1. Ecommerce analytics
Welcome back. In this video, we will discuss ecommerce analytics.
2. Deep dive
In the previous chapter, you built a data source, created metrics for customers and orders, and understood the business goals, such as cross-selling and upselling. Munchy's management wants you to dive deep into quantity upsell strategies. This particular strategy increases sales and saves on shipping costs. Your goal now is to build a dashboard to present shipping costs by region and product. You will also build a what-if analysis dashboard to present the impact of shipping higher quantities of a product on sales and profitability. In this video, we will review the relationship between quantity, shipping distance, and the costs.
3. Shipping distance and the costs
Munchy's hasn't automated integration with shipping providers and does not capture shipping costs at the transaction level. Monitoring shipping costs remain a focus for the management.
Shipping costs go up as the distance increases. Munchy's has a warehouse in California on the West Coast of the US. This means shipping to East Coast locations like New York is slow and expensive. However, the management has prioritized reaching a larger customer base even with a lower profit margin. This is because they plan to open a new warehouse on the East Coast soon. To build this displayed map, you will merge a custom state-region mapping in the data source and color the map by region.
4. Shipped quantity and the costs
Let us look at a fictitious example of shipping a glass jar of spices from California to Texas. The cost of shipping an individual jar is $10. Suppose you were to ship a crate with nine spices; the package dimensions and the total weight increases. The shipment now costs $45 for nine jars or $5 per jar. The per unit cost went down as the quantity increased. These savings can be passed on to the business as extra profit or to the customers as extra savings. Besides, this is great for the environment — a win-win solution for everyone. Munchy's management wants to implement a similar strategy for their pet food business. But before they do, they want you to build a what-if analysis. Let us understand what that is.
5. What-if analysis
In a what-if analysis, you empower users to visualize the impact of changing parameter values. For example, average shipped quantity. When combined with interactive action filters, a user can see the impact on business operations. Using the what-if analysis dashboard you will build, the management can view the shipping cost savings at the individual product level as well as across the entire business.
6. Interactive analysis
As you build your dashboard, the following data visualization guidelines will help you structure your dashboard and effectively communicate insights.
Add appropriate page and chart titles that answer the goal of a dashboard and that of each chart.
Display key KPIs, for example, sales and shipping cost savings, in large numbers. These are also called big angry numbers, or BANs for short.
Interactivity using parameters improves user engagement and invokes follow-up questions.
And finally, text annotations help provide additional context around numbers and add navigational assistance.
7. Let's visualize!
Let us now start building our what-if analysis dashboard.