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A leading pizza chain uses data science for business growth

Data science is the new toping to growth

Evidence-based Decisions Making for Business Growth

US based leading pizza outlet chain wanted to analyze the impact of introducing online ordering facility for each of its outlets located across the US and also identify feasibility of opening new outlets at the right locations.

Cosine Similarity Model:
  • Developed a cosine similarity model which identified the 10 most similar outlets based on key characteristics and compare their performance.
Clustering:
  • Set out the common characteristics of the best and worst performing delivery stores.
Rollout:
  • This functionality helps the client to identify the non-online ordering outlets that were most similar to the best and worst performing outlets and decide if introducing online ordering will improve the outlet’s sales performance.
Business Dashboard:
  • Created an interactive dashboard for quick view of the overall performance of all outlets across the United States.

Solution outcomes

The system developed with an initiative dashboard that helps the client to find detailed analytic reports and information for taking evidence-based business decisions.

Some of the information includes:

Impact Evaluation:
  • Ability to accurately evaluate the impact of introducing online ordering facility between an online outlet and the non-online nearby outlet.
ROI Optimization:
  • Ability to identify the outlet which is most likely to perform better if online ordering is introduced to expand the delivery rollout and optimize ROI
Outlet Attributes:
  • Understanding of what outlet attributes are associated with strong and weak delivery performance
Outlet to Avoid:
  • Ability to identify outlet to avoid for online ordering delivery rollout
Performance:
  • Ability to compare actual performance vis-à-vis’ target of new launches

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