Quantium-Data-Analytics

This repository consists of 3 tasks for completed the Quantium Data Analytics Virtual Experience Program by Forage using Python.

Certificate of Completion: https://insidesherpa.s3.amazonaws.com/completion-certificates/Quantium/NkaC7knWtjSbi6aYv_Quantium_FP4uifGCw2g4B733o_1624611954645_completion_certificate.pdf

Introduction

Quantium has maintained a data collaboration with a prominent supermarket chain over the past several years, during which this supermarket has been providing transactional and customer data. Our team of employees work together to harness the power of data to drive revolutionary change that benefits us all and deliver the best results for our clients. As a data analyst at Quantium, your role involves delivering valuable data analytics and insights to assist the company in making strategic decisions.

Supermarkets routinely alter their store layouts, product offerings, pricing, and promotional strategies. They do this in order to meet the evolving needs and preferences of their customers, stay competitive in a dynamic market, or take advantage of emerging opportunities. The Quantium analytics team actively participates in these processes, assessing and analyzing the outcomes of these changes and offering recommendations regarding their success.

Task 1 - Data preparation and customer analytics

Conduct analysis on your client's transaction dataset and identify customer purchasing behaviours to generate insights and provide commercial recommendations.

• Analyze transaction and customer data to identify trends and inconsistencies.
• Develop metrics and examine sales drivers to gain insights into overall sales performance.
• Create visualizations and prepare findings to formulate a clear recommendation for the client's strategy.

Task 2 - Experimentation and uplift testing

Extend your analysis from Task 1 to help you identify benchmark stores that allow you to test the impact of the trial store layouts on customer sales.

• Define metrics to select control stores.
• Analyze trial stores against controls.
• Use Python for data analysis and visualization and summarise findings and provide recommendations.

Task 3 - Analytics and commercial application

Use your analytics and insights from Task 1 and 2 to prepare a report for your client, the Category Manager.

• Use the Pyramid Principles framework for structuring the report.
• Submit a report that incorporates data visualizations, key insights, and recommendations.