While they had plenty of disparate customer data overall, they held no actual knowledge of personas, needs or trigger points. Their teams worked on rule base customer segmentation and targeting with no real measured impact for campaigns, as well as multiple teams reaching out to customers with different messages.
ElectrifAi deployed and scaled an Ai driven solution to 70+ million subscribers within 6 months. To begin, we established a new analytics workflow that prepared and transformed data, as an automated process for longitudinal views of customers, including Customer Demographics, Account Information, Device Information, Equipment Installment Plans, Customer Care Memo Logs, Payments and Usage.
We also enabled data driven customer segmentation, insights into customer needs and predictive insights on the campaign pipeline. Our model used advanced ML to predict and optimize the following:
Residual Lifetime Value
Network/Coverage Experience and Satisfaction
Aspirational Value and Headroom
Propensity to churn
Propensity to add additional lines
Propensity to upgrade to a new device
Propensity to add a feature
Propensity to upgrade to a new rate plan
Incremental Annual Revenues
$70M through incremental lines added
$50M in incremental revenue through rate plan / feature upgrade campaigns
$10M from churn saves
