Data analysis is the process of collecting and organizing data in order to draw helpful conclusions from it. The process of data analysis uses analytical and logical reasoning to gain information from the data. The main purpose of data analysis is to find meaning in data so that the derived knowledge can be used to make informed decisions.
We used a scientific approach for data analysis and performed deep-dive examination to look through data and find insights for an US-based multiple restaurant chain company.

Features and Outcomes

Restaurant analytics involve gathering, measuring, and combining multiple sets of data to reveal clear, actionable insights. Through a deep-dive into data and analyzing it, we were able to find areas of improvement that lead to more profit generation, cost-cutting and more advantage to the company. Some of the outputs were:

  • Trip Segmentation 
  • Visit Pattern 
  • Loyalty Strategy 
  • Fast, medium, slow moving items
  • Largest, smallest revenue generating item 
  • Item Combination 
  • Sales spread on Time/Day/Month frame. 
  • Location wise Sales + Spread 
  • Pricing Strategy

Technology Stack:

Restaurant Analysis

Let's Get Started