Where Digital Meets In-Store Data

The Challenge

A major retail brand was struggling to connect their digital marketing efforts with actual in-store performance. They were spending significant budgets on digital campaigns but had no clear visibility into how online engagement translated to foot traffic and in-store purchases.

The disconnect between digital analytics and physical store data made it impossible to accurately measure ROI or optimize campaigns for in-store conversions. Marketing decisions were being made in silos, with digital teams optimizing for clicks and store teams focused on foot traffic, with no unified view of the customer journey.

The Solution

Adalane deployed AI agents to integrate digital campaign data with in-store performance metrics in real-time. Our solution included:

• Unified Data Pipeline: AI agents connected Google Ads, Meta, and in-store POS systems to create a single source of truth
• Attribution Modeling: Machine learning models correlated digital touchpoints with in-store visits and purchases
• 24/7 Optimization: Agents continuously adjusted digital campaigns based on in-store inventory levels and foot traffic patterns
• Store-Level Targeting: Geo-targeted campaigns optimized for individual store performance, not just broad regional metrics

Expert strategists from Adalane reviewed agent insights weekly to refine the attribution model and ensure campaign strategies aligned with broader business goals like new product launches and seasonal promotions.

The Results

Within 90 days, the client had complete visibility into how digital campaigns drove in-store performance. Budget allocation shifted dynamically based on which campaigns drove profitable store visits, resulting in significantly improved overall marketing ROI.