Case studies Retail & CPG
Separating real promotion uplift from noise
A major retailer
Baselinetrue organic demand isolated across thousands of products
Promo ROI
Quantified per campaign
A/B
Validated in market
Faster
Campaign planning
The challenge
Frequent promotions across thousands of products and stores made it impossible to tell genuine uplift from sales that would have happened anyway. Discounts subsidised loyal customers and hid the true cost of acquisition.
What we built
- A model trained on non-promotional history forecasts what would have happened without each campaign.
- Behavioural auditing finds categories that have become dependent on discounts.
- Control and treatment groups validate predictions against real-world results.
The results
- The retailer can cut wasteful discounts and invest in campaigns that work.
- Automated forecasting shortened campaign planning cycles.
- Promotion decisions now rest on measured uplift.
Related work.
2×search-to-purchase conversion rate
Conversational product search and recommendations for a consumer health brand
A global consumer health company
60%projected reduction in manual data collection
IntelGather: an automated intelligence platform for marketing insight
A consumer brand
70%improvement in machine reliability
Predictive maintenance for a global energy company
A major energy conglomerate
A similar workflow in your business?
Tell us how it runs today. A strategist and an engineer will work out what agents could do with it and what that would take.