Tokmanni wanted to increase customer store visits and engagement. They used a mobile application to offer discount coupons to registered loyalty customers.

However, the usage rate of these standard coupons was low. The company needed a way to make offers more relevant and appealing to individual customers. They decided to use AI for personalized coupon recommendations and pricing, but lacked the internal capabilities to build and manage such a system.

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We partnered with Tokmanni to create an AI-driven personalization engine for their mobile app offers.

Our team analyzed customer data to understand purchasing patterns. We built the necessary technical foundation (MLOps) to develop, deploy, and operate machine learning models efficiently. We then created AI models to recommend relevant products and set optimal discount prices for each customer. The solution also included using GenAI for creating product summaries and integrating smoothly with their existing mobile app and business rules. We implemented A/B testing to measure success and gradually rolled out the automated system to all loyalty customers.

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The implementation of AI-powered personalized recommendations yielded significant positive outcomes. Tokmanni recorded a 2% increase in mobile-app customers visits to their physical stores. The personalized offers contributed to a 2% increase in overall sales for mobile-app customers. Furthermore, the usage of mobile app coupons increased by 88%, at the same time reducing the average discount of coupons.

These results clearly demonstrate that using AI for personalization can drive customer engagement and sales more effectively and cost-efficiently.

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