“Customer is King”. What is the value of your Kingdom?

"ProCogia helped one of the largest technology retailers in US determine value of its customer base." Jill U. and David R.

Save PDF


The client was having issues with customer churn and attrition. Their sales team did not have a toolset that could serve as an early warning system to prioritize and proactively target at risk customers. Most of the action was taken on gut instinct and there was a lack of consistency in the results. Furthermore, the Customer Lifetime Value (CLV/CLTV) was unknown which caused issues in executing retention campaign and led to inefficient use of resources.

Key Objectives

  • Maximize the ROI of loyalty card program by developing a model to evaluate CLV/CLTV.
  • Measurable improvement in customer retention.


  • ProCogia segmented the customer base into five segments based on their purchase behavior.

    1. Red – High Risk of Attrition
    2. Yellow – Medium Risk of Attrition
    3. Green – Low Risk of Attrition
    4. Silver – Medium Loyalist
    5. Gold – Most Valuable customer
  • Examined attrition on each segment and identified movement between segments to identify attrition rates.
  • Developed revenue models using a stochastic process and CLV for a 5 year period using Markov Chains.
  • Constructed a predictive model to identify the purchase behavior of each of the segments.
  • Calculated and attached a Churn quotient to each customer, enabling client’s sales team to prevent churn among the most valuable customers.
  • Tracked and adjusted the prediction model constantly to improve its accuracy as time progressed.


$113M of incremental revenue was generated by reducing customer churn and attrition. ProCogia synthesized the data to generate insights that led to proactively targeting high attrition risk customer and launch initiatives to reduce customer churn.

Additionally, the predictive models aided the management in decision making by allowing them to conduct various ‘what-if’ scenario analysis. ProCogia helped the client to unlock the value of their existing data and institutionalize the data driven approach to decision making.