The attribution model is the way in which Facebook/Instagram and Google campaigns adjudicate (give credit for) sales. This means, the way in which user interaction with ads is measured and its influence upon conversion. Here we explain the attribution model of each platform!
📌 Clarification: whenever we’re talking about Facebook, we’re also talking about Instagram. Even though they are two different channels, both of them belong to Facebook and they are managed from the same Business Manager, where everything that applies to one, applies to the other as well.
👉 Standard attribution model
Facebook attributes by default with the 7 day click, 1 day view model. This means that sales that are generated within the 7 days after the ad click are credited, or if the user had an ad impression on the last day before the purchase.
Let’s think about a person that sees an ad from your site and clicks on it. Then, they visited the site but decided not to purchase right then. After a few days, they went back into your online store and finally completed the sale. In this case, if they clicked on your ad up to 7 days before the moment of the purchase, Facebook adjudicates that sale to that ad.
The same happens with the view. If that person saw the ad (meaning, your ad had an impression) and bought that same day or up to 24 hours later, Facebook also gives credit for that sale, even if they didn’t click on it.
The sale is credited to the date of the click. That means if a person clicked on the 1st of the month but ended up purchasing on the 7th, the sale is registered as credited on the 1st.
If you’re going to look at yesterday’s results in our campaigns, we recommend that you go back and look at them within 7 days, because you will most likely see more sales produced by our ads on that day.
👉 Other models
Although the precious model is standard, there are other attribution models that can be chosen on Facebook.
The choice of attribution model will depend on the type of business, of product, on the purchasing process, and the size of the website.
➡️For example, the purchase decision process of a piece of clothing is much shorter than that of a mattress. This has to do with several reasons. One of them is what has to do with how fashion impacts more due to its esthetics and it encourages a compulsive buy, but the purchase of a mattress has to be more studied due to its characteristics, differential qualities, and comfort. It isn’t only a matter of taste, but rather a purchase that requires research.
Also, the price of a mattress is much higher than a piece of clothing and that makes the decision require more time and only be made when one is sure to have compared it with the competition.
In this sense, then, it’s important to evaluate for each type of business what attribution model is fitting.
You can generate an attribution model by mixing up different time ranges of Visualization and Click.
The number of sales that shows up in our platform’s control panel will depend on the attribution model that corresponds to your business.
❗️Attention: We only recommend models outside the standard for websites with lots of traffic and conversion and with long and complex purchase processes. If it has to do with a small or new site, the standard attribution model is representative of reality because there are no other sources of traffic that generate conversions.
👉Standard attribution model
Google attributes, by default, with the 30 day after click model. This means that if a sale is completed up to 30 days after a person clicks on a Google ad, this platform will give credit as its own.
Just as we’ve said of Facebook, the same happens with Google. A user looks up a term that made your ad fire, they went into your site by clicking on it, but didn’t purchase right then, but rather visited again 29 days later to complete the operation. That sale will be credited by Google to that ad or to the last one that the user interacted with before making the purchase, up to 30 days before being completed.
Just like with Facebook, the conversions will be credited for the day of the click, with which the results of a particular date will improve when the 30 days of the attribution window have gone by.
👉Other ways of measuring
On Google you can also measure by last click, which means by the last click before the purchase. This is done through linking the Analytics account, which just so happens to measure conversions that way. In the subsection below, we explain it more!
Analytics is a very complete and useful tool for analyzing metrics in relation to your website, the traffic, and generated transactions. It takes into account all the channels from which traffic is generated on your site, be it Facebook, Instagram, Google, organic, Google pay, references, etc.
In this sense, Analytics provides a vision that allows you to understand how the different channels interact and how they impact your website. Nevertheless, Analytics can be a double-edged sword when it comes time for analyzing each channel separately.
The problem with that tool is that its attribution model isn’t right for all channels. Analytics measures last click, which means, the last click that the user carried out before purchasing.
In the case of Facebook and Instagram campaigns, they are generally focused on the upper part of the conversion funnel, meaning that in order to take the user to the website to get to know your products. That means that the user takes the longer route in finishing the purchase, but if it weren’t for the Facebook ads, maybe they wouldn’t have found out about your brand.
➡️ An example that is usually used for explaining the “unfairness” that Analytics commits with Facebook is a typical situation: when you go to work, you look at your social media and you probably click on ads for things that interest you. At that moment, although you had the intention of buying, it’s impossible to do so because it implies pulling out the credit card and going through the whole payment process which, while in public transportation, is hard to do.
So, it’s probable that when you get to work, you will search for it on Google from the computer and end up buying it. In that case, since Analytics attributes the sales by the last click, this sale would be credited to Google (which could be due to a paid ad or an organic one), even when if it wouldn’t have been for the Facebook ad, you would never have gone in and searched for it with the intention of purchasing on the website.
In this sense, it often happens that sales that should be credited to Facebook are adjudicated to channels that are focused on the lower part of the purchasing process, such as Google. And if we’re going to take the Analytics results into account to redistribute the budget, we would start from a mistaken diagnosis because we overvalue Google and underestimate Facebook. Put simply, if it were up to Analytics, far less would be invested in Facebook.
For the person to get in through Google, they have to first create the need. And that need is generated from the Facebook and Instagram platforms.
So, although Analytics is an ideal platform for following up on traffic, we don’t think that it’s reliable for attributing sales to the different channels.
That’s why on our app, we import data from the Facebook and Google platforms. That explains the reason if you see a difference between our control panel and Analytics. If you would like to understand this better, you can go to this article where we explain it.