Problem

Traditional loyalty programs have become considerably less efficient, and retailers are looking for new tools to personalize their offerings and drive sales. In contrast to online retail, customer behavior trends and preferences are often not recorded and not used, the salesperson does not see the history of purchases and cannot make the most appropriate offer to the customer immediately.

Solution

A recommendation system based on video analytics, allowing you to "recognize the customer by sight", understand their purchase history, offer the most suitable and relevant goods, and serve them on the basis of preferences. The solution integrates with the loyalty program and allows the customer to build sophisticated AI-based interaction models.

Result:

• 5–15% sales growth.
• Average check increase by 10–20% due to upsale.
• NPS increase by 7% or more.

Implementation stages

PROJECT

Solution demonstration, discussion of possible use cases (1 day)

SCENARIO

Feasibility study based on the discovered customer issues (1 to 3 days)

PILOT PROJECT

Pilot implementation of the solution (1 to 3 months)

Scaling

Scaling