What is Predictive Analytics?

CX DICTIONARY

Predictive analytics is the application of math and statistics to data mining in order to predict what will happen in the future.

Why is predictive analytics important?

Predictive analytics allows businesses to predict future customer behavior by looking at past data and trends. Purchase history, customer service interactions, and demographics (to name a few) can predict customer churn, potential next purchases, and customer lifetime values.

Predictive analytics becomes more real when you bring in the true voice of the customer to detect sentiment. To do this, businesses must analyze data from all feedback channels, including surveys, social media, service calls, and more.

Clarabridge

How does Clarabridge improve predictive analytics?

Clarabridge uniquely combines qualitative, free-form feedback with quantitative data about past behaviors and trends in order to predict future customer behavior.

First, we uncover trends in buying, loyalty, and overall experience at the product, store, and user level. Then we bring this data together, alerting you to issues before they become viral and while they are still controllable.

Predictive models uncover areas to accentuate and those that require improvement. By combining this intelligence with root cause analysis, marketing, operations, and customer care teams can easily identify areas of focus that will drive continually improved customer experiences.

Marketing teams uncover the best future promotions and predict customer loyalty.

Operations teams determine the next best action for front-line staff in stores and at the call center, helping to keep staff and customers informed and happy.

Customer care teams determine how to best handle individuals while finding the most economical and efficient path to great customer service.

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