Case Study: Vimos achieves 12.3% revenue uplift and 8.45% gross profit boost with Competera Price Optimization

How a DIY retailer Vimos maximized revenue without traffic losses in the short term and saved profit during the low season

Vimos, a Russian DIY retail chain operating 43 trading centers with over 25,000 SKUs and annual turnover above $160 million, needed a quick, flexible AI‑driven pricing solution that could handle seasonal demand spikes, integrate with a legacy in‑house ERP, and be simple for category managers to use. After KORUS Consulting recommended an AI pilot, Vimos selected Competera and its Competera Price Optimization platform to run a limited-store proof of concept.

Competera implemented an AI-based pricing workflow that included data cleanup and integration with Vimos’s ERP, training neural models on historical and external data, onboarding seven product managers, and running a one-quarter pilot (5 test hypermarkets vs. 5 control). Using Competera’s recommendations for repricing ~25,000 SKUs (excluding promos/KVIs), the test group outperformed the control: +12.3% revenue, +8.45% gross profit, +6.31% sales items, +1% traffic, with repricing now taking two hours weekly. Following these results, Vimos scaled Competera across all 43 stores and moved forward with expanded optimization and monitoring.

Vimos

Ekaterina Kantina

Financial Director