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Beyond Putting Data to Work Strapline


A Leading Fast Food Chain was looking for a data-driven classification/clustering of their restaurant estate to help identify opportunities within and across their stores to generate additional ROI. They also wanted to understand where the gaps and challenges were in their data.

What We Did

Beyond Analysis carried out the following: Segmentation Model - Looked at a total of 132 variables to be narrowed down to 31 to build a segmentation model. Clustering - Used a k-means algorithm which considered all of the different attributes to group the most similar restaurants together, split across 12 clusters. Recommendations - Set out the data challenges faced and provided recommendations for addressing these in order to improve efficiency and accuracy of analysis.


A filterable report where a leading fast food chain could investigate and benchmark: restaurant clusters, and restaurants within their respective clusters. A set of ‘pen portraits’ of each of the clusters setting out key attributes including performance, customer types. Ability to use these clusters to optimise their estate planning operations and improve ROI. This helped to roll out EOTF and new branch openings in areas where the analysis suggested strong performance.

To summarise I would say: incredibly professional; incredibly articulate in their findings and presenting their findings; very diligent in the work that has gone on in the background with the analysis that they have done. I have been highly impressed with them and so has everyone else that has come into contact with them

Head of Business Insights

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