Maggie asks, "How reliable is using programmatic impressions data that's collected in GA (with an understanding of its value and the contribution of programmatic to website conversions), to use this value as a proxy and apply to social to give us a better idea of Facebook performance?"
This is an interesting question that will require experimentation and analysis on your part. To use programmatic impressions data as a proxy for Facebook impressions in general, you have to prove a couple of things:
- Programmatic audience composition is highly correlated to your normal Facebook audience composition - same people
- Programmatic audience behavior is highly correlated to your normal Facebook audience behavior - same actions
Can't see anything? Watch it on YouTube here.
Listen to the audio here:
- Got a question for You Ask, I'll Answer? Submit it here!
- Subscribe to my weekly newsletter for more useful marketing tips.
- Find older episodes of You Ask, I Answer on my YouTube channel.
- Need help with your company's data and analytics? Let me know!
- Join my free Slack group for marketers interested in analytics!
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 Maggie asks, How reliable is using programmatic impressions data that's collected in Google Analytics with an understanding of its value and the contribution of programmatic to website conversions to use this value as a proxy, and apply to social to give us a better idea Facebook performance? That's a lot to unpack there.
The question that Maggie's asking is, can you use data from Facebook programmatic advertising? To make to draw conclusions about your Facebook's audience performance in general? That's an interesting question.
My first instinct was to say no, but giving it some more thought.
The answer is maybe it may be reliable.
But you need to do some, some math.
So to use any kind of advertising data as a proxy for your audience's overall behavior, you have to prove two things, same people, same actions.
So in this case, you'd have to prove your programmatic audience composition, the people that you're reaching with programmatic is highly correlated to normal Facebook audience composition, is it the same people? So for example, if you go to Facebook Audience Insights, and you look at your, your, your audience that you have access to their? Is it this? Is it the same as the audience to reaching for your programmatic audience composition? And you should be able to do that, as long as you keeping custom audiences for both.
But you want to look? Is it the same age groups? Is it the same gender? Is it the same locations? Do they have the same page likes? Do they have the same interests and affinities, same political orientation, whatever, whatever factors, you can determine about both audience, you want to see how much they overlap.
If you are reaching very different people with your ads than you are with your organic content, then the impressions data that you get from programmatic inside Google Analytics is not going to be helpful, right? Because you're you're essentially measuring different people.
If you're measuring, you know, souk on this hand, and he's doing he's, he's a fan of Celine Dion.
And you're, you're measuring a margarita over here.
And you know, she's a fan of Evanescence, they're gonna be very, very different people, and have very different behaviors.
So same people make sure that the same people first second, you then have to prove, and this is something you'll do with Google Analytics, you have to prove that they have the same behaviors or similar behaviors.
How correlated here is your Facebook audiences behavior from organic from programmatic? And that's something that you're looking for, you know, what pages do they visit on your website, what percentage of the audience converts, return user, time on page time on site, all those things that tell you, yes, if you've got similar people, and they're behaving in similar ways, and this is different than the similar people, because even even though you may, you might have the same people, they will behave differently, they can behave differently, if they come to you with different intent.
If you're running, you know, by now, ads on Facebook, those people that you're you're obtaining have a different intent than somebody who just clicked on a blog post article wants to read more, right, you can see that just just the difference in language alone, by now versus read more, you going to get very different intent, very different behavior, which means that using one set of behavior to try and predict another is not a good idea.
So you have to be able to show that these two audience behaviors are the same, or least highly correlated.
And if you can prove both same people and same actions, then you can use that impressions data as a proxy.
If you can't prove that, if you can't show Yes, the same people same actions, then it's not going to be very helpful.
And intent matters a lot.
If you look at your digital customer journey, you may see Facebook, social, and then like Facebook paid social, if you've got to configured correctly in Google Analytics, maybe, and probably are at different points in the customer journey.
Right? Facebook, organic social, more often than not, for a lot of people is at the beginning of the customer journey, that awareness building.
And Facebook paid is sort of you know, the deal closer gets is what not just somebody over to filling out that form or, or picking up something from the shopping cart.
If the behaviors of the same because you're running the same type of intent campaigns, then you may then you may have something to work with.
So if you are posting on Facebook, organic, social, you know, Hey, get to know us.
And you've also got a get to know us campaign in programmatic, then you may see similar behaviors.
But a lot of that is contingent on the analysis.
And that brings up one final point.
Your programmatic performance will have to mirror and continue to mirror going forward.
The unpaid performance, right.
So if you go from a get to know us campaign to a buy now campaign, the intent changes and your predictive strength for your for your model.
Let's say that, yes, you proved same people same actions, when you did the analysis that may drift, because you're changed the intent of the programmatic campaign.
So just keep these things in mind.
As you are trying to do this analysis, the answer is a solid, maybe you have to do the analysis.
We don't know enough about your audience to be able to make that determination.
If I had to guess, it's probably not a good fit, because most people use paid advertising in a very different way with a very different intent than they do on unpaid content marketing.
Interesting question, challenging question you got a lot of work to do.
Got a lot of homework to do.
But the answers will be valuable to you, even if you can't use it.
predictively you at least have established and you know much more about your audience now because you've done the analysis and you can see the difference between an unpaid audience and a paid audience.
And I think that's an analysis that every marketer should do.
As always, please leave your comments below.
Please subscribe to the YouTube channel.
Enter the newsletter and if you're subscribed, the YouTube channel hit the bell icon to be notified when I upload new videos.
As always, thank you for watching.
I'll talk to you soon take care what help solving your company's data analytics and digital marketing problems.
This is trusted insights.ai and let us know how we can help you
You might also enjoy:
- How To Start Your Public Speaking Career
- How to Set Your Public Speaking Fee
- You Ask, I Answer: Creating Content for Search Engines?
- You Ask, I Answer: Microsoft Clarity vs. Google Analytics?
- You Ask, I Answer: Quantifying Hallway Conversations?
Want to read more like this from Christopher Penn? Get updates here:
Get your copy of AI For Marketers