Tableau data in use: How to monitor customer acquisition
Updated: Aug 18, 2021
Acquiring new customers is always one of the top business strategies for any business looking forward to grow customer base and profits. However, many businesses in this customer acquiring spree don't take a step back to evaluate which strategy is working. Knowing the rate of customer acquisition over a certain period like a day isn't enough. But, being able to view the whole journey over a long period will provide a different insight. Therefore, in this article I will demonstrate how Tableau can help you answer this question.
Using Superstores dataset packaged with Tableau app, I will visualize customer acquisition over the period provided by the data. The goal is to show how this happens cumulatively. Our columns of interest are 'Customer ID' and 'Order Date'.
Connect Superstores dataset above to follow along.
Step 1: Compute customer acquisition date. (The date each customer made their first order)
Using Tableau LOD, I will compute the minimum 'Order Date' for each 'Customer ID', see below.
Step 2: Create a logic expression to separate acquisition date from other dates
Remember, this particular customer has had subsequent orders after the first one, therefore, it's good we separate these subsequent orders from the first order (equivalent to date of acquisition) using the formula.
Step 3: Lets do our analysis (build the view)
Drag day of Order Date to the columns.
Drag Count Distinct of Customer ID to the rows.
Drag the calculated field 'New/Existing Customers' to the filters shelf and keep 'New'.
Under CNTD(Customer ID), add a table calculation. -> Quick Table Calculations >> Running Total.
This chart gives us the general view of customer acquisition. However, for cases whereby a business has different avenues of acquiring customers, e.g Branches or Regions. This chart makes it easier to compare customer acquisition in the different Branches or Regions by dragging the particular category to the Color shelf. For this case of Superstores dataset, I will drag 'Region' to the color shelf. See below.
Related: Measuring customer loyalty
From the resulting chart, users can tell at a glance that the West region acquired more customers than the rest of regions, while South region had the least customer acquisition. This view not only gives the users the course level of analysis, but also enables them to view the finer level data through tool-tip action.
Using tool-tip action, you can see that on April 13, 2013 the West region had already acquired 205 customers with 3 customers being acquired on the same day. I hope this article was helpful to you.
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