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An American broadcaster uses AI for customer retention

The challenge

A large media company needed to revamp its approach to customer retention, as a result of legacy systems and processes. Customer service agents used various systems to obtain necessary data, taking longer than anticipated to review subscription packages and provide recommendations to customers. The company had two primary objectives:

  • Increase Monthly Expected Revenue (MER) and reduce customer churn by providing better experiences.
  • Leverage data and automation to make the call-center operations more efficient and more resilient to understaffing as a result of the COVID-19 pandemic.

The solution

Capgemini and Pega helped the company transform with four innovative solutions:

  • Custom next-best-offer algorithm that analyzed customer data and selected the most relevant offer for each customer.
  • Revamped the call-center experience by automating operations using Pega BPM.
  • Identified adoptive models for subscription offers, displaying for the agent in real-time which offer the customer is most likely to purchase.
  • Targeted multiple customer segments with automated best-retention offers, without an agent.

The outcome

The media company delivered an efficient and effective customer experience, using automated prompts and reducing the wait time for a new offer.

The results

51,000+

Customers who’ve received an algorithm-approved offer

 

16,000+

Customers who’ve accepted algorithm-approved offers

 

30 seconds

Average reduction in handling time per call

 

7%

Reduction in calls handled by 10,000 agents worldwide

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