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Transcript:

LinkedIn targeting is the reason we’re willing to pay LinkedIn premium prices. Oh, you know we’re about to get geeky today.

Welcome to the LinkedIn Ads show. Here’s your host, AJ Wilcox.

0:21
Hey there LinkedIn Ads fanatics! Today we’re taking a deep dive into the targeting facets on LinkedIn. And I’m about to brain dump on you. If you were one of the ones who loved episode three because of how geeky we got into the history of LinkedIn Ads. I think you’re gonna like this one just as much. I’m going to cover each available type of targeting that LinkedIn has to offer. Yes, all 24, and we’ll discuss #1) how accurate the targeting is, #2) how it’s useful, and then #3) any gotchas or nuances that you should know about or care about as you’re using it. We’ll also talk about how it’s derived. And we’ll also target the targeting facets in order presented in campaign manager so you can follow right along. Alright, let’s hit it.

1:05
First up in the news, the COVID-19 pandemic is causing a lot of advertisers to pull back. I hear from those who are heavy on Facebook ads that this is something that has caused prices to significantly drop on Facebook. On LinkedIn, we are seeing advertisers pull back so you’re seeing maybe slight decreases in CPMs or CPCs. You may see an increase in traffic as more and more people are working from home. And maybe there’s some unrest about potential layoffs. And so they might be using LinkedIn to maybe line up their next job or check and see other opportunities. So this is a great time to be advertising on LinkedIn, because it’s my belief that B2B will always move a little bit slower than B2C. So I’m guessing that b2b will recover much quicker and probably won’t take as much of a hit. So right now, while costs are a little bit depressed, now is a good thing. To be running ads, and starting those conversations with people who are maybe these are longer sales cycles. So you’re starting the relationship now, and not asking immediately for a demo. For any type of advertising where you are asking directly for a demo, let’s say it’s search ads, or maybe you are using LinkedIn as a bottom of funnel type of platform, then yeah, I think now would be a good time to either pull budget or pull back. But if you’re using LinkedIn as intended to capture audience attention, and start to nurture that relationship with something like, you know, free content, gated assets, that kind of thing. Now’s a really good time to continue to spend while your competitors are all fearful. All right, as we move into targeting here, LinkedIn has the most detailed business targeting of any platform on the planet. We’ve talked about that before. I love the fact that it’s so scalable, it’s access to this audience, pretty much for anyone who’s a white collar professional. Plus, it was purpose built showcasing your professional self. So it’s the first and sometimes only place you go to tell when you change positions. I like to joke that LinkedIn is the second person to know when I make a career change after I tell my wife. It’s got unprecedented scale, since platforms like Facebook come and go with popularity. But LinkedIn is a constant. I like to call it a low level hum. LinkedIn doesn’t always make a lot of noise, but it’s always there and always useful. And because of that low level hum, it always seems useful, and it seems immune to pop culture attention. So while Facebooks will come and go and become the Myspaces, I think LinkedIn is here for the long haul. There’s no other platform that can replace it. The way you will notice the unprecedented scale is it’s really rare when one of our clients has a budget that we can’t actually spend on their very ideal target audience. So that tells you the extent of the scale you get with LinkedIn, with these white collar professionals. Certainly if you’re targeting someone who maybe LinkedIn isn’t a perfect fit for, like, let’s say something like door to door salespeople, maybe you’re trying to recruit them. They’re out knocking on doors all day long and so they’re not in front of a computer. But for the most part, it’s really not hard to spend any sort of budget you have on the perfect audience on LinkedIn.

Now, as for how LinkedIn derives each of these targeting methods, we’ll dive into that. And there are three main types. LinkedIn has a lot of the first two, and is starting to incorporate more of the third. So these types are Explicit Targeting, which means you’re specifically told LinkedIn something about you. Then there’s Implicit or Implied Targeting, meaning that the platform looked at something that you did give it and derived or guessed something about. And then the third is where there might be a behavioral an observational bent to this data. So LinkedIn may know something about you because of actions you take on the platform, not necessarily what you told it in an open field, or anything that it derived from something else. So each of these targeting types, I’ll let you know whether it’s derived explicitly, meaning it’s going to be very accurate. Or maybe it’s implicit, were based off of something you did give the platform, they’re gonna make a guess about you, and it won’t be as accurate, but likely, you’ll get a lot more scale. We’ll also talk about inclusion and exclusion in the targeting. Now, inclusion makes audiences smaller and much more targeted in general. I like to think of exclusions as just cutting out the pieces that you don’t want. Like if you’ve ever been cutting a potato or peeling a potato, and it’s got a few bad spots. exclusion on LinkedIn is a lot like cutting off those bad spots of the potato. And even just this year, we got access to Boolean targeting, which gives us the ability to specify and targeting or, or targeting now, and they will make your audience tighter, you could say something like, I want this job title, and this company size. And that means you will only get the people who have that exact job title, and are also at a company of that size. If you use or targeting, you’re going to make your audiences much broader. And an example here that we’ve actually used would be something like we want this job title, or if you’re a member of this group. And the reason you might want to do that is maybe there aren’t enough job titles, or people who own that job title to spend your budget. But maybe if you have that job title, you’re just as relevant as someone who went and joined a specific group about that topic that might give you the targeting you want. Back in episode two, we talked about the difference between targeting the right company versus the right individual. And for my experience, most of the time, we’re combining these we want the right ideal role in the right type of company. And I like to use the example if you told me your ideal target audience are CFOs, but your product costs $1,200 dollars a month, I would tell you that you are your target audience is certainly CFOs, but not a two person company. So you’d want to combine larger companies that could actually afford what it was you were selling with the right role who would feel that pain point and you’d be able to help them out. The most useful filters for targeting people with roles are job title, job function, which is someone’s department, their level of seniority skills on their profile, and groups that their members have. So those are my star five, that’s my dream team have role filters. Then you have the company filters that will allow you to target things like company size by number of employees, the industry someone is in or their company is in, as well as company name for you account based marketing advertisers out there. Alright, let’s break through each of the different targeting types, starting with geography. Now this is the only required targeting type. LinkedIn from the very beginning has always made you select a geography. So if you don’t care about geography, you’re okay with this worldwide, then you will have to specifically select all seven continents. This is definitely explicit targeting. On someone’s profile, they will list where their geography is and this has recently been updated now with all of Microsoft and Bing’s geolocation data. So it used to be that here in the state of Utah, we had two major metro area. There was Salt Lake, Metro up North and Provo Metro down South. And if you didn’t want to target one of those two, you just have to target the whole state. Well, now with Microsoft and Bing’s break down data, and this is already rolled out, you’ve already got access to this, you can target all the way down to the specific city, I would expect to have maybe difficulties with targeting people by granular areas like cities, at least for the next few years. Because when people originally set up their profile, they got to choose a metro area. Like for instance, I work with people outside of the state of Utah and all over the world. So even though I don’t live right in the city of Salt Lake City, I still live in Salt Lake City metro as it’s more recognizable. I actually work in a city called Lehi, which if you know Utah is the tech hub of the state, and I love it, but if you’re not familiar, you may question if someone in a city called LehiĀ is actually good at what they do that this could be some Podunk town out in the sticks, you’d never know. So as long as people are actually updating their profile geography, then targeting all the way down to the city level will make sense In the future, right now, I think there will be a lag of people who originally set up their profile in a metro and haven’t yet updated to a specific city. So you’ll probably want to target a little bit more broadly, at least until that catches up. Then we get into the matched audiences. Now, there are three different kinds of matched audiences a fourth of you want to get real particular here. And we’ll start with an email list upload. Now, this was something we got access to back in 2017. One of my favorite features on the platform, you can upload a CSV or an Excel sheet of up to 300,000 emails. And these can be either raw emails, or they can match a 256 Sha, an encrypted list of how email addresses might be obfuscated. So if you’re working with an agency, for instance, and you don’t want to give them a list, like let’s say your whole customer list, you can export that as a 256 Sha encrypted list and LinkedIn will still take that and be able to recognize it. This is definitely explicit targeting because if you give LinkedIn an email address that they recognize, they will then target that person. And if they don’t recognize it, they won’t go about trying to target anyone. They’re not making any guesses here. This is very, very useful for inclusion purposes. So for instance, if I wanted to target all of my current customers, I could upload this list of email addresses as a matched audience and run targeting against them to tell them about a deal I’m running or something like that. You might be tempted to run this as a suppression list or excluding it. And be aware that it doesn’t work great as a suppression list, just because there’s oftentimes a pretty low match rate between here’s my email address and LinkedIn saying, Oh, yes, I know someone with that email address. I much prefer using company name or what they they’ll call account match. As a suppression list. It’s going to be a lot more accurate and cover more If your audience. Just like any sort of LinkedIn targeting, you do need at least 300 of the emails on your list to match with LinkedIn. Because you can’t target any audience smaller than 300. Personal emails will match at a higher rate, which is great, because a lot of people are more willing to give you personal email addresses. But LinkedIn also does have a great database of people’s professional emails. One of the great ways that they do this is if you are working with someone and you’ve sent them an email, then they can upload their email list into LinkedIn and say, Hey, show me people I’m not connected with already. And LinkedIn will allow them to send invites to people that they’ve emailed with, even if LinkedIn doesn’t know who owns that. So what happens is you’ve received a connection request from someone over email that says, hey, so and so would like to connect with you. And as soon as you log in to LinkedIn and click accept, LinkedIn goes, Oh, this this personal email address you usually lost. With also matches to this work email address. So whereas on Facebook, you might have a huge personal match rate, but as soon as you upload a business address, it just goes to near zero on LinkedIn, there’s going to be a pretty good match rate both with your personal emails, as well as pretty decent on professional. Now LinkedIn will let you know your match rate. But it’s going to be pretty broad here, it might say something like 30%. Or maybe you have a list you pulled directly from LinkedIn. So there’s theoretically 100% match rate, but they’ll just tell you 90% or higher. Now, this makes a lot of sense with email addresses, because you probably wouldn’t want someone to be able to tell whether that email address actually matched a LinkedIn profile. That seems like there could be some privacy concerns.

13:48
But as we move on to the next matched audiences feature called account lists or account match, this is actually my favorite matched audience. And this one, the match rate doesn’t make quite as much sense, but we’ll get into that. You can upload a list of up to 300,000 company names matched. And again, this is explicit targeting. You tell LinkedIn, this company name we want to target. And that person says I work for that company, and therefore the match works. So this is explicit targeting. And I find this feature extremely useful, both as an inclusion for here’s a list of companies I really care about, and I want to show specific ads to as well as an exclusion as a suppression list like “Hey LinkedIn, here is a list of all of my competitors, or my current customers or my current and past customers, and any ad I show, I want you to exclude these people from seeing my ads because I’m not going to get any value out of a competitor clicking my ads and charging me money”. The gotchas here is that it does require the employee to have claimed working for the company. page. So as long as the employee came into the company after the company page was set up, then this is going to make a lot of sense. It also requires the company to have created a company page. Because if that company page does not exist, and you put in some company name, LinkedIn won’t know who to match it to, because they won’t see any employees attached to it. This all is dependent on your company page itself. Now, like I mentioned, the match rate here is pretty obfuscated, and it’s understandable with personal email addresses, but I get really angry about it when it’s around account names. The reason why is because there’s no privacy involved in a company name. So if I uploaded a list and let’s say I was trying to target IBM, and that didn’t match, LinkedIn is only going to tell me that it was 90% or higher matched. And I might have missed the fact that that IBM didn’t work, but if I would have typed I. B. M. it would have. So I do wish that LinkedIn would actually give us a specific percentage. And even let us know which account names did not match. But so far that hasn’t happened. You can add a web URL for a much better match right here. And I highly recommend that if you can pull a list of your company names, and then in the next column over, you give the URL for that company that would totally solve for that IBM issue I mentioned before, because LinkedIn would go oh, I don’t recognize IBM. Oh, but I do recognize ibm.com. Yeah, that map’s to I. B. M.

16:41
The third type of matched audience targeting here is retargeting. Now this was one I was really excited for. And like we mentioned in Episode Three retargeting is about to get a lot better, but as of right now, it’s it’s pretty weak in how it works. It’s 100% cookie based retargeting, which means someone has to land on your website that you have control of, and you’ve placed the LinkedIn pixel. And then their browser has to accept cookies, which as of right now, half of the browsers don’t even accept cookies. That’s all iOS devices running Safari won’t even accept the cookie. And anything running the Mozilla Firefox browser also won’t take it. And we know within the next two years, Google Chrome has already announced a sunset around third party cookies. And we also know that Microsoft is never last to the conversation about privacy. And so I’m guessing that Internet Explorer or edge will probably sunset cookies before then. So within about two years, LinkedIn’s retargeting won’t even work, but that’s why the enhancements that they’re rolling out with engagement retargeting are so exciting to me. This type of targeting is based on user behavior. It’s once you’ve landed on a page, we’re going to stick that cookie on you and make you eligible to be retargeted in the future. Now this is only mildly useful right now for exactly the reasons I talked about. But some additional things. The cookie pool minimum is 300. Because on LinkedIn, you’re not allowed to advertise to any audience smaller than 300. So you have to have at least 300 people in that retargeting pool. And because only 50% of browsers accept the cookie, it makes it unreliable as a suppression list. So you might say, if you’ve clicked on my ad, but didn’t convert, now I want to exclude you moving forward. And you could set up that rule, but of course, only 50% of the browser’s out there would actually honor it. So you’d still be getting a whole bunch of return traffic there on that campaign. The other benefits that are usually associated with retargeting are that you’ll be able to stay top of mind as you remind people about your product or service. Well, people just don’t spend that much time on LinkedIn. And they’re just not super active in general, it’s like three to four log ons per month is average. And so there’s not a whole lot of benefit in retargeting people on LinkedIn, just so that they have an opportunity to see your ad three or four times a month. Retargeting is also usually very economical, but on LinkedIn, it’s not really the case. We oftentimes see costs lower than $1 per click coming from Facebook and Google’s retargeting. And on LinkedIn, it’s really rare when we see a retargeting click that’s less than about $4. So sure, you’ll probably get some kind of discount, but it’s usually not big enough to really entice me.

19:36
Then the fourth element here of matched audience targeting is look alikes. Now we waited for look alikes for a long time any of us who have experience with Facebook Ads, the look alike targeting is one of the best technologies Facebook has. So people were screaming for it like “hey, LinkedIn, can you come out with look alikes just like we have on Facebook?”. And there just wasn’t a good reason for LinkedIn to have look alike functionality, because the original targeting was so good. If you want a look alike, you can just go and say I want to target everyone with that job title. Or you could say if I like targeting that company, I’m going to target all of the companies in its industry or of its size or both. So when LinkedIn acquiesced, and actually gave us look alike targeting, it just wasn’t all that useful, because their original targeting was so good originally. So because of that, I do call it mildly useful. It is really good to create a look alike from your customer list where you might not have specific titles or specific types of companies, but you can let LinkedIn make those connections. It’s important to understand it’s actually based off of the audience expansion functionality that you find in every campaign selected as default, which I’m not a fan of. But what I do like about look alikes is that you can break it out into its own campaign. I never use audience expansion just because it muddies my current audience. But with a look alike, you pretty much get to use the same logic, the same engine that gets you additional people, but you can run it as a whole separate campaign so you can test. This is very much implicit targeting because it’s derived from people have likely similar roles and also similar types of companies. And it is very much a black box, we can’t see what’s happening. Plus on Facebook, we get some really cool functionality this slider bar from one to 10%. Basically how tight do you want this look like to be? Do you want it to be the most precise type of targeting this is really really close. Or are you okay with most of it in there and Facebook can just use a little bit of artistic license to add to it. LinkedIn there’s only one setting it’s, here’s my list, create a look alike from it, and you’re you are kind of stuck with whatever it comes up with. If you’re doing having any sort of account based marketing approach where you’re targeting by company name, do make sure that you have not selected that audience expansion checkbox because you’re specifically telling LinkedIn, I want to target just these companies. And then LinkedIn is going “Ooh, I know companies that look like that”. And they’ll start to broaden your audience, which you obviously don’t want.

22:21
Then we move on to the company filters. We talked about how the three major company filters were company name, company size, and company industry. So we’ll go through each of those. With company name it’s just like account match, where we could upload a list of up to 300,000 company names with a few small intricacies here. First of all, you are limited to only 200 company names per campaign, which is really, really terrible to actually go and type out 200 company names. It will be one of the worst things that you do with your time. But the coolest part about it is if you will do this, you will have a 100% match rate on your company names. Because as you type IBM, LinkedIn will pop up a message that says is this the company you mean, and you can make sure that you’re hitting that exact company. If you uploaded that same company list into LinkedIn through a matched audience, it may not have 100% match rate, and LinkedIn wouldn’t even tell you which ones you were missing. So if I’m ever targeting fewer than 200 companies per campaign, then I’m going to use this feature just the company name targeting. Now this is explicit. Someone does say I work for this company and LinkedIn goes “Ah, I see that company’s company page I know that exists, I can match these up”. And I do find this very, very useful. We use company name targeting for account based marketing campaigns all the time. Then company size. This is where you can target a company by the number of employees it has. Some people would like the ability to target by revenue target, for instance. But LinkedIn asks people from the company page, hey, how many employees do you have, and that number becomes gospel. And that’s what we are able to target. Because of that it is explicit. The company page owner has to say we are this size of organization for you to be able to target them by their company size. This is very, very useful. We use this all the time. It’s how we make sure that we’re targeting either the enterprise or small to medium sized businesses or anything in between. The gotchas and nuances here are specifically that most of the companies out there do not have a company page profile, or I guess I’ll say it like this. Most LinkedIn members are not linked to a company page where LinkedIn knows their size. So that means if you are using company size targeting, you are probably going to exclude about half of everyone on LinkedIn. Now this number has improved significantly. When I very first got into LinkedIn Ads back in like 2011, it was something like seven times more people did not have a known company size. And now that’s only 50/50. That’s pretty good. We can actually use this to our advantage, though, because a lot of people are probably using company size targeting. But let’s say that you are specifically targeting smaller companies, let’s say companies with fewer than 50 employees. Rather than just targeting the companies who are explicitly less than 50 employees. What you can do is exclude all companies that are larger than 50. And what that does is it gives you the companies of the smaller size that you’re looking for. But it also gives you all of the unknowns. And the majority of the unknowns are probably from companies with fewer than 50 people. It usually takes a marketing person to say, “hey, we should probably own our profiles across the web”. Keep in mind that each person can fit under multiple company sizes because of their multiple positions. So imagine that someone works in an enterprise, a 5,000 and above size company. And maybe they have their own consultancy on the side. Or maybe they’re on the board of some nonprofit. And so you might be targeting companies with 5000 or more employees, and then you get a lead from a tiny nonprofit. That can happen sometimes with company size targeting just because each member can be currently connected to more than one company. Make sure you don’t use company size as an exclusion just because you’re lazy and you don’t want to select more checkboxes because anytime you use company size exclusions, you’re going to be left with those who are undefined, which tend to be small. Now company industry targeting this is where you can target someone by the industry that they are in or their company is in. Now, that’s a really important distinction to make. This is explicit the member on their individual profile gets to choose what industry they’re in. And they are also likely associated to a company page. And the company page admin got to select an industry as well. So I might have as my industry, marketing and advertising, but my company might be in high tech or something like that. Same rules apply here that if someone has multiple roles on their profile concurrently, they can also qualify for more than one industry. Not to mention I’m pretty sure they can be targeted by their company’s industry and or the industry they claim themselves. In addition to those basic company targeting, there are a couple more that are related to companies. So one’s called company followers, and this is where you can reach the followers of your company page. I say your company page, and I mean it. You actually have to have admin access to any company page to be able to use this targeting feature. And I do wish that we could show ads to followers of our competitors, for instance, but we can’t do that you have to own the page to either target your own followers or exclude them, which is more often what we’re doing with it. And that is pretty explicit as targeting goes. Because if you’re either following a company or you’re not. This can be really useful for let’s say, if you’re in the SaaS software industry, it’s really nice to show product update ads to the people who are your users of your product. Because that way, when it’s time for your contract renewals to come up, you can remind them how good your product was. So hopefully they resign again. I tend to use this mostly as an exclusion, because if someone’s already following my company page, they’re already seeing my content and oftentimes ads for free anyway. So I might want to just exclude them from my ads so that we’re not paying for them. Your ads account does have to be associated with your company page to make this work. Then there’s an odd one here called company connections, where you can reach just the first degree connections of any company you select. And companies are only available if they have more than 500 employees. So you’re not reaching the employees of that company, you are reaching the first degree connections of the employees, which I can’t imagine a case where this would be really incredibly useful. This is of course, explicit targeting, because you’re reaching just people who are first level connections and this is very clear data. One good reason I can think of to use this is messing with people. So maybe you want to target a competitors first degree connections and maybe say something bad about the competitor or embarrassed them in some way. And of course, all of these people have a connection to that brand in some way. That could be something you try if that’s really your style. But more often than not, but maybe more helpful on a serious note, you could exclude this segment along with your competitors company name, if there’s something that you really don’t want to get back to a competitor, because you can exclude your competitors from seeing your ads. But maybe one of their connections or one of their good friends sees it and shoots them a screenshot of the ad that they saw their competitor is running, and they might send it to their friend and clue them in. So you can exclude your competitors as well as their first degree connections and really be helpful that that message isn’t going to get back to them.

30:52
All right, then you have your age targeting. Now, this is really important to understand that it is an implicit type of targeting It’s derived from the date that you started your first position that you claim on your profile. This is important to understand because no one ever put in their birthdate into LinkedIn, it’d be pretty easy for them to ask that when they sign up. But no one ever did that. And so LinkedIn is gonna look at it and say, ah, people usually start to graduate from college around the age of, let’s call it 22 or something. And that means when you start your first position, you’re probably 22 around that time, and we can calculate how old you are. This can be pretty inaccurate, especially because you’ll find some people who go “uh, my earlier career experience wasn’t related to marketing or wasn’t really wasn’t related to sales, so I’m just going to leave that stuff off of my profile”, and then all of a sudden, LinkedIn thinks that you’re 12 years old. So I try not to use this facet unless I absolutely need to. And it is pretty broad anyway. Then you’ve got gender which is also implicit. It’s really interesting because of how wrong this can be. It only has two categories, male or female, I think they’ll probably give additional categories in the future just to be sensitive to transgender. But this is derived based off of a probability of someone’s first name being either a masculine or a feminine name. So we have a client whose name is Lenny. And it’s a man his name is is Lenny. But he gets ads all the time, like, “Hey, are you a female executive?” And he’s like, “No, definitely not”. So I would call gender maybe mildly useful, I would imagine it’s probably, I don’t know, 90ish% accurate. So I try not to use it unless I absolutely have to realizing that because it’s just a guess based off of someone’s first name, there will be a little bit of spillover in both directions. Okay, here’s a quick sponsor break and then we’ll dive into the rest of the targeting options.

32:53
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33:02
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33:20
Alright, let’s jump into the rest of the targeting options. So next we have degrees. Now, this is explicitly derived from the profile. When you go to add education, it will ask you what your degree is. And I would say in the Higher Ed segment, this is a really, really useful and important type of targeting. As a gotcha though, there are so many degree names. You can have a Bachelor of Science in marketing, a Bachelor of Arts and marketing and a bajillion of other options. So be aware there. If you are specifically trying to target one type of person, you’ll probably want to type in something like for instance, if you’re going after marketers, you’ll type in marketing or you’ll type in bachelor’s, and then just scroll through that big list trying to find anything that is relevant. Next is field of study. This is also explicitly added from your profile when you add an education. You get to say what you studied. So for me, it was marketing, I studied marketing. And this can be really helpful for Higher Ed types of targeting. And there are so many different fields of study. So be aware, again, like degrees, you’ll probably be trying to target by a lot of different variations. Then you’ve got schools, again, this is an education. This is explicit, someone says I went to this University, and it is optional to add, but most people probably do, I think most are pretty proud of their school and their degree, so they will add it even if optional.

34:46
Then we get into some of my very favorite targeting criteria here. These are the ones that are helpful for targeting the individual. So job function is the department that someone works in. They say they call it job. function in my mind, I just tell myself department. And this is derived from several different things in a profile. LinkedIn told me they are in the process of updating and changing how this is done. But at least when I was informed about it many, many years ago, this was derived from your job title, your industry, and I believe it was skills, but it might have been something else. So they match those three, three things together and try to figure out what departments you fit in. Each member can have multiple from a single position. So let’s say your job title is Chief Financial Officer or CFO, LinkedIn looks at that and goes, Oh, well, you are 100% in the finance job function, but we’re also going to put you at 16% in the business development function, which is what a lot of C Executives fit into. So you can have one person fit multiple departments or job functions. Because this is pulled from some other things in your profile like your title, your industry and skills, that does make it implicit, which means it’s a little bit less accurate. But it is LinkedIn’s broadest targeting. And we find this to be really helpful in combination with other elements, like company name, for instance. So if I ever tried to overlay job title on top of company name, I would likely not hit nearly as many people on my audience size as I wanted to. But because job function is so broad, I love it in conjunction with other types of targeting that make it quite tight. Now, here’s a nuance that you won’t know until you go and try to do it. And then LinkedIn tells you you can’t, you can’t combine job function and job title in almost any way. That means as inclusions or exclusions, and that is because job function is derived from job title. So they look at it and go well, you can’t exclude one from the other because they come from the same pot. Something interesting that we found out when LinkedIn came out with the segment breakdown several months ago, where you can look at audiences and see what LinkedIn categorizes them as we did the job title of CEO, and then went to go look at the job function of a CEO, because we’ve always been curious, like, what is a CEO? What is what department does the does LinkedIn think that it fits into, and CEOs are near 100% business development, which is odd to me, it didn’t make sense, but I’m glad that I at least know. And of course, that opened it up to us learning a lot more about how LinkedIn categorizes these job functions. For another example here, sales manager job title, if you go into segment breakdown, LinkedIn calls them 98% sales, but 6% operations 5% business development, 4% marketing and 2% support, which is odd that they would have such small percentages. I would imagine that they are those percentages in certain industries, which tells us why they’re so low

38:01
Then you have seniority and seniority we use almost all the time. It is a fantastic filter. And it is also implicit from your job title. It’s derived from the perceived level of your job title. This is really easy when you have something like a manager, director, VP kind of title, but obviously more nebulous if you have something like specialist, analyst, consultant, those types of things. We find this one extremely useful. We use it all the time like I sai. There are quite a few gotchas and nuances with the job seniority filter, for instance, one of the options is unpaid. And I just wonder from the job title, how do they know that they’re unpaid? If you go into segment breakdown, LinkedIn says the majority of unpaid jobs in your 30s have at least 12 years of experience. So and that’s 15% of them was the biggest amount in that list. And so I look at it and go “wait, does that mean that they’re categorizing CEOs or really senior people as unpaid”? It didn’t seem like it jive to me. Then they have training again, I wonder how do they know that someone is in training 61% of people in training are in education. And then if you look at the years of experience 9% of training are in the 12 or more years of experience bucket. And then there’s 7% in the 1, 2, 3, 4 years of experience bucket. So I wonder if they’re training, what’s this connection, two years of experience. And then there’s entry level. 22% of entry level are registered with over 12 years of experience. So again, I maybe I’m wondering a little bit about that. Not quite sure how accurate it would be. Then senior, so many people get senior wrong as a seniority. What it means is when I think senior, I think individual contributors. This is someone who manages projects and things, but not people. And the thing everyone gets wrong. They go, “oh yeah, we’re targeting senior managers or senior directors or senior VPS”. That’s not what it means. It doesn’t mean you have a senior in your title, it means that you are an individual contributor. And then I look at that and go wait 36% of senior seniorities have 12 plus years of experience. So again, years of experience seems maybe unreliable at this point.

40:28
There’s a manager seniority, which we end up using a lot. LinkedIn calls this a people manager. And I again, I wonder if you have manager in your title, how does LinkedIn know that you manage people and not just projects and things? Something interesting if you’re looking at manager seniority, 4% of those people are also in Director, 3% are also owners, 2% are VPS, so again, that breakdown maybe leaves me with some more questions than I had before. Director, VP, CXO all of those make pretty good sense to me. And when I looked at owner as a seniority, it’s like CEO because it’s near 100% business development as a job function. I thought that was interesting. Partner, I oftentimes will equate owner and partner together. Partners are qualified as 57% business development and 53% entrepreneurship. So I guess that makes sense. It’s just interesting to see how LinkedIn slices it. Okay, then we have job titles. Now, because your job title is a free form field, you can write whatever you want in there. And so LinkedIn is attempting to look at your title and understanding and equate it to other people’s titles to try to build this model around it and understand which job titles make sense. When you look at it, though, LinkedIn only understands about 30% of the job titles out there. So that means that when you’re using this targeting facet 70% of your audience won’t be reachable with this. It is explicit and it’s going to be very accurate because someone really had to closely match a job title for LinkedIn to understand it. We find this to be really useful. And we use it around a lot around roles. In fact, we probably use this with every single client, we are usually running a job title campaign for a role. Through the API, we queried and found that there are 30,223, so just over 30,000 unique titles on LinkedIn. And there are other known titles that roll up under those, which means your LinkedIn has 30,000 that you can type in and it will match that there are a whole bunch of others that LinkedIn says roll up to that that we can’t see. What’s been interesting to me for a long time is you know, here in marketing I know a lot of people who have PPC or demand Gen in their job title. And I’ve been waiting for like nine years now for when I type in PPC or demand Gen into a job title that LinkedIn will match with something. So LinkedIn tells me that they would roll up under things like digital marketing. But because I can’t see it, I just don’t know if maybe their index is really old, they’re not looking at more current titles, maybe it’s not updated very often. Or maybe LinkedIn understands all of these titles fantastically and I just don’t know. Because most marketers go to LinkedIn because of the job title targeting, it’s the first thing they they go to, it’s the first thing they try out. This does tend to be some of the most competitive inventory out there. And because LinkedIn only understands about 30% of job titles, that means that there’s diminished audience inventory, but demand for that inventory is higher, because this is job title targeting that people really like to use. So because of that job title targeting is going to be some of the most expensive targeting that you do. And you just expect it’s going to be very accurate. It’s going to give you more or less smaller audience sizes, and it’s going to cost more, but probably give you very good lead quality. If you’re targeting standard job titles like sales manager, HR manager, you’ll probably capture the majority of them. Those are very easy titles for LinkedIn to understand. But then that also means that those are very easily reachable for less money with something like job function, and seniority. And because members can have multiple positions listed concurrently on their profile, let’s say something like you work for a fortune 500 in the daytime, but you’re also on the board of a nonprofit or you do consulting on the side so you have both titles currently running. That also means that you can qualify as multiple job titles. Then we have skills, another one we use all the time. These are explicit because each member can claim up to 50 skills on their profile when they sign up. And these are always things you can go and edit later. They are more specific than job title. So for instance, I might have the job title of digital marketing manager but I think might be really highly specialized in LinkedIn Ads, or Google Ads or Facebook Ads. So those types of ads, the channels themselves would be under skills quite easily. But I couldn’t reach that person just from their job title, unless I wanted to go broader, like digital marketing manager that really could be managing anything, anything paid organic, social search, whatever. It does aid and giving us broad audiences. And so it is very, very useful. Also, for things like overlaying on top of lists of companies for ABM lists, this can be great for that. As for the nuances here, each member can have up to 50. But it’s also not the strongest signal. So for instance, I took a SQL class one time SQL, a database class, and because of that, I put SQL as a skill on my profile, but certainly you wouldn’t want to try to sell me a database management software. It’s not what I do primarily. It’s just one thing. I was proud of I liked. If you wanted to try to target people like me who might have a job title of ad specialist or PPC something, because there’s no PPC job title skills can be a great way to reach someone like me who maybe LinkedIn just didn’t understand their job title. One thing I would absolutely love, people claim skills and you can endorse each other, you’ve probably done this a lot, you’ve probably received a lot of endorsements. I wish that we could either bid up bid higher on people who had more endorsements on certain skills, the ones that were bidding on, and maybe even ignore, if you only have three or fewer endorsements around a skill, maybe I don’t want to target you. And that would be really cool. I’ve given this feedback to LinkedIn, please give it to your reps as well. I think that’d be awesome. Skills, back in the day used to be free form and I think this was probably sometime around 2014 when this changed, you could write any skill you want. So we used to play jokes with this, we would nominate other people in assigned skills like snowboarding to to friends trying to get them things like contracts or influence or attention in sports. So now they have enough skills out there that you’re kind of forced, there are a certain number of skills you can put in. I don’t know how often these are updated. I don’t know how often they add new skills. But certainly this is something that you’re kind of closed into a box now.

47:21
Years of experience is another pretty interesting one. Again, just like age, this is implicitly drawn from the date you started your first claim position. The definition would be the number of years you’ve been in the professional world realize that it’s only mildly useful because it is very implicit and you just never know how accurate it’s going to be. I think rather than age or years of experience that seem very prone to error, I would much rather use seniority that doesn’t seem nearly as prone to error. Then groups I absolutely love groups targeting. Now don’t mistake this. This is targeting people who are members of certain groups, it doesn’t mean that your ads are going to be shown when they’re logged into the group, I get that question quite a bit. This is very explicit. In fact, you have to go way out of your way on LinkedIn right now to join a group. And I don’t think LinkedIn is very proud of their group’s product right now because you really, really have to go out of your way. If you’re searching for a group, you’ve got to get like four clicks deep before you’re ever even seeing an option for groups. I think this is very, very useful. Because if you’re passionate enough about a topic to go and join a group all about it, you’re probably really relevant to what I’m trying to sell you. Back when LinkedIn was really proud of their group’s product, and they were really highly used. A lot of people joined groups and then kind of forgot about them, and they’re still part of it, which is great. It means when I use group targeting, I’m going to have larger audience sizes, but realize that may not be quite as up to date. And because fewer people are members of groups, these will usually give you a smaller audience sizes.

48:59
Then you have member interests. There are currently 11 broad interests, and then they break down into a bunch of more micro and niche interests. It’s interesting that these are part of the third category of how targeting is determined. These are part of the behavioral or observed category. The way they do it is looking at what you interact with in the feed. So subjects that you’re posting on subjects that you are completing social actions on, like liking, commenting, and resharing. And if they can get the data from you, if you do any sort of searches on Bing, they will pull from your Bing search history to try to figure out what you’re interested in. I think this is not very useful. I don’t use interests a whole lot it just because of how broad they are and how prone to error. My big question is, what does someone have to do to be labeled as interested in a certain topic? Is it like you hit the like button once on a post about that topic? Or do you have to comment three times? Or is it a single search on Bing? Is it 15 searches on Bing with a keyword?, we just don’t know this. So I would suggest using it for things like paring down an audience when there just isn’t a reason for you to be targeting a million people. But your targeting isn’t tight enough to get it down to like a very small group, we might overlay interests just to give yourself a better shot. It’s also really interesting to look at your audience’s interests just to see how much faith that you are willing to put in. So what you could do is put in the job title of someone that you’re trying to target, then you look in the right rail under the breakdown, the segment breakdown, and look under interests just to see does it jive? Are you targeting developers and there’s a ton of stuff about like Bitcoin? Maybe that’s maybe that makes sense. If you’re targeting developers, and there’s a ton about travel or Instagram influencers or something like that, I wouldn’t have as much faith in it.

50:56
Then you’ve got some new stuff called member traits. Now Member traits used to be something called custom segments that was beta targeting that you only got access to, if you had a LinkedIn Rep. And what’s really cool is they’re starting to slowly roll these out. And at one point, there was something like 30, or 40 different custom segments that your LinkedIn rep had access to. And now I think they’ve released maybe four or five of them. And I hope they keep going. I think these are so so cool. They are also behavioral and observed types of facets. But what’s so cool about them is LinkedIn knows a lot about you because of your behavior on the platform. And so I feel like these are a lot more trustworthy. There’s still tons that haven’t been released yet. So definitely ask your rep if they have any ideas for custom segments that might be good for the audience that you go after. There’s one called frequent contributor, obviously, I don’t know what their baseline is for how many times you have to post or comment on something to be a frequent contributor, but it’s there. This There’s one called frequent traveler. And I think they know because if you’re on the mobile app and you log into LinkedIn, from IP addresses that go across the country across the globe, they know that you’re a business traveler. There’s one called job seeker that this one makes a lot of sense. If someone has viewed at least three job postings, or applied to any one of them. LinkedIn goes, “ah, they’re looking for a job”, so you can target them pretty easily. There’s one called open to education. There’s one called device preference. And device preference is really interesting to me. I don’t know where we’re all the way there yet. But it’ll break down into do they prefer desktop or mobile for their LinkedIn experience. And under mobile, you can actually break down to iOS and Android. It is called preference and it doesn’t mean the device they’re on. I believe this just means the the device that they tend to use the most often, so not quite as accurate as I have liked, but certainly that gets us closer. I certainly expect more coming out here because there’s a lot of custom segments we’ve used in the past that aren’t in the list yet. As for how useful these are, it really is a yard sale or a garage sale, whatever you want to call it, where you just have to look at the list and maybe something applies. Maybe something doesn’t. It’s really unorganized or disorganized. But there’s lots of good options, maybe something is a good fit for you. So check that those out. Then you have something called audience templates. Now, audience templates are different from our member traits, because they don’t involve anything that’s behavioral. These are just templates that LinkedIn has built for you that make it easier to target certain types of people. So for instance, there’s one that’s expertise in Bitcoin. And if you actually apply this, you see that all LinkedIn did is they just automatically applied all of the Bitcoin and blockchain groups targeting. Then there’s financial advisors and then all they did was added all of the job titles that financial advisors seem to have, and added some finance industries on to it, you can choose IT decision makers, but this is just job function of IT with a seniority of like manager and above. There’s nurses, there’s medical doctors, these are ones that mostly rely on job title. There’s also degrees which you can exclude, which is really helpful for Higher Ed. This one, again, is kind of a yard sale, you don’t know if there’s going to be something that fits your audience or not until you look and there’s 26 out there right now. So check those out when you get a chance.

54:37
So my recommendations for you as you’re designing your targeting, use explicit as much as you possibly can. This is going to give you the highest lead quality, it’s going to be the most precise, and this is so much of the reason why we like LinkedIn is this precision in targeting. So when you need quality, go explicit on your targeting options, and then use the implicit ones, when you just need volume, and you’re okay with a little bit of error. Most of the time, you’re going to need a little bit of a mix. And I really like testing these targeting methods against each other. For instance, if I have an audience like sales manager, I’m probably going to test job title of sales manager, and job function of sales with manager seniority against each other. And I want these in two separate campaigns. And I want to see which one gives me more volume, lower cost, better efficiency down the funnel. Because I understand the need for quality versus volume. And it’s kind of a sliding scale in most cases, I would use job function with seniority on an ABM list on an account list anytime. But if I’m just using LinkedIn’s native targeting to reach every one of this role in North America, I’d be much more likely to use job titles or even groups that really narrow it down. Alright, so I’ve got the episode resources for you coming right up. So stick around

56:04
Thank you for listening to the LinkedIn Ads show. Hungry for more? AJ Wilcox, take it away.

56:15
All right, here are the resources for this week. Anyone looking to get into LinkedIn Ads check out course that I did with LinkedIn Learning. The link is right there in the show notes. I’ve said this on previous episodes, but it covers about the first hour and a half of the trainings that I give people one on one and charge $500 an hour for and I think it’s only $25 bucks so it’s a great value. Definitely check that out. That will get you up to speed in LinkedIn Ads pretty quick. It’s also free if you have LinkedIn premium.

56:45
On whatever podcast player you are on right now. Please look down and hit that subscribe button and please consider rating and reviewing. I would love any sort of attention you could give this podcast and certainly the offers always on the table. Reach out to us at [email protected] with any feedback, anything in the future you’d like us to feature talk about, discuss, or dive into. And we will see you back here next week. Cheering you on in your LinkedIn Ads initiatives.