Iper’s Data Revolution: Predictive AI for Smarter Retail Marketing

Iper, one of Italy’s leading retail chains, embarked on a data-driven transformation to overcome the limitations of marketing strategies built on fragmented and predominantly descriptive data. The challenge was clear: unify online and offline data, improve identity resolution quality, and shift media campaigns from volume-based execution to value-driven optimization.

In partnership with Bytek, Iper built a BigQuery-native predictive ecosystem, integrating loyalty, CRM, e-commerce, and digital behavioral data into a Single Customer View enriched by Predictive AI models. This architecture enabled Iper to activate high-value audiences on Google Ads and Meta, measure in-store conversions through Google Store Sales, and replace static segmentation with dynamic, predictive logic.

The results include a +20% increase in match rate on first-party audiences, offline conversion measurement for 15% of eligible in-store transactions, a +25% predictive uplift compared to rule-based models, and the identification of 100+ predictive interest signals.
The case demonstrates how a Predictive AI and first-party data-driven approach can improve media efficiency, connect online and offline journeys, and lay the groundwork for advanced use cases such as Predicted Lifetime Value and data monetization.