Attribution Modeling – What is it?
I don’t want to go on another rant about how things were so easy in the good old days, but *clears throat* here we go again. All you needed was just a radio ad. Investing money on a radio ad in prime time meant that you could reach out to a measurable amount of customers. And the results were streamlined and to the point. You could actually statistically record the amount of increase in sales during that time period and put a monetary value for the transaction. At the end of the day, you would have a number that states the efficiency of your ad.
Things are much more abstract and chaotic in today’s digital landscape. Every brand is active on more than 7 social media platforms at the same time. They use an average of 13 unique types of marketing tactics and around 3 paid advertising platforms to get the required reach. Keeping track of all of these, the amount of time and money spent on them and the profit/loss margin for each of them can be a real pain in the backside. What do you think is the best way to keep track of their efficiency?
Attribution Modeling allows us to take a peek into how exactly your ads have been working and tap into the efficiency. There are various ways that you can approach this. Let us take a look at some of the different models.
The different models of Attribution Modeling:
The last Click is both the most commonly used model and one of the most inaccurate. The Last Click model assigns 100 percent of the revenue generated to the last customer touch point before a purchase.
In layman’s terms, First Click attribution is the polar opposite of the Last Click, it attributes 100 percent of revenue to the first consumer touch point. For example, if a customer first comes across your brand by clicking on an organic search listing, and then later spends £100 on your website, organic search is said to have driven £100 of revenue.
Last Non-Direct Click
This model is similar to the Last Click, except for cases when the Last Click is a direct visit. In such cases, this model finds the latest click that isn’t a direct visit and attributes 100 percent of the revenue to that channel instead. The rationale behind this model is the idea that once a visitor comes directly to your website they have already made the decision to buy from you, so the cause of that purchase is not the direct visit itself, but the one that pre-empted that direct visit.
Where the previous models deem that one part of the customer journey is solely responsible for the sale, the Linear model states that every step of the customer journey is equally responsible. It is the democratic attribution model; every touch point gets credit for an equal portion of the revenue a customer spends. Therefore, in a customer journey where the consumer had five interactions with the brand, each interaction will be credited with 20 percent of the revenue from that customer.
While the familiar path of Awareness > Consideration > Conversion has become more sophisticated in recent years, the fact that there is a journey, which starts with a potential customer finding out about a brand, is undeniable.
The Positional model acknowledges and represents this by combining aspects of First Click, Last Click, and Linear. Essentially it says that the first touch point and the last touch point are worth X percent each, and all the other touch points in between have the remaining percentage divided up evenly among them.
In the Time Decay model, the principle is that the closer (in terms of time) a touch point is to the conversion, the more influence that touch point had on the customer decision. While the Time Decay model is one of the more sophisticated, in both implementation and understanding, this does not make it the best or the one that everyone should use.