Restaurant Transaction Analytics Study
An academic study, not a restaurant deployment. The modeled gains are scenarios, not results.
An academic restaurant analytics project examining transaction-level data across restaurants to explore profitability, patterns and operational improvement opportunities.
- Why
- I wanted to use business analysis to turn hospitality transaction records into defensible operational decisions.
How I built it
- I scoped an academic project around restaurant transaction patterns and operational decisions.
- I worked with Python, SPSS and Excel as analytical tools.
- I treated modeled profitability changes as scenarios, not actual improvements.
- To copy it you need
- Use a public or synthetic restaurant POS dataset, define KPIs, and analyze potential profit drivers.
Try it yourself
Copy this prompt and paste it into ChatGPT or Claude to try it yourself.
I want to try a version of the restaurant study on Jovan Diaz's What Are We Building? profile. It looked at transaction-level data across restaurants for profit drivers and operational ideas, using Python, SPSS and Excel. He treated every modeled profit gain as a scenario and never as a result. Start with a public or made-up restaurant sales dataset. Ask me which numbers matter, define a few KPIs, and then analyze what might drive profit, labeling each gain as a scenario. Ask me for anything you need.
Tools I used for this project
