Customer Acquisition Cost is an important metric to understand the return on investment you’re getting from different marketing channels.
With some marketing channels you can see exactly how much it has cost to get a conversion. However, some other channels can be more complex. If a website visitor found your company’s blog post while searching on Google and then converted, how much did it cost to acquire that customer?
A simple and DIY way to work this out is to use a combination of Google Analytics data and your own marketing spend added to a Google Sheet.
In this blog post, I’ll show you a method for calculating the cost of acquiring customers in Google Data Studio.
1. Add your Marketing Spend data to a Google Sheet
So I’ve added in some hypothetical marketing spend to a Google Sheet.
It includes a Notes column to indicate how the money was spent.
You’ll notice there is no Date information in the table. Unfortunately this means that in the Data Studio report we won’t be able to adjust the date range so that the Spend changes.
Therefore this type of reporting is best suited to looking at a weekly, monthly or quarterly overview of your marketing spend and conversions.
2. Add your Google Analytics and Spend data sources to a Data Studio report
First, add your Google Analytics data to your new Data Studio report.
Then add the Google Sheet which contains your Spend data.
You should now have both data sources added to your report, as shown below.
3. Blend the Google Analytics and Spend data together
The next step is to blend the Google Analytics and Google Sheet spend data together. This will give you a Blended data source.
To do this, click Resource > Manage blended data > Add a data view.
We can use Channel from the Spend sheet and Default Channel Grouping from Google Analytics as the join key to blend the data.
I’ve added in a ‘purchase’ goal completion from the Google Analytics data source.
When we’ve blended the data this is what our new data source should look like.
Click save and now we can move on to creating charts with our new blended data source.
4. Create a table showing Spend, Purchases and Customer Acquisition Cost
Using our new blended data source, which I’ve named Spend & Purchases, we can now create a table displaying this data.
Shown below is what the table data tab should look like.
It should have the following dimensions and metrics;
Dimensions: Channel, Notes
Metrics: Purchases completed (SUM), Spend (MAX) and a new calculated metric CAC per purchase
Customer Acquisition Cost per Purchase shows the amount of money spent on marketing for each purchase on the website.
The calculated metric CAC per Purchase is created as follows.
MAX(Spend)/SUM(Purchase Completed (Goal 1 Completions))
Now that we’ve created our CAC per purchase metric, we can create the table.
5. Create a chart showing Spend, Purchases and Customer Acquisition Cost
Next, we can create a line and bar chart showing Spend, Purchases and Customer Acquisition cost per purchase.
We set up the data tab in the following way;
Metrics: Purchases completed (SUM), Spend (MAX), and CAC per Purchase (created again using the same formula shown above).
We can have Spend and Purchases as bars and CAC per purchase as a line on the chart. Have Spend on the right axis and Purchases and CAC per purchase on the left axis.
Our finalized chart should look similar to what is shown below.
6. Looking at the Data Studio report
And now we can talk a look at our completed Data Studio report!
What does this tell us? It allows us to see that the cost of acquiring a customer via Organic traffic is $11.68 while the cost of getting a customer through Paid Search is a whopping $57.69!
This suggests a number of possibilities, such that our blog posts are really effective at converting website visitors, our paid adverts are useless at converting website visitors or a number of other scenarios.
Anyways, I hope you found this useful. Obviously this is a simple overview and doesn’t take into account a lot of the complexities of digital marketing and attracting customers to your site. But it does show how you can use Data Studio to report on your data and as a starting point for analysis of the data.
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