can also exclude your 1st party audience from your audience definition to suppress your customers from your targeting. This ensures you're not wasting ad dollars by spending on your existing customers who have already purchased.
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