Hannah asks, "For attribution modeling, what model do you use on your Facebook campaigns?"
Facebook offers substantially similar attribution models as Google Analytics; most of these will fail to give you an accurate picture of every digital channel. Unsurprisingly, Facebook's models tend to paint Facebook in the best light possible; their data-driven attribution model, for example, only looks at Facebook performance. Which model to use depends on the length of your customer journey.
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today's episode, Hannah asks for attribution modeling, what model Do you use on your Facebook campaigns? So, Facebook offers substantially similar attribution models as Google Analytics.
If you're familiar with the models in Google Analytics, first touch, last touch linear time decay, position based, data driven.
Most of these models are have a Facebook analog, Facebook's attribution models are unsurprisingly all centered around the social network and the advertising you do on it.
If they are, okay.
They tend not to take into account all the other things that their campaigns could be doing and they tend not to take into account you interactions between campaigns outside of Facebook Just be aware that there are some pretty substantial limitations, especially if you don't have the Facebook analytics, pixel setup and properly working on all of your other digital properties.
Unsurprisingly, Facebook's attribution models tend to pin paint Facebook in the best light possible.
If you look at how things like the data driven attribution model works, it only works for Facebook's properties.
So Facebook, Instagram, the and the campaigns that you run on those platforms.
And so, again, you don't really get a very good picture of what is happening in terms of all those models.
which one to use, if you have to use Facebook's attribution modeling is going to depend on the the type of customer journey you have and how how long the path To conversion, when you look at models like first touch and last touch, if you have a very transactional relationship with your customers, they come in, they do their thing and they're gone, right and they don't hang around, they don't engage, they are not loyal to you, you are a commodity to them, then you know, first and last ditch work fine.
You know, if 99% of your transactions have a customer journey length of like one, meaning they come from one source, they do their thing and then they leave, then last touches fine.
You also don't actually need attribution in those cases because you know that 99% of your transaction is coming from one thing they come in and they do their thing and they leave.
If you have a more complex sales cycle, and one in which there's a lot of decision making, maybe multiple stakeholders, maybe a lot of consideration then out of the box time decay is the least bad model, as long as you set the window long enough to accommodate almost all the transactions that are possible.
So if it takes 60 days for someone to make a purchase your your window of attribution should be at least 60 days, ideally 120 right to cover all the outliers.
That said, again, Facebook is not going to give you a comprehensive look at how it functions with the rest of your stack.
For that you're better off using Google Analytics attribution models and looking at Facebook's performance in that, you'll want to make sure that you are separating out paid social media traffic from unpaid in Google Analytics, get that set up in your analytics settings first so that you don't mix organic and paid traffic yet together.
That's a critical flaw that a lot of folks overlook.
And then use, again the Google attribution models.
choosing one of those, again, same idea.
The first and last touch are, are great if if you are transactional linear models, where it's just even credit distributed across all channels, is appropriate in environments where you have absolutely no idea what's working, what's not.
And it's a good way to start experimenting and to see like, you know, is there a substantial difference in credit given in a linear model compared to say a time decay model? If there is, then you may be starting to suss out that some channels are more important than others.
The best models to use are ones that are not built into these pieces of software.
There's one, Google offers it in their attribution products.
But The useful part is really only an attribution 360, which is the paid version of the product.
They use what's called Shapley game theory, it is a machine learning model that looks at how models how channels change, based on when a new channel enters the mix.
And the analogy that is often used for that is a poker game.
You have four players sitting on a table, they're all betting certain amounts, and then a fifth player sits down on the table.
Not only do you look at how the fifth player bets, but you also look to see the behavior of the other four players to see if how their behavior changes.
You know, some guy who shows up clearly the sucker and a whole bunch of the other channels will start, they'll boys will start betting more heavily chaplet game theory is applied to your digital marketing channels.
If you add a new channel in, do all the other channels performance change in a positive or negative way.
The model that I have found works the best Again, this is something that requires a lot of technical experience to do is called Markov chain modeling where it behaves like a basketball game.
You know, if if Steph Curry is on the court, you know, he's going to, you know, shoot the free pointer, and he would be the example.
So the last touch, but the question is who assists him to get the ball to him? Right? In those cases, when you're looking at who's valuable on the team, you need to figure out who assists him the most, who assists the assist, etc.
And you can build a model of who is most effective and where the same thing is done in Markov chain modeling in machine learning for marketing channels.
Is there a channel that assists more? Even if it isn't, what gets the last touch in Now again, less helpful if 99% of your conversions are One touching done.
But if you have steps if your product is something that requires consideration, then it's a really good model to use.
So time decay, good for, it's the least bad of the models that are in the box.
Facebook's data driven attribution model.
Nobody knows what algorithm they use.
So I would be very reticent to recommend that first and last touch if your product is purely transactional, and there's no customer loyalty whatsoever, nobody ever comes back to your website after after visiting once.
And use the machine learning models if you have the technical and statistical capabilities to do so because that will give you the best answers possible based on what's happening, when you can use Google Analytics and Facebook analytics and see how it goes.
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