Since the dawn of optimization tools in the ecommerce world, marketers have always asked one question: How much money could this marketing tool make me?
And the truth is that usually, there’s no simple answer.
Let’s see an example to understand why it’s not that simple!
Let’s say that someone reaches your site by clicking on a Facebook ad, and then makes a purchase. You can reasonably connect this purchase to your Facebook ad.
But let’s assume another situation: this visitor doesn’t buy when they land on your online store. They come back a day later by searching for your brand on Google and clicking on your paid Google ad, and this time they make a purchase. Is it attributed to the first Facebook ad or the second Google ad?
Attribution measurement isn’t easy, and although Google Analytics hides how complex it is, you will still need to be fully aware of how it works in the ecommerce world.
Depending on the attribution model you choose, there could be varying end results.
In the previous example where the visitor returns to your website for a second time, the winning ad depends on the fact of whether you use “first-click” or a “last-click” attribution model to determine your champion.
When measuring your popups’ (or any onsite CRO tool’s) performance, there are some aspects you need to consider before evaluating any results. Let’s see what those are!
1. Attribution event
The first main aspect is the event.
So what’s the user interaction that you’re keeping an eye on when it comes to attribution? There are three main event types that you can use:
1. Conversion-based: This is when we assign revenues to a popup only when it leads to actual conversions (e.g. the user subscribed). This is the most popular attribution method. For example, this is used when measuring “Total Attributed Revenue”.
2. Impression-based: Impression-based attribution means that you assign revenue to a popup when it was shown to visitors. They’re typically used when you can’t measure attributions based on conversions (e.g. there’s no CTA on the popup or you’re A/B testing it against no popups) like when you measure “Campaign Assisted Revenue”.
3. Pageview-based: The most generic and less popup-specific measurement method is to split the traffic and measure how much each segment spends on your website. In this case, the attribution event is basically the pageview. Once a user lands on your website, they’re assigned to different segments. And the amount of money they spend—will be attributed to their respective segment, independent of popup impressions or conversions. This is used mostly when measuring Net Assisted Revenue.
2. Attribution window
The second main aspect of revenue attribution is about relating a time window to a user’s decision to buy. This has a direct correlation with a specific popup that the user saw within a selected timeframe, and the result was that it convinced them to convert.
For example, if a visitor makes a purchase 2 minutes after they opted in for a coupon on your popup, it’s quite obvious (and it’s easy to measure in Google Analytics since it’s session-based). This conversion would be attributed to your popup.
But if they leave your site without buying, come back a month later because of a follow-up email, and use the same coupon, where would that conversion be attributed to?
There are two main attribution windows you can measure and use:
1. In-session attribution: This is when purchases are only attributed to your popups if they happen in the same session.
While this attribution window is easy to measure, it’s usually also quite misleading because it doesn’t bring other variables(like collected emails, phone numbers, or successful on-site chat assistance) into consideration.
2. 5-day attribution: Often users aren’t ready to buy the first time they visit your site, but luckily, popups help you retain their contact details (email or phone number). If they come back later after subscribing through a popup, it makes sense to attribute some part of the revenue.
Compared to in-session attribution: here you can measure how much money users spend within a 5-day span. Usually, we consider this window a reasonable attribution period.
One other thing you need to decide on is if you’re measuring the performance of a stand-alone popup campaign and its variants, or the overall performance of the popups on your store. Depending on your goal, there are two main types of measurements you could use:
1. Campaign Level: It makes sense to attribute revenue to campaigns if you want to compare two campaign variations or determine whether a campaign/message is working or not.
2. Store Level: If you want to find out if your popups are effective or not, you can use store-level measurement. This means that you attribute revenue to any user that converts through popup impressions or conversions.
As you can see, there are several attribution models. And understanding their differences will allow you to make sense of the three main Assisted Revenue types. Then, you’ll be equipped to use them to grow your store or troubleshoot your existing in-house processes.