his study presents an analysis of customer reviews from the Hambre Delivery platform,
focusing on improving user experience and the performance of partner stores. Through the
application of KDD (Knowledge Discovery in Databases) and Artificial Intelligence
techniques, data mining was conducted on the reviews, addressing three main metrics: product
quality, delivery time quality, and store quality. The analysis included calculating the averages
for these metrics, identifying stores with below-average performance, and creating a
notification system to alert the establishments. Additionally, a geospatial study was carried out
to map the distribution of stores by city, using Python libraries such as Pandas, Folium, and
AST. The results provide valuable insights into store performance, helping to identify critical
areas and opportunities for improvements on the platform. The study also presents a clear
visualization of stores on an interactive map, allowing for spatial analysis and expansion
planning. This work contributes to the optimization of the app’s processes and provides support
for future growth strategies and service improvements.
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