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Customer Churn Prediction (Coffee Chain)

Industry : Retail
One of Russia's largest coffee shop chains (160+ locations in Moscow, St. Petersburg, and other regions)
Task
Reducing customer churn and optimizing marketing budget through accurate buyer behavior prediction and personalized offers.
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Insight AI

AI implementation process

Data preparation
Collecting loyalty program data: visit frequency, average check, preferred menu items, response to promotions
ML model development
Algorithm to identify hidden behavior patterns preceding purchase cessation
Uplift model
Algorithms for selecting individual discounts and communication channels (SMS, Push, Email)
CRM integration
Automating mailings and creating marketing dashboards

Client results during the AI implementation process

Revenue growth with AI
Revenue growth without AI
according to McKinsey & Company
23% churn reduction
30% ROI improvement on marketing campaigns
CRM marketing automation

More about the solution

A loyalty program is not just about discounts — it’s a vast body of knowledge about how your guests live and what they truly want. We’ve taught the system to see real people behind the numbers: to notice when a regular latte drinker suddenly starts visiting less often or changes their usual morning routine for occasional purchases. The model analyzes these changes in real time and identifies those who are about to stop coming, even before the guest themselves realizes it.

Instead of bombarding everyone with the same push notifications, we introduced smart bonus management. The system understands who just needs a friendly reminder to return, and who actually requires a serious discount to win back their loyalty. This saves businesses from the biggest mistake — giving away unnecessary rewards to those who are already willing to pay full price. Machine learning handles all the routine: it segments the database, chooses the right communication channel, and ensures that every ruble invested in marketing brings real profit, not just an increase in the number of receipts.

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