Case Study 1: Retail Media Optimization Using Advanced Analytics

Client Industry: Global Retail & E-Commerce
 Challenge:
 A leading retailer wanted to optimize its retail media monetization strategy while balancing customer experience and revenue growth. Existing methods lacked agility and often resulted in sub-optimal ad placements, leading to reduced customer engagement.

Our Solution:

  • Developed a Scenario Planner Application powered by advanced machine learning models to simulate multiple retail media strategies.

  • Built an Optimizer Engine that dynamically allocated ad placements and budgets for maximum ROI.

  • Incorporated customer behavior insights to balance revenue objectives with user experience.

Results:
 ✔ Improved retail media ROI by 27% within the first quarter.
 ✔ Enhanced customer engagement through smarter ad placements.
 ✔ Provided leadership teams with real-time scenario analysis, enabling faster and more informed decisions.