Tool : Python
Visualization : Looker Studio
Dataset : KPMG
KPMG is a worldwide network of independent professional firms offering a wide range of services to various industries, government entities, and non-profit organizations. Their service areas include Audit, Assurance & Risk Consulting, Deals, Tax & Legal, Management Consulting, and Innovation & Digital Solutions.
Within KPMG's Digital Solutions, the Data, Analytics & Modeling team will be utilizing their expertise to analyze data sets on behalf of Sprocket Central Pty Ltd, a company specializing in bicycles and bike accessories. The objective is to assist the client in developing and optimizing their marketing strategies.
To achieve this, the client has provided KPMG with three datasets, including customer demographics, customer addresses, and transaction data. Through effective data analysis, valuable insights will be derived to drive Sprocket Central's marketing success.
Sprocket Central Pty Ltd seeks assistance in handling their customer and transactions data. Although they possess a substantial dataset regarding their customers, they lack the expertise to effectively analyze it for optimizing their marketing strategy. Recognizing the significance of optimizing the quality of customer datasets, they understand that improved data quality enhances the potential to drive company growth.
In response to this, the client has entrusted KPMG with three datasets:
- Customer Demographic
- Customer Addresses
- Transactions data from the past three months
The main objectives are to assess and evaluate the data based on Standard Data Quality Dimensions and subsequently devise strategies to address any identified issues. This endeavor aims to equip Sprocket Central with the valuable insights needed to propel their marketing efforts to success.
The marketing team of Sprocket Central Pty Ltd aims to enhance their business by analyzing their current customer dataset to uncover valuable customer trends and behavior. Using the existing labeled dataset consisting of three datasets (Customer demographic, customer address, and transactions), the objective is to recommend which of the 1000 new customers should be targeted to maximize the organization's value
- Create customer segmentation using the RFM model.
- Analyze customer trends, behavior, and demographics.
After building the model we need to present our results back to the client. A list of customers or algorithm won’t cut it with the client, we need to support our results with the use of visualisations.
- Develop a dashboard with looker studio