Wiwino, a proud icon in the wine industry, aims to understand the wine market better using data analysis. This project encapsulates extensive data analysis to provide insights into the global wine market. The dataset used for the analysis includes information on a variety of wines, their ratings, prices, countries of origin, and more.
Extract valuable insights from the given data and present recommendations for Wiwino to enhance sales, target marketing strategies, award best wineries, identify customer preferences, and provide better services to clients.
The database is structured as illustrated in this diagram. It includes tables for wines, vintages, countries, regions, grapes, and more.
We analyzed the data to answer several market-related questions:
1. Which wines should we highlight to increase sales?
Our initial approach was based on high ratings and affordable prices. However, wines with high ratings proved to be either exorbitant or scarce. Ultimately, we decided on wines with a large number of ratings and a price limit of €100. This assures popularity and availability, leading to increased sales.
2. Which country should we prioritize for our marketing budget? Our analysis found the country with the highest potential for our marketing efforts.
3. Which wineries are deserving of awards? Due to data constraints, we were unable to answer this question.
4. Can we group wines based on specific taste keywords? Unfortunately, we weren't able to form a cluster based on the most popular wine flavor combinations due to our team's expertise limitations.
5. What are the top 3 most common grapes worldwide and their best-rated wines? We identified the top 3 most common grapes all over the world and listed the top 5 best-rated wines for each grape.
6. Creation of a country leaderboard showing the average wine rating. We've created a leaderboard showcasing the average wine ratings for each country.
7. Recommendations for a VIP client who likes Cabernet Sauvignon. We provided the top 5 Cabernet Sauvignon wine suggestions for our VIP client.
Besides answering the questions, we provided creative insights and recommendations based on our data analysis.
We faced certain issues with the database regarding the linking of wineries with wines, inconsistency in wine count, and a lack of clarity on user structure count.
You can find the visualizations of our data analysis in our presentation.
- SQL for data extraction and analysis
- Python for data processing and visualization
- Excel for data presentation
You can access our source code in this GitHub repository.
This project presented an opportunity to glean valuable insights from a wine database, analyze user preferences and trends, identify potential opportunities for marketing efforts, pinpoint existing data-related issues, and provide well-founded recommendations to our client, Wiwino.
Despite data-related challenges and expertise limitations, we've managed to provide meaningful insights and suggestions that could potentially pave the way for increased sales, better client offerings, and data improvements in the future for our client.
Maintained by: Oleh Bohatov, Data Engineer/Data Analyst (Trainee) at BeCode