Case Study: BUTIK. Improves LTV and Customer Segmentation with OWOX BI

New Customer Segments Help BUTIK. Improve LTV

BUTIK. is an omnichannel fashion retailer selling clothes, footwear, and accessories online and through a large Moscow store. To reduce ad costs, increase customer lifespan, and improve LTV, BUTIK. needed a better way to segment customers by buying activity and personalize communication across email, SMS, call centers, and ad channels. They worked with OWOX and used OWOX BI Pipeline along with Google BigQuery to combine website behavior data from Google Analytics with CRM order and customer data.

OWOX helped BUTIK. consolidate all data in Google BigQuery, build custom customer segments, and automate reporting in Google Sheets via the OWOX BI BigQuery Reports add-on. The new segmentation model identified groups such as New Members, New Buyers, Good Buyers, Very Good Buyers, Casual Buyers, Sleep, and Inactive, while reporting tracked segment transitions and KPIs like revenue, orders, and average revenue per user. As a result, BUTIK. gained a unified data foundation for personalized marketing, saved ad budget by excluding already-reached users, and improved its ability to analyze and act on customer behavior.

BUTIK.

Yana Parshutina

Web Analyst