# The Hidden Complexity of Measuring Return on Ad Spend

I recently switched from WordPress.com’s data team to its marketing team where I’ll be using my dev and data-science background to help with our marketing efforts. I’m really excited by it because marketing is an area where I don’t feel particularly strong and now I’ll have a lot of opportunities to learn the ins and outs. As I pick up new things that are generally applicable, I’ll try to share them here on this blog.

This week I’ve been learning about how we calculate the profitability of our online advertising campaigns. I’ve done some work on this previously, but am really getting a chance to dive into now. At first it might seem like a simple calculation, but this rabbit hole goes quite deep.

Lets start with a very simple example: You spend \$100 on AdWords; a handful of people click on your ads and it leads to 2 purchases totaling \$120. Your ROI is \$120/\$100 – 1 = +20%. There’s also a metric known as Return on Ad Spend (ROAS) which is just revenue divided by cost which in this case would be \$120/\$100 = 120%.

Nothing too complicated here… or is there?

How long do people who click on the ad have to make a purchase for that purchase to be attributed to the ad? If they clicked on your ad on May 1 and purchase the same day, you probably want to attribute it to the ad. But what if they don’t purchase until August 1? Did the ad on May 1 cause the person to make a purchase 3 months later? Probably not, but maybe.

One option is to build an internal tool that keeps track of which ads a user clicks on prior to signing up and making a purchase. When they click on an ad, you keep track in a cookie details about the ad. Then when they sign up for an account, you tag their account with those details. When they make a purchase, you then know which ads they clicked and in which order. Even in this case though, you won’t be able to tell who saw your ads but did not click on one.

What if a person clicks on your AdWords ad on their laptop, signs up (at which point you can tag the user in your internal database so you know they came from AdWords), then jumps on their tablet and makes a purchase. Because you tagged the user, your internal tool can attribute the purchase to AdWords, but AdWords won’t because they didn’t start and complete the purchase on the same browser. Unless they’re signed into a Google account, then AdWords can figure out that they’re the same person.

Similarly, if they click on your ad on their laptop, then sign up and make a purchase on their tablet, you won’t be able to tag their account because the tablet can’t access the laptop’s cookies. Here again, AdWords might still count it as a conversion if the user is signed into their Google account.

If you run a service with recurring revenue, do you try to estimate their lifetime value (LTV) when calculating the profitability of the ads? You should, but that also introduces complexity. The type of people who you advertise to might have different purchasing behavior than your other users. They might spend more on average – or less. They might renew at a higher rate – or lower.