You can now analyze historical customer responses and learn more about adaptive models by extracting past interactions. Based on the historical responses that you extract and download, you can also build a model in a machine learning service of your choice.

Every interaction between your customer and your business, such as accepting or rejecting an offer or clicking your banner on a website, provides a meaningful context for your adaptive models. By enabling the recording of past interactions in Prediction Studio, you can reuse the gathered historical data to improve future adaptive models and, in effect, increase the accuracy of customer decisions. When enabling historical data recording, you can also customize the data that you collect by specifying the percentage of all positive and negative responses that you want to record.

The following video demonstrates how to enable historical data recording for an adaptive model that predicts whether a customer is likely to click a web banner. A web banner typically has a significantly lower number of positive responses (banner clicks), than negative responses (banner impressions). In such cases, you can decide to record all positive responses (100%) and only a small amount of negative responses (1%).

For more information, see Extracting historical responses from adaptive models.