The client, a premier national bank, wanted to improve client retention rates through customer engagement. However, its legacy system could not scale to meet growing customer expectations. Since many processes were still manual, and there was no omnichannel view or support for customers, they could not deliver personalized, contextual experiences in real-time.
Their goal was to deliver effective marketing campaigns using predictive analytics and adaptive learning while enabling business users to contribute and coordinate work with IT.
The client wanted to:
The Pega engine powers the bank's new customer decision hub to create personalized interactions with customers through:
Gaining the ability to assess the call deflection rate using adaptive modeling prioritization and the accuracy of intent prediction between traditional static ranking and adaptive AI-prioritization also helped the bank achieve significant results.
vEngage helped the bank:
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