Customer churn and retention is an ongoing challenge for many service providers. This is especially the case for Telco services in the first 90 days.
Customer retention is a challenge for telcos and currently, there is no way for telecommunications service providers to coherently orchestrate the customer through the first 90 days of their contract so that communications are consistent and end user appropriate with tailored interactions via web, email, SMS.
– Delivering personalised experiences to customers is needed to retain customers and upsell services
– Static machine learning systems quickly become inaccurate
– Periodic retraining can be time-consuming and expensive and businesses cannot afford offline training time
– User apathy is difficult to predict and measure, so user feedback can be unreliable as a success measure
The collaboration with Brite: Bill led to the development of a prototype intelligent engagement machine learning utility for common end-user lifecycle cases in the telecommunication industry. This project enabled the development of Brite: Bill’s Brite: Now product offering which affords the ability to reduce customer churn by offering data-driven personalised customer interactions.
Inputs: Customer data
Technology: A modified version of the k-nearest neighbours (KNN) model.
Outputs: Case’s utility score according to its predictive performance.
Results: The tool harnessed statistical and machine learning techniques to provide insight and evidence to inform the optimal configuration of personalised interactions for customers as they journey through their first 90 days of a new contract with their (mobile) service provider
Data-driven customer engagement prototype.
Improve customer journey, improve pre-sale conversion, improve post-sale retention.
Automated management of bespoke customer communications across billing, client services, fulfillment and product offerings resulting in reduced churn, better retention, and brand loyalty.
Check out this video on Digitally Enhanced Engagement
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