Case Study: Starbucks uses geospatial analysis to identify new market opportunities
- Dabble Retail
- May 1, 2022
- 2 min read
Starbucks, the world's largest coffeehouse chain, used geospatial analysis to identify new market opportunities for expansion. By analyzing demographic and geographic data, they were able to identify potential markets that were underserved by coffee shops and had a high likelihood of success.

Step 1: Data Collection
The first step was to collect relevant data such as population density, income levels, education, and age distribution. Starbucks used third-party data sources such as the US Census Bureau, Nielsen, and Esri to collect this data.
Step 2: Data Visualization and Analysis
The next step was to visualize and analyze the data using geospatial analysis tools such as GIS. Starbucks used ArcGIS, a popular GIS software, to analyze the data and create visualizations such as heat maps and scatter plots.
Step 3: Identify Potential Market Opportunities
Based on the analysis, Starbucks identified several potential market opportunities. For example, they found that there were many densely populated areas with a high concentration of young professionals that were underserved by coffee shops. They also identified areas with a high concentration of college students, where there was a high demand for coffee.
Step 4: Decision Making
Using the insights gained from geospatial analysis, Starbucks was able to make informed decisions about where to expand their business. They opened new stores in the identified locations, which proved to be successful and contributed to the company's overall growth.
Conclusion
Geospatial analysis played a critical role in helping Starbucks identify new market opportunities and make informed decisions about where to expand their business. By analyzing demographic and geographic data, they were able to identify underserved markets and successfully expand their business into those locations. This case study demonstrates the power of geospatial analysis in market analysis and decision making.
Can we get an actual sample dashboard to support each step mentioned above?