25% Boost in Campaign CTR Using GenAI & Vision-Powered Image Intelligence
Retail, Marketing Optimization, Azure OpenAI
Background
A leading U.S. grocer needed a scalable way to extract and identify marketing-relevant product attributes from thousands of food and in-store images. Manual tagging was inconsistent, time-consuming, and a major barrier to executing personalized campaigns at scale.
Impact
- 25% increase in CTR on targeted marketing campaigns
- 80% reduction in manual effort for attribute tagging
- Improved content relevance and personalization, driving higher shopper engagement
Solution
Affine developed a Generative AI and Computer Vision–powered system to automatically extract three distinct types of product attributes:
- Explicit Attributes (e.g., “Eggs,” “Butter,” “Bakery” section) using image classification via Azure Vision and Azure ML
- Implicit Attributes such as shopper mission, dietary preferences (e.g., “Vegetarian”), and audience types (e.g., “Healthy Foodie”) using prompt engineering on Azure OpenAI GPT-4V
- Textual Attributes (e.g., “Honey Nut,” “Lucerne”) extracted through Azure AI Vision OCR, interpreted using GPT-4V for brand identification The fully automated pipeline enabled faster campaign targeting, improved audience segmentation, and seamless integration with downstream marketing tools.
Impact
- 25% increase in CTR on targeted marketing campaigns
- 80% reduction in manual effort for attribute tagging
- Improved content relevance and personalization, driving higher shopper engagement
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