Data Visualization on Customer and Product Dashboard
The skills we demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
Background and Introduction
Customer data is becoming extremely appealing to companies in order to make more impactful decisions that will drive better business outcomes. In order for company executives to make better decisions based on information gathered from customers, the visualization of data must be outcomes-driven, straightforward, and easy to understand.
For the purposes of this exploratory activity, it is assumed that an online UK retailer’s leadership team is looking to explore areas of opportunity for their customer-focused efforts and product-focused efforts based on customer-driven e-commerce data gathered over the course of one year. The sample data set utilized can be found here.
Shiny App's Data
The Customer and Product Dashboard has three tabs:
- Customer
- Product
- Data
The Customer tab summarizes key customer-focused highlights and visualizes the spread of customers across the world. The info boxes containing customer-focused highlights (i.e., total customers, average customer spend, average number of invoices per customer) provide background on the current customer base. The map shows where customers are located across the world, which could be used to inform customer expansion efforts (e.g., increase hiring for account managers based on location). In future efforts, customer-specific drill-downs including top products ordered, types of products ordered, and frequency of orders could be incorporated. This could influence customer-specific marketing and upselling strategies.
The Product tab summarizes key product-focused highlights and displays how many products are sold to companies within each country. Similarly to the Customer tab, the info boxes (i.e., total products, average product revenue, average number of products purchased per customer) provide background on products offered from the online retailer. The plot showing total products sold by country visualizes where most products are distributed to, which could potentially inform operational and logistical decisions (e.g., where to open a new warehouse location). To further develop this tab, products most frequently sold together could be presented. This could influence product bundling tactics.
The Data tab contains the complete raw dataset. On the Data tab, users can explore the complete dataset if desired.
Conclusion
While having a complete and informative dataset is important, it is even more crucial to visualize data in a way that is clear and intuitive to the target audience. The Customer and Product Dashboard clearly portrays data differently based on the types of decisions (i.e., customer and product) that will be influenced.
The Customer and Product Dashboard discussed in this blog post can be found here.
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