Skip to main content


         This documentation site is for previous versions. Visit our new documentation site for current releases.      
 

Adaptive analytics

Updated on May 17, 2024

Adaptive Decision Manager (ADM) uses self-learning models to predict customer behavior. Adaptive models are used in decision strategies to increase the relevance of decisions.

ADM models are self-learning which means that they are automatically updated after new responses have been received. The ADM service captures predictor data and responses and can therefore start without any historical information. You can use adaptive decision management to identify propositions that your customers are most likely to accept, improve customer acceptance rates, or predict other customer behavior.

Adaptive models work by recording all customer responses (both positive and negative) and correlating them to different customer details (for example, age, gender, region, and so on). For example, if ten people under 35 years of age accept a particular phone offer, the predicted likelihood that more people under 35 years of age will buy the same phone increases. The likelihood can also go down if a negative response is recorded, from this group. Over time, reliable correlations emerge.

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

Did you find this content helpful?

Want to help us improve this content?

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us