The model we built made it possible to predict over 65% of unsubscribers based on change of customer behavior. Every time the specific client shows the behavioral pattern that is likely to lead to unsubscription, she was classified as potential unsubscriber and treated differently from the rest of the clients. Model implementation dropped email unsubscription rate by about 40%.
The unified system collecting information from multiple sources was developed. The sources included prediction of site visitation (split by specific pages and page zones), evaluation of the site demographics (from 3 sources), estimation of unique visitors by sites, estimation of audience intersections (by sites and by media types), information about percentage of views of the video ads to the end, estimations of expected discrepancies of visitor counts depending on the counting system.
Attracting new clients is costly, so retaining clients is absolutely critical for the business success.
The predictive model of churn rate was built. It made possible to predict over 70% of unsubscribers based on change of customer behavior. Project implementation dropped the unsubscription rate by about 50%.
There is hardly any monitoring of online diapers sales in Russia. The key task of the client was to cover at least 60% of highly sparse small online diaper retailers and find data for own brands and competitors. The database with automatic reporting and notification system was created to collect information about availability and price for over 200 SKUs of diapers across 50 key online stores automatically.
The smart algorithm allows calculation of the fair market price of the complex product using the Market Price Calculator (MPC) approach. The demonstration is devoted to the laptop market.