Retailing is about understanding the purchase forces that drive and fulfil consumers’ needs, taking into account time, price and product. AlgoTrace provides the tool that predicts the correct move a retailer should make in order to optimize consumer satisfaction while maintaining a high level of operational efficiency and optimal pricing. Our non-code, fully automated AI and Machine Learning tool assists retailers to use predictive modelling in easy yet powerful manner.
Retailers can use our tool for optimizing loyalty programs, operational cost reduction, pricing and more.
Here are some use cases we have already done,

Use case Description
Loyalty program optimization Using data mining techniques to better identify customers with a high likelihood of loyalty program churn, individual pricing and more.
Price optimization AlgoTrace’s solution adjusts the right price for the right branch location at the right time with a specific emphasis on special dates and holidays.
Geographical analysis for marketing campaigns Using Geographical data to better design marketing campaigns and driving more insights for each branch and each valued customer base on competition and inner history transactions.
Providing the ability for cross-selling and upselling offering By predicting the likelihood of each client to respond to a cross-selling and up-selling offering, marketing managers can better approach different segments of client’s base.
Increasing occasional and loyal customer satisfaction Using advanced predictive analyses for increasing customer’s satisfaction by predicting future needs for each client while on the visit.