You Ask, I Answer: Google Analytics Campaign Timeouts and Lookback Windows

In today's episode, Mike asks, is in Google Analytics, is look back window the same as conversion window. So this is a a good question. It's uh at first it can seem similar, but they're they're very different features. A conversion window in this case, the proper name of it is campaign timeout, and it's basically the amount of time that somebody can be enrolled in a campaign, which you did to them by tagging a link they clicked on with the UTM campaign tracking code, um, and subsequent actions within that campaign before they stop. So everything within Google Analytics operates kind of on like a timeline.

You do something, and then some time goes by, and then you do something again, and it's almost like a clock resets and says, Hey, you just didn't a new thing, I'm gonna say that you're you're you're back in the game, right? And then you need some more time goes by, and then that person doesn't do anything, and then whatever that window is that you set, uh, Google Analytics will say, Well, you know what, that was the last time you did something, and it's it's a a long time has passed. So the next time you come back, if it's outside the window you set, you can say, I'm gonna put you in a new campaign, uh, or I'm gonna treat you as though you were in uh maybe a similar the same link named campaign, but you are essentially a separate person at that point uh because you've gone outside that window. This is important for attribution analysis because uh if your campaign windows are too short, then essentially every time that person comes back outside of that window, they're treated as a new person, and that's not something that you want to have happen. You want to know that that's the same person um uh as much as possible.

And so there's two schools of thought on this. One is just make the campaign window as long as possible, which there is some sense to that. But if you have a product or service which has um repeat buyers and things, and you want to know uh and that window's a super short window, you may want to know that yes, this person came back and really should be treated as a new person for the for the purposes of understanding things like upsells and stuff like that. Another school thought is you know keep the the window uh as short as the sales cycle, which can be risky because again, if you want to treat that person as a new person, or do you want to know it was the same person the whole time? So let's look in Google Analytics where this is stored.

I'm gonna bring this up here. Uh in Google Analytics, the campaign timeout, if you go to uh your settings in the lower left-hand corner, go to tracking info, and then you go to session settings, and this is where campaign timeout is stored. And you can see it's got a maximum of 24 months. Out of the box, it comes with a a six-month campaign window. Um the general recommendation here is uh if it I would say if it's your your campaigns are less than six months, uh then keep it at this.

Uh if it's more than six months, then it should be ideally double what your average sales cycle is. So if your average sales cycle is nine months, make it 18 months. Why? Because you want to be able to catch those people who are anomalies, who who sit outside that window uh and uh and know that they're essentially are the still the same person. Uh in if you have a a sale that it occurs yearly, you definitely want to have this be maybe even be that 24 months to see is that person the same person over and over again.

Right. So you have to do some analytics now. Look back window is something uh different. Look back window. If we go into multi-channel funnels here into assisted conversions, you will see the the look back here.

Uh look back window is how Google uses time to do the attribution analysis itself in this window. And it's it always resets itself to 30 days. Um back window is how long of a time Google should take into account data for more complex attribution models. Um generally speaking, uh most people use Google Analytics with the default, which is last touch. And look back window doesn't really matter for that.

It's also a bad attribution model. Um look back window is more helpful for uh more complex models like time decay, where uh essentially there's half-life windows every seven days that Google assigns decline in credit to conversions that are to uh to touches that happened earlier in the past, saying, hey, yeah, you opened email, but you opened that email 80 days ago, and so the credit it should get is very little compared to that Facebook ad that you just clicked on two days ago. That should get more credit in the conversion because it's more recent. Your look back window uh essentially tells Google take into account however little or much um information we have here in order to uh from from a time perspective, in order to get a more nuanced view of how much how far back should we be looking to to give conversion credit to different channels. So if you'll see I have a 11 assisted conversions, 60 last touch conversions here.

If I set this look back window, crank it all the way to 90 days. Well, that didn't really change anything. Um let's do this here. 113 what 51 there, and let's see if there's a substantial difference here. You can see the assisted conversion value went down a little bit when I shortened that window because essentially we're saying when you get when you shorten that window, give credit only up to how far back to look.

So stuff that happened previously suddenly starts to lose credit because it happened so long ago it's outside this window. So instead, uh generally speaking, for most companies most of the time, there isn't a harm in keeping that window at 90 days just to be able to see what as far back as you can go deserves some credit when you're looking at these assisted conversions. What deserves a little bit of um credit and attribution for those conversions? So that's the where to how to use this look back window. This is especially important for e-commerce uh because e-commerce has actual dollar amounts built in, but it also does use the dollar amount set when you set your goals and goal values.

So those are the two timeouts and windows within Google Analytics that are important. And they're both very different in application. It's important to know what to use and where uh in order to get great answers. Remember though, with especially when it comes to look back window and attribution models and stuff, the ultimate goal is not to have a fancy model. The ultimate goal is to make good decisions to say, okay, what should I invest more in?

What should I invest less in? What's driving better results or worse results for me? And that's the purpose and function of this information. So good question, a good follow up question. Um as always, please leave your follow-up comments in the comments box below.

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