Project 2 - Supply and Demand Gap Analysis
Project 2 - Supply and Demand Gap Analysis
Bridging the Plate: Supply and Demand Gap Analysis of Bengaluru’s Restaurant Scene Using Zomato Data with Power BI
The detailed documentation of the project should contain the following:
- Aim
- Introduction
- Problem statement
- Methodology
- Analysis
- Insights
- Recommendations.
- Conclusions
Aim:
To identify and analyze the gap between the demand (customer interest) and supply (restaurant capabilities) in Zomato-listed restaurants using available data and to recommend strategies for reducing those gaps.
Introduction:
With increasing competition in the food delivery industry, understanding the mismatch between what customers demand and what restaurants offer becomes crucial. By analysing factors like rating, online order availability, cost, and customer preferences, we can highlight areas where demand isn't effectively met.
Problem Statement:
Despite high customer interest in certain types of food or services (like online ordering), not all restaurants fulfil these demands efficiently. This project aims to pinpoint mismatches and provide actionable insights to restaurant owners or aggregators.
Methodology:
- Data Cleaning – Cleaned rating values, standardized column names.
- Feature Engineering – Converted categorical variables (e.g., online order) into binary.
- Demand Proxy – Used votes & ratings as indicators of demand.
- Supply Proxy – Used online_order, book_table, and food category.
- Gap Identification – Compared high-demand restaurants vs. service capabilities.
Analysis Plan:
Key Data Points:
- Votes = Demand Indicator
- Rate = Customer Satisfaction
- Online Order / Book Table = Supply Capabilities
- Liked Food = Popular Demand Themes
- Calculating Demand score by DAX = Demand_score = ('Zomato-data-'[Rating]*'Zomato-data-'[votes]/'Zomato-data-'[approx_cost(for two people)])
Visualizations:
- Clustered bar chart: Like food by count of rate
By this chart, we are getting a clear Idea that Biriyani is the most selling food and liked food across all the orders.
- Line and stacked column bar – Correlation between votes, rate, cost.
By this line stacked column chart, we have rating in X axis and sum od votes and approx. cost for 2 people in Y axis< sum of votes and cost of 2 person are in bar form so even though the hotel has good rating and vote the cost per 2 person is low.
- Stacked Bar Chart – Restaurant name Vs sum of demand score
By this chart, we can clearly understand which hotel has the highest demand. we have used a DAX formula here calculating the demand score using votes and rating.
- Ribbon chart – Online order availability across high/low voted restaurants.
In this chart, we are getting the idea that online orders for food ahs more reviews and votes
- Pie Chart – Distribution of restaurant types (listed_in_type).
6. Pie char: restaurant name Vs count of liked food
In this chart we are getting to know that percentage of liked food by each restaurants.
7 . Gap Chart – Restaurants with high votes but no online order/table booking
In this graph, we are getting an Idea of which restaurant has the highest votes and rating, and whether they have an option of ordering online or not, we have sorted the table according to the sum of votes and Rating.
8 . Cost vs Most liked food vs demand score – To identify pricing imbalance.
Insights :
- Restaurants without online ordering had 40% fewer votes on average.
- “Chicken Tikka Masala” and “Biriyani” are top liked dishes, but not uniformly available.
- Some restaurants rated high despite not offering bookings—suggests potential service improvement area.
Recommendations:
- Promote online ordering for restaurants with high vote count but no such option.
- Standardize popular dishes like Biriyani across more outlets.
- Offer table booking options for high-footfall establishments.
- Optimize pricing strategy for restaurants with good ratings but fewer votes.
Conclusion:
By identifying restaurants that have high customer interest but lack key services (like online ordering, and favourite dishes not available in the outlet), Zomato can work with partners to bridge the supply-demand gap and enhance customer satisfaction.