Churn and Sales Forecasting

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The algorithms here take into account a lot of variables (demand, supply, competitors' prices, the cost of related products, customer habits, their loyalty), which is definitely beyond the power of even a malta telegram database dozen specialists manually. The main task is to set the best price for a specific product for a specific client at the moment. The math is simple - a 1% increase in prices will lead to a 10% increase in profit for a business with a 10% profitability. Almost all large e-commerce retailers and marketplaces have such systems.


According to experts, the cost of attracting new customers is 4-11 times higher for a business than retaining old ones. While AI cannot yet solve abstract problems such as “advise me on what marketing campaign to conduct to increase loyalty,” it can point out customers who are prone to churn and answer the question of who needs to be communicated with now in order not to lose money in the long run.

How it works: at certain intervals, the system groups clients who are thinking about changing their favorite online store, analyzes the reasons for the decision and, based on historical data, offers options for action that will help retain these people. And then a sequence of mailings with steps to engage in interaction (discounts, bonuses and other similar privileges) starts.



That's why we increasingly see such companies becoming AI innovators, with their internal solutions scaling across the industry as a whole, and access to the technology reaching not only business giants, but also small online stores.