Case Study05/17/2023

Case Study: Optimizing Ingredients based on Geographic Demand

Joseph Day
Senior Machine Learning Scientist

In a recent engagement, Strong Analytics worked with a leading partner in foodservice innovation that develops and brings user-centered solutions to market. Our partner company is always innovating to stay ahead of the curve, leveraging digital technology to modernize the food industry.

We worked with this leading foodservice innovation partner to improve their understanding of how product sales for certain ingredients differ by geographic market. This would enable them to optimize their deployment of ingredients based on where consumers are located.

The Problem

Our partner came to Strong Analytics with the goal of ​​better understanding which of their products sells best in different markets. To address this, they aimed to build a dashboard for general managers and sales leaders across the USA and Canada to help them understand local market conditions and trends. They wanted the dashboard to integrate multiple potential data sources and enable data-driven decision making for products and sales.

The Solution

We designed and built the MVP version of a market health tool for our partner. This tool leverages restaurant purchasing data and Yelp restaurant review data to understand what ingredients sell best at different restaurants and what people have to say about it online.

The MVP version of the tool incorporates a high-level overview of the popular ingredients nationwide. The dashboard we built also enables key stakeholders at the firm to understand how ingredient demand differs by geographic market.

Performance Impact

Our work enables the partner’s key stakeholders to explore the trends for themselves, allowing them to extract critical insights that drive strategic business decisions. Given the success of the MVP, we are currently in the process of converting the MVP version of the market health tool to a fully functional app that will be leveraged by a broader user base.


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