AI Solutions
Churn Management
  • Our powerful, data-driven churn prediction provides the insights needed to re-engage customers based on their risk of churn, and keep them engaged with exact targeting, perfect timing, and redefined messaging.
  • Leverage our multi-modeling propensity prediction technology to account for multiple factors such as profile details, satisfaction scores, engagement level, business volume, and industry trends.
  • Develop targeted customer retention strategies by predicting the individual risk of churn.

Success Stories





Canada’s Leading Protection Provider

Time taken for prediction and validation was

< 7 Min

for 60,000 customers record

Actual churn is


accounted by first two declines

Service quality accuracy were predicted has


for three customer feedback metrics


Canada’s leading provider of protection and wealth products/services wanted to improve its customer engagement strategy.

The company wanted to identify the customers at higher risk of attrition and predict overall customer satisfaction rating for key service parameters across three business units.


A proprietary self-learning, multi-modeling automatic predictive technology from Findability.AI was used to:

  • Divide customer records into deciles on likelihood to churn.
  • Predicts customer satisfaction rating for three measures of customer service quality such as ease of doing business, proactive contact, and problem resolution.


Telecom industry

Fine-tune promotional offers

made by client for customers

were they divided in sub-groups.

For churn pre-emptive strategies

formulated by client because of external events

Highest risk of churn were predicted


In telecom industry, customer behavior is influenced by several external factors like new phone launch, festivals, time of the year etc. making it difficult to predict likelihood of retention.


Findability.AI's, Proprietary self-learning, multi-modeling AI technology predicted customer churn based on CRM information, plan details, usage, and billing.

Findability.AI also analyzed unstructured content for chat bots and emails and accounted for reported malfunctions/defects while predicting churn.


Global multimedia and creativity software company

Additional retention of


over the base retention rate of 15% was observed in the highest rank customer segment.

Proactive outreach plan

formulated by client for customers who were mostly likely to be retained

Customers can target remedial measures at others


A global multimedia and creativity software company wanted to determine retention propensity for retail consumers who had contacted their call center with the intention to cancel subscription.


Customer tenure and product subscription history was analyzed using a self-learning, multi-modeling prediction technology from findability.

AI The proprietary algorithm ingested historical data to develop multiple prediction models to account for all possible scenarios in the dataset.