• rds team

Tableau data in use: How to monitor customer acquisition

Updated: Sep 3, 2020

Acquiring new customers is always on the top business strategies for any business looking forward to grow customer base and profits. However, many business in this customer acquiring spree don't take a step back to evaluate which strategies 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 we'll demonstrate how Tableau can help you answer this question.

Using Superstores data set packaged with Tableau app, we'll visualize customer acquisition over the period provided by the data. We aim to show how this happens cumulatively. Our column of interest is 'Customer ID' and 'Order Date'.

Connect Superstores data set above to follow along.

Step 1: Compute customer acquisition date. (The date each customer made their first order)

Using Tableau LOD, we'll 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) required in our analysis using the formula below.

Step 3: Lets do our analysis

  • 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 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 different Branches or Regions by dragging the particular category to the Color shelf. For this case of Superstores data set, 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 acquisition. This view not only gives the users the course level of analysis, but it also enables them to view the finer level data through tool-tip action.

Using tool-tip action, we can see that on April 13, 2013 the West region had already acquired 205 customers with 3 customers being acquired on same day. I hope this article was helpful to you.

Stay tuned for the upcoming articles on Tableau for data analysis. Thank you for reading.


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