What did I build?

Develop a rule-based recommendation tool for retailers to optimize offers.

How did I build it?

The project involves developing a rule-based recommendation tool for retailers to optimize offers. The tool allows retailers to determine whether to promote or avoid a SKU, update prices based on historical competitor prices, negotiate better with manufacturers, and adjust SKU placement for better reach.

The tool provides a threefold improvement for a flyer, including planning and optimizing SKUs before going live, competitor SKU tracking, and validation and improvement after going live. It also helps retailers simulate scenarios before execution, update SKU offer price, and export data.

The impact of this tool is that it enables retailers to plan and optimize product promotions, compare data points across multiple competitors, and increase their margins or become more competitive in pricing.

Challenges & Lessons Learned

• Developing accurate and useful KPI dashboards
• Ensuring data quality and consistency across competitors
• Creating effective and scalable rule-based recommendations
• Collaborating with cross-functional teams to incorporate feedback and optimize the tool