Show Resources
Here were the resources we covered in the episode: Analysis of Job Titles vs Functions
Systematic Approach to LinkedIn
Targeting
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Show Transcript
LinkedIn only understands 55% of job titles. Wait, what? Really? What does that even mean? Well, we're dissecting how Job Title works on LinkedIn ads today on the LinkedIn Ads Show.
Welcome to the LinkedIn Ads Show. Here's your host, AJ Wilcox.
Hey there LinkedIn Ads fanatics. So I put a post out about a month ago that mentioned a stat that I use, and quote quite regularly. I've said in the past, LinkedIn only understands 30% of job titles. And the post got a lot of engagement and several people question that stat. Where I got it from, not to mention the number of LinkedIn employees who've messaged me on the back end and said, Hey, AJ, where did you get that stat? I'm curious. And of course, no one's very disrespectful. No one's commenting, like AJ, you're a liar. That's bullcrap. But I wanted to walk you through my methodology of how I came up with that stat. And especially to inspire you guys all to do the same thing. I want everyone doing research to better understand how the platform works. Well, after being questioned on that stat, the 30% stat. I'm happy to report that we dug in and reran a bunch of research, and found that LinkedIn had actually improved, its targeting quite a bit in the last several years. So let's dive in now and explore.
I think, first of all, what you need to understand is that job titles as a field on LinkedIn, are freeform, meaning that anyone can type whatever they want. You can come up with your own title, you can use a standard one that's been around for years. And LinkedIn, not to mention any other platform, really can't be held accountable for trying to understand every single weird and odd job title out there. I'm connected to a CEO whose job title used to be Chief Trashcan Emptier something cute like that. And of course, LinkedIn is going to look at that job title and say, I have no idea who that is or what they do. So what LinkedIn does is it takes a look at the job title and tries to categorize it in which job functions in which seniorities it should fit. And I would say for the most part, it does a pretty good job of categorizing these. And then they take it a step further, which I don't actually like all that much. There's this concept called super titles. And you won't know about LinkedIn having super titles, unless you have access to LinkedIn's ads API like we do, because it's one of the elements you'll see in the API. But basically, what they do is they'll take and group similar job titles together to roll up into one kind of a master job title. So when you go and put in the job title of Salesforce Administrator, you probably don't know this, but you're probably adding quite a few other job titles along with it. And we're really trusting LinkedIn, that they've done a good job of grouping these job titles together. And the problem is, you can't actually see anything about your super title and you can't see the other job titles that are being targeted underneath it. Like I said, most of the time, LinkedIn does a pretty dang good job of this. We have noticed a few weaknesses. The biggest weakness we've seen is, for some reason, the job title Marketing Specialist gets rolled up to Chief Marketing Officer. So we had a client where we were targeting CMOS, and we noticed that a lot of Marketing Specialists were coming through their forms. And so of course, we did the great agency thing, we went in, and we excluded the job title of Marketing Specialist. And then all of a sudden, the whole campaign was too small to run. We were targeting CMOS, specifically by job title and as soon as we excluded Marketing Specialists, boom, the whole audience went away. I definitely think that this is a bug, I think someone miscategorized that one job title. But I think it's fair to say this is probably not the only mistake that LinkedIn has made. And so you do have to be pretty careful when you're using job title targeting. And let me start by saying, I hope none of you get the idea that AJ hates job title targeting, because I certainly don't. I still use it a lot. And I still recommend that everyone else use it a lot, too. But the reason why I care so much about this is we need to understand how each type of targeting works so we can use that as a tool to help us optimize towards whatever our goal is. For one client, I might use only job title targeting. And another I might do 10% job title targeting and 90% job function targeting. And it just totally depends on a client's budget, and who their target audience is. If you go back and listen to episode two of this podcast, we talked about the systematic methodology for how we go about targeting an audience. I don't want you to misunderstand and think that what I'm telling you is job title targeting is weak and doesn't have a place and you shouldn't use it. I will say though, whenever we use it, we generally have other campaigns targeting the same persona through a different way that are meant to support that campaign. And, of course, we're going to analyze the day data afterwards to help us understand, you know, did Job Title outperform or underperform? Do we need to bid one of them up, one of them down? What can we learn about how we are targeting these people? So go back and listen to episode two to go way deep into that. And if you stick around till the end of the episode, I'm going to go over a couple of comments that we got on that post that I told you that had a lot of engagement with really good questions, really good input. And we'll answer those questions right here at the end. So make sure you stick around. And here's a quick sponsor break and then we'll get to dive into the methodology of the data collection.
5:33
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Alright, let's jump here into the methodology. We know that job function is by far the most broad way that we can target someone on LinkedIn. And sometimes we might have a job title, like my example of Salesforce Administrator that we can't target by job function. There's no job function for Salesforce Admins. And actually, I just checked they do they fit underneath the IT job function. Okay, that was interesting to know. So if job function is the most broad, and we want to test job titles, which we know is one of the most narrow, the best way I could think of to do this was to take job function and seniority, a combination of which has a really common job title associated with it. And then compare those audience sizes to the job title. So I'll give you an example. If we take Marketing Managers as the job title, that's a pretty standard job, that there should be a lot of people who have and if we take a look at the audience size associated with that, and compare it to the audience size of the job function of marketing, plus the seniority of manager. Ideally, if LinkedIn had a perfect understanding of all job titles, those would be the exact same audience size because they're essentially the same audience. So that was what I set out to go understand and prove. So as I review this data, it's important to understand that there's a lot of job titles that aren't directly aligned with a direct job function and seniority. So we can't compare, we won't have these insights. So what I wanted to do was compare all of the ones that we can see the ones that we can understand. And hopefully that gives us a good idea of maybe what we can expect for the ones that we can't see and can understand. For everyone to follow along. If you go down in the show notes below, you can click on a Google sheets link. And that will take you to the Google sheet where we put all of this research. And please let us know anything that you've improved. Or if you've taken this and started your own study or understanding somewhere else, please, we'd love to take part in the analysis with you. And also, if you can tell anything that we've missed or should be improved in our testing methodology, please speak up, let us know. So what we did is we took the top five job functions that are really standard that was Sales, Marketing, Finance, IT, and Operations. And we paired each of them with the seniority of Manager, Director, VP, and C-level, we went and collected their audience sizes, as well as their suggested bid ranges. And then we compare those against campaigns that we put together, where we just expressly targeted those job titles. So for instance, under Marketing Manager, there were things like Digital Marketing Manager and other types of Marketing Managers. And I went ahead and added them to the list to kind of buoy them up. In that particular list, I didn't include product marketing, so anything with product, I left it out, just so you understand. And you can see all the data there in that sheet. You can see those that LinkedIn understands the very least, and those that LinkedIn understands the very best. There are a couple of call outs that I've got for you on this one. For instance, VPs of Operations, LinkedIn only has 13.6% of them accounted for in job titles. I thought that was pretty interesting, because a VP of Ops should be a pretty standard job title. Then we have like an Operations Manager, which LinkedIn actually really understood quite well. It matched really high at 77.8%. So those were our highs and lows. And there were a couple really odd ones, for instance, Marketing Managers, the job function audience size on this one was only 360,000, but the job titles size was 640,000. And I'm pretty sure that's a weakness in LinkedIn job function targeting, because Marketing Directors have 490,000 and generally, there are more managers than there are directors. So I think the actual size on LinkedIn of Marketing Managers should be somewhere around the, like 900,000 or a million. But the targeting only showed me what it showed me so that was weird one for sure. Something similar happened with IT managers. There were only 480,000 IT Managers by job function. But when I combine them by job title, there were 630,000. So all in all, there were three where job function actually caught fewer of these people than job title. But for the most part, it worked as expected, and there were many more under job function than there were under job title. And when I combined all of the data for all five of these job functions, we came out with an average of 55%. Meaning that LinkedIn probably understands 55% of the job titles for these super standard job title positions. In my defense, because these are the ultras simple straightforward job functions and titles that means that the super not straightforward ones, like Marketing Ninja or Sales Expert, probably match at a much lower percentage. But at least with this methodology, I'm comfortable using the stat that LinkedIn understands about 55% of job titles. Now, when you go and look at this data, if you scroll over to the right, you'll notice that I collected the floor bid, the low recommended bid, the recommended bid, and the high bid for each of these audiences that we built on job function and on job title. And I started with job title, because it's usually the smallest and I subtracted the job function audience. So what you get here is any number that is positive, it means that the job title was more expensive, it had a higher either recommended or minimum bid than the job function campaign that it's associated with. And I did it this way because I expect that job titles are going to be more expensive because it's more targeted and because LinkedIn understands fewer of those job titles, and more people are bidding on them, they should be more competitive. And what we found is, on average, a job title's floor audience is 17 cents higher than the job function audience. When you look at the low recommended bid, though, it drops to job titles only being three cents more expensive on average. When you look at the recommended bid that drops to basically zero, meaning that a job function's recommended bid is usually a cent higher than the job title. And then when you get to the highest end of the bid range, on average job title is 12 cents cheaper. And I'll be honest, I don't have a whole lot of faith in the recommended bid ranges that LinkedIn provides, but if this is any sort of clue as to what the auction actually looks like, what the level of competition looks like, for each of these audiences, then that's really insightful to understand that Job Function is actually more expensive when you're bidding high and Job Titles are going to be less expensive when you're bidding low. So definitely go familiarize yourself with the data, get an understanding for it. And of course, please use it to start your own research and share with us what you find. So this conclusion that we came to have LinkedIn only understanding about 55% of job titles, that means that job titles are a pretty tight way of targeting. And that's why we like it, we're glad that there's a tight way of targeting because if we only had to target by job function and seniority, that would be way too wide, way too large of audiences and we love this ability to a super narrow target on something. And this is why it's also ultra important to utilize all of the different targeting types that LinkedIn gives us. Understand how all of them work so that you don't miss any audience members. And again, go back to episode two to learn about those targeting strategies. You can also look at Episode 11, to understand the various targeting options that there are to do a deep dive into how each of them work. And as a reminder, this shouldn't dissuade you from using job titles in your targeting, they still are very valuable. Okay, like I promised, here's a couple of the comments that we got on this post and I wanted to read to you and explain what was going on. So Kyle Reeves said, "I was told by a higher up LinkedIn team that they normalized job titles in order to include less common ones into a more common group as best they can. For example, a Marketing Ninja would be grouped in with Marketing Specialists." And Kyle That's exactly right. That's what we talked about with this super titles concept of how LinkedIn tries to roll up smaller titles into the larger. It's just kind of a black box. We can't see actually how LinkedIn handles this and so I would love a lot more visibility into that. Also Nuno Pereira mentioned, "Are you saying that if I target an audience of 1,000 VPS of Marketing by job title that LinkedIn will, on average, recognize only 300 of them, even if all of them have VPS of Marketing as their current job title on LinkedIn?" And Nuno, in theory, yes, but obviously if all 1000 of them actually put VP Marketing as their job title, LinkedIn is going to understand all of them. The problem is a whole bunch of them have put something other than that, or something in addition to that, who they might be a VP of Marketing in their full time position. But the way that LinkedIn is interpreting what they've said, their job title is, you might have actually 1,000 People who are all considered VPs of Marketing, but LinkedIn only categorizes, let's say, 55% of them. And actually, because I have this data, I can be a lot more exact here. For VPs of Marketing, LinkedIn understands 46.5% of them. So hopefully, that's helpful. All right, I've got the episode resources for you coming right up. So stick around.
16:14
Thank you for listening to the LinkedIn Ads Show. Hungry for more? AJ Wilcox, take it away.
All right, as promised, here's our great resources. The very first link here is going to be the analysis of the job title versus job function, audience sizes that we did. It's a Google sheet where anyone with the link can view and definitely go check it out. Let us know any questions, thoughts, corrections, whatever you find. You'll also see the link there to the systematic approach to targeting episode that was episode two on the podcast, as well as the deep dive into the different targeting facets on LinkedIn. That was episode 11. If you or anyone that you know is trying to learn LinkedIn ads, point them towards this link. It's the LinkedIn Ads course that I did with LinkedIn, on the LinkedIn Learning platform. It's by far the cheapest and the most effective training course I've found out there. And whatever platform you're listening to this on right now, look down and hit that subscribe button if you've appreciated this. And please do rate and review. If you do leave a review, we'd love to give you a public shout out. Shoot us an email at Podcast@B2Linked.com with any thoughts, questions, suggestions, anything like that around the episode. And with that being said, we'll see you back here next week. cheering you on in your LinkedIn Ads initiatives.
