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Case Study: Ecommerce Analysis in Tableau

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, you'll investigate data from an online pet supply company.

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3 Hours4 Videos27 Exercises

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Course Description

Are you ready to apply your Tableau skills to solve practical business problems? For ecommerce businesses, increasing sales and reducing expenses are top priorities. In this Tableau case study, you'll investigate a dataset from a fictitious online pet supply company called Munchy's.

Use Your Tableau Skills With a Practical Case Study

First, you’ll analyze the sales dataset and find out which products are frequently bought together and in what quantity. You will then make upsell and cross-sell recommendations by building a market basket analysis.

Next, you’ll need to address the fact that shipping costs remain a big expense for online retailers. You’ll work on strategies such as shipping more of the same product to reduce per-unit costs. You will also need to understand where the customers are and what they buy to make recommendations to the management for a new warehouse location.

Analyze The Data and Visualize Your Findings

As you collate your findings, you’ll create calculated fields and various visualizations in Tableau, such as dual-axis graphs, highlight tables, and maps. Finally, you'll use filters and parameters to make your graphs dynamic and combine everything into a story to share your recommendations.
  1. 1

    Data Exploration

    Free

    In this first chapter, you’ll build a dataset for sales and expense analysis. You’ll combine multiple files, filter out invalid data, and create metrics for customers and orders. Using a self-join on sales data, learn to create a correlation matrix. Use the correlation matrix to determine products that are frequently bought together.

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    Analyzing ecommerce data in Tableau
    50 xp
    Build a product sales data source
    100 xp
    Product costs exercise
    100 xp
    Data clean up
    100 xp
    Create calculated metrics for customers
    100 xp
    Create order and shipping metrics
    100 xp
    Data source for market basket analysis
    100 xp
    Standardize attribute names and values
    100 xp
    Market basket visualization
    100 xp
  2. 2

    Ecommerce Analytics

    Next, you’ll create metrics for the most profitable products and customers. You’ll standardize location names and build a map of sales by state, before exploring the shipping cost metrics. Finally, you’ll build a what-if analysis to display the impact of shipping higher quantities on shipping costs.

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  3. 3

    Visualize Your Analysis

    In the final chapter, you’ll build multiple dashboards and present them as a coherent story. You’ll display the product and customer attributes that will result in the highest ROI for the upsell/cross-sell campaign. To round off, you’ll recommend specific actions to reduce shipping expenses.

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Datasets

Workbooks and DatasourcesMetadata sheet

Collaborators

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Maarten Van den Broeck
Collaborator's avatar
Iason Prassides
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Carl Rosseel
Dev Bhosale HeadshotDev Bhosale

Head of Business Intelligence at SOC Telemed

Dev is a seasoned management professional, consultant, trainer, and speaker. He discovered in early 2000s that Microsoft DOS is capable of displaying data in a graphical format. Ever since, he has been obsessed with helping people use data in a visual way. He has worked with some of the best data teams in the world, and holds Tableau Server, AWS Solutions, and Azure Fundamentals certifications. He has spoken at Tableau conferences, user groups, and online events. Dev lives in Washington, DC region with his wife and two children.
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