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Adaptive IVR Blog

Contact Center Customer Self-Service Data Mining: Secrets Revealed

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When have you had the opportunity to delve deeper into contact center data mining, and in particular in the customer self-service channel? This is historically a “set it and forget it” channel, which means there’s a whole source of actionable analytics that you may be missing out on.

We get it, no one can be accused of being Superman in the contact center - seeing through the data, tools and technology in the blink of the eye to the core actionable answers. That would be great, but it’s not reality.

Data Mining is the Secret Sauce

Customer interactions in the contact center create an exorbitant amount of data that no organization can manage on its own, and they shouldn’t have to.  In fact, many organizations are still behind the times in realizing how much data can be leveraged to improve customer experience, contact center results and operational effectiveness.  And usually it’s because resources are thin and demands are high for many conflicting priorities.

For instance, did you know that effectively leveraging what data can tell you in your IVR and your digital channels can help you drive improvements in the areas above with:

  • Built-in continuous improvement measures
  • Personalization that creates CX and cost benefits
  • Fraud prevention that improves security and stops the bad guys

Secret Recipe Revealed

I recently presented on the secret recipe behind data mining in customer self-service channels at a prepaid card conference, and the information I shared is summarized in this brief video.

Take a look and let me know what you think.

David Scott

dscott@contactsolutions.com

Watch this brief video >

Watch the Contact Center Data Mining Video

Data Mining Video

Get the secret recipe behind data mining in customer self-service channels summarized in this brief video.

Watch the video

Topics: Industry Insights Customer Care Consumer Behavior IVR Business Case Performance Optimization Customer Experience Process Improvement Customer Data Contact Center Insights Personalization Fraud Analytics