Create predictions to anticipate business events and customer behavior, such as the chances of a successful case completion or the probability of a customer accepting an offer. You can then increase the accuracy of your decisions by including the predictions in your decision strategy.
For example, you can create a prediction that calculates whether a customer is likely to accept an offer, and then add the prediction to a next-best-action strategy. The next-best-action strategy prepares several propositions for the customer, and then selects the one that the customer is most likely to accept.
You can create predictions with or without historical data. Historical data contains the outcomes of previous customer interactions.
- Predictions without historical data
- Learn in real time based on incoming results of customer interactions.
- Predictions with historical data
- Learn based on the outcomes of previous and incoming customer interactions.
Select the type of prediction that you want to create:
- Creating predictions without historical data
Anticipate business events and customer behavior by creating predictions that learn in real time, based on the incoming outcomes of customer interactions.
- Creating predictions with historical data
Anticipate business events and customer behavior by creating predictions that learn based on the outcomes of previous and incoming customer interactions.
- Anticipating customer behavior and business events by using predictions
Better address your customers' needs by predicting customer behavior and business events. For example, you can determine the likelihood of customer churn, or chances of successful case completion.
- Adaptive analytics
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.