Executive Summary:
The Dataset is from a Major retail firm that sells children's clothing.
Strategy is to increase profits through:
- Market segmentation
- Demography and Sales Analysis
- Elasticity modeling and Market Basket analysis
Visualization areas:
1.Intro
- Contains snippets of different segments.
- Segmentation is done through a tool called Latent Gold. K-means clustering could also be used,but since this method has arbitrary Cluster and seed inputs, chose Latent Gold which provides segments based on Probability scores.
2.Demography
A detailed analysis of different segments based on
- Age, Income, Education & gender
- Mode of Communication
- Location
- Added an interactive segment slicer
3.Sales
Analysis of product Sales for different segments using the following Visualizations:
- Top 5 Products by Revenue
- Revenue by month and Percent Change
- Sales vs Units by Year - Added a play axis containing Year
- Sales vs target
4.Analysis:
An interactive slicer containing different segments. Please note that this page makes sense only when a segment option is selected.
Price Elasticity Analysis:
- Select a Segment and a Product to view Elasticity characteristics. Suggested price change and predicted revenue are displayed.
- Analysis is done using Linear Regression with SAS. An alternate way to do this is by using an R script with Power BI.
Market Basket Analysis:
- Find which products to combine to get the most out of the segments.
- Analysis is done using Logistic Regression with SAS and Product affinities are displayed for every segment.
5.Challenges faced:
- To pick which variables to segment on. Zeroed in on important behavioral and product attributes to achieve this.
- Since Original Dataset had 220 features, choosing which ones to visualize required significant data munging.
- Price Elasticity Analysis was done for 21 products each in 5 segments.
- Market Basket Analysis involved performing logistic regression for 20 different products in every segment.
- Involved Python code, power queries and pivot tables in Excel to bring data to a clean format.
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