Without predictive analysis:
If a business needs users who buy a lot, the media buyer sets the conversion action as «add to cart». He asks the ad network to bring in users that are similar to those who have added items to the cart. The hypothesis is that those who add to the cart will bring more profit. However, for some users this hypothesis will work, and for others it will not.
With predictive analysis:
Working with a predictive model, the advertiser asks the ad network to attract users similar to those with a high target metric. The advertising network starts to bring not 1000 users who will add the product to the cart and of which 20 will buy it, but it brings 1000 users who will be similar to those who have a high LTV. It means they will all buy the product.
3. It is possible to buy more traffic
In performance campaigns, a benchmark is being set — the cost of a conversion action. For example, for the «add to cart» conversion event, the advertiser is willing to pay the advertising service $2 per user. But if you put up one benchmark, then you can buy at the auction only what you put up.
With the help of predictive analysis, you can find out exactly how much money the user will bring. Then you can set individual benchmarks for campaigns that are optimized for the predictive metric values from different audience segments. So you can pay for a user depending on how much money he brings based on the value of the metric.
Let’s look at an example. Let’s create an event generated by users whose pLTV is 1000-2000, 2000-15000, 15000-20000. We will pay $2 for the first segment, $15 for the second segment, and $75 for the third segment. Thus, we buy out not just one segment of the auction, but we break it down into benchmarks necessary for business and buy out the entire auction.
This is important for the businesses that want to purchase a big amount of traffic profitably.
