Here were the resources we covered in the episode:
Contact us at Podcast@B2Linked.com with ideas for what you’d like AJ to cover.
I win auctions every day. No, I’m not an eBay addict. I’m a LinkedIn advertiser. We’re talking about how to win the ad auction on this week’s episode of the LinkedIn Ads Show.
Welcome to the LinkedIn Ads Show. Here’s your host, AJ Wilcox.
Hey there, LinkedIn Ads fanatics! LinkedIn’s ad auction is confusing to advertisers because it’s so opaque. And you don’t quite know what’s going on in the background. If you’re looking to improve the performance of your ads, though, you’ll definitely want to understand what’s going on behind that curtain. So on today’s episode, we’re going to do a deep dive into the ad auction. First of all, some great stuff in the news. I found a resource that LinkedIn released called the professional identity resources for LinkedIn advertisers, I’ve gone ahead and link that down below in the show notes so you can check it out. But basically, it’s a download of how LinkedIn is looking at, and thinking about privacy concerns. And it’s really helpful to understand the direction that LinkedIn is moving with things like conversion tracking, and some of the things we’ve seen recently like with reach being taken away. So if that’s interesting to you definitely go check that article out, there’s quite a few things there. I was also able to attend the meeting for LinkedIn API partners and we got a bit of a roadmap update, which was really exciting. Usually, LinkedIn likes to keep their advances that are on the platform up to date with what’s happening on the API as well. So if you happen to use LinkedIn API in any way, like if you’re using a partner of LinkedIn, that helps you at all with what you’re doing inside of campaign manager, then you might notice this kind of functionality coming out. What they talked about, that I got especially excited about were dynamic UTM parameters. And it looks like these are going to be available in LinkedIn API first, and then we’ll eventually get them inside of the dashboard. So for those of you who are already advertising on Facebook, and you love how you can create the same ad once, but in every campaign, or every ad set that you run it in, you can have different UTM parameters running to it, we’re eventually going to have that on LinkedIn as well. I’m a huge fan of this. I’ve been asking for it for years, they also talked about how offline conversions are coming. And I’ve got this inside of my campaign manager dashboard so it’s available on the UI to me now, I don’t know if it’s available to everyone yet. But we know it’s probably coming to the API soon. So you might be able to use a different partner program to help you with something like these tying offline conversions back to your adspend.
So let’s talk about offline conversions. It’s a little bit limited in the way that LinkedIn is doing it. But you’ll understand why. Imagine that you’re advertising and then one of your ads turns out later to generate a sale. What you can then do is send that list of email addresses of those people who’ve become your customer back to LinkedIn. And then LinkedIn will take that and match it up to that same user if they’re able to find that same email address attached to a user and figure out which campaign which ad they initially clicked on. And then they’ll be able to do that attribution. The obvious weakness here, though, is that LinkedIn knows personal email addresses, because that’s how we log in and sign up for LinkedIn. And if you close a customer off of LinkedIn Ads, they’re probably going to end up giving you their professional email. So let’s say if LinkedIn only understands 50% of email addresses, that’s still cool to have these offline conversions being tied up in the platform. So I’m excited about the functionality, but just realizing it’s not going to be fully complete. There was also some new development around DMP segments coming out with the API. So that could end up being interesting. If there are those of you who are using DMPs.
Going a different direction here. One of LinkedIn engineers reached out to me with a really interesting ask. She said, she’s working on the accessibility features for campaign manager, and that she’s searching for some LinkedIn users who might actually utilize those accessibility features. So maybe it’s someone who is vision impaired. And they’re using things like a screen reader, or utilizing the alt text of images, when either creating or consuming different ads. She would love to have a brief chat with them over zoom or over the phone and share some takeaways with their engineers as they’re trying to make their accessibility features better. So I’m calling on all of you. Do you know anyone who builds ads who uses any of those accessibility features? Maybe because their vision impaired or for some other reason? If so, please reach out to us at Podcast@B2Linked.com and I’d love to introduce you to Carol.
We reported a few weeks ago that LinkedIn is now only reporting on some averages for reach and frequency. And we’re no longer getting those accurate counts. It was done so suddenly that I think there was a lot of advertiser blowback. And so LinkedIn appears to have reverted this change, but the bad news is, it’s likely still going to be averaged again in the future. But at least for now we have the raw numbers. So go ahead and use them for whatever they’re worth. But know that we’re probably going to lose them again soon here in the future.
I have a really cool announcement. I’m actually getting married this week. And so I’m very excited. It’s gonna be fun. We’re gonna go on a cruise for honeymoon. The bad news to you is that I may end up skipping a couple of weeks of episodes, but I promise I’ll be back as soon as I can. I wanted to highlight a review that came in from Maggie Mulholland one of our friends, actually, who works at LinkedIn. She said, “Great resource! Such a time worthy listen for anyone in the industry. AJ brings an honest and well rounded take on all things LinkedIn.” Maggie, thanks so much for sharing that. I do try really hard to have it be an honest and well rounded take. I do hope we’re not ruffling any feathers at LinkedIn when we talk about some of the products the way that we do. But I also hope that the praise that we keep on the platform also comes across as intended as well. So thanks, Maggie, great to have you as a listener.
Alright, so now to the topic at hand about the LinkedIn ads auction, let’s hit it. First, we have to ask ourselves, what is an auction. Put simply, LinkedIn has a limited number of ad impressions that it can show to any given user. And there are obviously quite a few companies who would love to show an ad to any of these users. So LinkedIn, just like all the other major ad platforms, especially like Google and Facebook, it holds an internal auction to decide which advertisers ad to show to any individual during the day. This was a concept that I believe was pioneered by Google early on with Google AdWords, that’s now Google Ads. And it’s a really genius way of maximizing the profit of any individual user on the platform. So let’s talk about how it works. Let’s say you and I both want to reach the same audience member on LinkedIn. And let’s say I’m willing to pay $8 for a click, but you’re willing to pay $10 per click. We would naturally assume that LinkedIn would look at it and say, Oh, that person is willing to pay $10 A click that’s $2. More for a click than Aj is. Let’s show their ad. So that situation seems pretty easy at first blush. Well, what about if you and I are both willing to pay $10 for a click? How does LinkedIn then decide which of our ads they’re going to show? Google’s answer to this was called the quality score. And the essence of it was, if we’re only paying for when someone clicks, then LinkedIn can figure out which one of us is more likely to make the network money when they show our ads. So for example, let’s say that my ads have a .5% click through rate, meaning that every 200 times they show my sponsored content ad, I’m going to get a click, and LinkedIn is going to make $10. But in this example, you’re also bidding $10. But historically, your ads get a 1% click through rate. So your ads get clicked on twice as often as mine. LinkedIn looks at that and says, whoa, both of these advertisers are willing to pay $10. But they make $10 for every 100 people they show your ad to, but they only make $10 for every 200 people they show my ad to. So now you can see how it’s in Lincoln’s best interest to show the ads of the advertiser who tends to get the best engagement. So the metric that judges how effective you are at getting people to click on your ads, and how effective I am at getting people to click on mine is called our relevancy score. Really similar concept on Google, it’s called quality score, really similar concept on Facebook ads, it’s called relevance score. And it’s really cool. But the challenge to it is we as advertisers, we don’t know what our relevancy score is. Google used to show us quality scores all the way down to the ad level. But over time, they took that visibility away, which makes a lot of sense, because it’s in the platform’s best interest to hide your relevancy score or your quality score from you. The reason why is just so someone doesn’t game it. So let’s say your relevancy score is updated every single day, and LinkedIn shows it to you. That means you can effectively do one test per day on changing an ad or launching a new campaign. And maybe over time, you can start to understand how your relevancy score is affected by the changes that you make, effectively gaming the system. Many of you know my background, I started out in Google ads. And I know that the quality score algorithm was something that was heavily debated by advertisers. We always wanted to try to figure out more about what goes into it and how it’s taken into account. This dates me a little bit, but I remember back when Google announced that they had 21 different factors that affected their quality score. So when I started getting really heavy into LinkedIn Ads, I was pleasantly surprised how simple the relevancy is. Your calculation really was. At the time your relevancy score was really just a combination of your historical click through rates and your current click through rates. So if your campaign has had really good click through rates over a long period of time, and you launch a new ad into that campaign, you may start out with a really good assumed relevancy score, which is so helpful. LinkedIn’s product team hasn’t given me any sort of insight into LinkedIn relevancy score, currently. But my guess is, it’s now gotten a lot more complex. But we’ll of course talk about that a little bit later. So your relevancy score is effectively a normalized range from zero to 10. Zero meaning that your ads are providing no value, and a 10 mins that people are clicking on it like crazy, and really loving what you’re putting out as an advertiser. Now I say a normalized range, because if you are a seven today, but all of a sudden, a competitor enters the auction against you, and they have a much higher relevancy score, let’s say they have a nine, your relevancy score is a calculation of your performance compared to those who are in the auction with you. And so yours might sway. Yours might bumped down to a six, because there’s just so good, and it’s all averaged. Okay, so you have this relevancy score that somewhere between zero and 10, and you start bidding in the auction, you don’t know what those who are bidding against you what they’re bidding. And so it really is a blind auction that way. So that example that I used before, where you’re willing to pay $10 for a click, and I’m only willing to pay eight. And of course, the auction is going to give it to you. Well, that’s not the case. Thank goodness, it’s not so simple. So the way it works is that two parties enter the auction. And in reality, there’s a lot more than just two parties. But for simplicity’s sake, let’s say it’s just you and I who are bidding for an audience member. Let’s say I’m willing to pay $12 for a click, but you’re only willing to pay $6.50 per click. So you’re bidding basically half of what I’m bidding. So at first blush, you’re now thinking, ooh, it sure seems like LinkedIn is going to want to show AJs ad over mine. But now when I tell you that behind the scenes, this campaign only has a relevancy score of four, but yours has a relevancy score of eight, what LinkedIn is doing behind the scenes, they are multiplying my bid, times my relevancy score, and your bid times your relevancy score, to get this combined score. So in this case, my combined score would be a 48. It’s my bid of $12 times my relevancy score of four, and you’re bidding $6.50. But you already have a relevancy score of eight, which if you multiply that together, you get a 52. So now what LinkedIn is doing is saying, Ooh, whoever has the highest combined score is who actually wins the auction for their ad to show in this exact impression that just arose. Okay, so your combined score is higher than mine, which means you’re going to win the impression. But now LinkedIn has to decide how much are you going to pay for that click, because we were obviously bidding very different amounts. I was willing to pay $12 for a click, and you were only willing to pay $6.50. So the way that it does this is it takes the second place bidders That’s mine, my combined score, which in this case is a 48. And then they divide that by your relevancy score, which is an eight. This simple mathematical operation tells the system what the second place bidder would have had to bid in order to become the first place. And with this simple mathematical operation, it lets us see exactly what you would have had to bid in order to beat me in the auction, which would have been exactly $6. And because LinkedIn is a second price auction, the same auction model that Google pioneered, we add one cent to it. So basically, even though you’re bidding $6.50, you only have to pay $6.01 for that click, because that’s all it took for you to outbid me. If this is a little bit complex to hear about math over a podcast, I totally get it. Down in the show notes, you can click on a video that LinkedIn created that actually explains their auction system, and they show it with a really cool animation, I think you’ll like it. So now you understand how the auction system works behind the scenes. But that’s not especially helpful because all of this is visible to LinkedIn, those who are hosting the auction, but it’s totally invisible to you. All you see is you bid a certain amount, and then get a certain amount of impressions that turned into a certain number of clicks. So you can change your bids frequently and try to understand how close am I to be getting more advertisers in the auction and being able to win a lot more impressions, or how low can I bid without losing the vast majority of my impressions that I get. But LinkedIn is help article will tell us exactly how they explain relevancy score. It says, ads are assigned a relevancy score that measures how likely a member is to take an action on the app. Relevancy scores include factors like expected click through rate, comments, likes, and shares, your relevancy score can change over time, as members interact with your content. While you can’t see your ads relevancy score, you can use the campaign quality score as a proxy. So this gives us a really important clue. When I go and run a campaign export from within campaign manager, I noticed one of the columns says campaign quality score. And that’s a number from zero to 10, which looks a lot like relevancy score. So if we read into what LinkedIn is saying, we can look at campaign quality score, and it acts as a proxy to what our relevancy score is. But we won’t actually know what our relevancy score is. So relevancy score is something that applies to ads and to campaigns, but your campaign quality score is just that same normalized range from zero to 10 that describes the campaign. So they’re essentially not giving you any information about individual ads, but you do get a little bit about the campaign itself. Alright, here’s a quick sponsor break, and then we’ll dive back into the meat of it.
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Alright, let’s jump back into relevancy scores here. So when I used to look at the campaign quality score column, in my campaigns report, I honestly thought that oh, some engineer at LinkedIn who used to work at Google, accidentally mislabeled it and wrote quality score when they should have written relevancy score. But I put a post out in June, asking for help and thoughts from the LinkedIn masters out there. And one of my connections, Decker Frasier., he turned me on to this. He pointed me towards that help article, where it talks about how your quality score is a proxy for your relevancy score, but they’re not going to show you what the actual relevancy score is. So Decker, thanks so much for turning me on to that. That was new info for me. So then I got to dive into the help article all about campaign quality scores. And I’ve linked to that article below if you wanted to go and do your own research. The article starts off “A campaign quality score is an estimate of how likely a member is to act on a sponsored content ad in your campaign. scores help indicate how relevant your campaigns are compared to your peers campaigns targeting that same audience.” So immediately, we’re understanding that this is totally based on the competition around you. So you could have a terrible click through rate and still have a great quality score if all of your competitors are also getting terrible click through rates. Or conversely, you can have an amazing click through rate, but if so many of your competitors have even better than you’re just stuck with a normal or an average quality score. The article then goes on to explain how campaign quality scores are based on the predicted click through rate of the ads in your campaign, as well as the predicted click through rate of your peers ads targeting the same audience. So that raises the question, how does LinkedIn predict what your click through rate is going to be? Here’s another little nugget to point out in this article, campaign quality scores and predicted click through rate are only helpful for evaluating campaigns using CPC bidding. So what that means is, the only ones of us who are actually part of the auction are those who are bidding by the click. So if you are bidding by the impression, or if you’re using LinkedIn’s maximum delivery or auto bidding options, you’re effectively bypassing the auction entirely. You don’t have to worry about your campaign quality scores or your relevancy scores. And that’s because if you tell LinkedIn that you’re willing to pay a certain amount, regardless of who clicks for every 1000 times they show your ad, LinkedIn can very easily compare you to another advertiser who’s saying the same thing. So if you’re willing to pay $120 for them to show your ad to 1000 users, and your competitor is only willing to pay $100 to reach that same 1000 users, LinkedIn doesn’t have to do much calculating at all. It just says, oh, that advertiser is willing to pay me $20 more for the same traffic, I’m going to give them more impressions. I have had several members of my team come to me and say, “Hey, has campaign quality score gone away? Because when I run a report, I don’t see it in there.” Well, LinkedIn is help article here says, “If a campaign quality score isn’t available, it’s probably because your campaign isn’t active, or it’s not using the sponsored content ad format. Or maybe it’s too early. And your campaigns ads haven’t competed in the minimum number of options for that score to be calculated.” So if that column is blank for your campaign, one of those four reasons is going to be why.
So that then begs the question, how do we improve our quality scores or our relevancy scores? Well, that’s pretty simple. It’s improving our click through rate. But of course, that’s much easier said than done, check out Episode 59, where we talk all about how to increase click through rates, and all the different controls we have on them. And although our bid doesn’t directly contribute to your relevancy score, your bid is used in the calculation of your combined score, which then decides if you win auctions or not. Let’s say you’re bidding pretty low at $7 per click, you may see that you get, let’s say, 200 impressions per day. If after increasing your bid to $12 per click, you might see your impressions jump up to 1000 per day. And what that means is you were only winning like 200 impressions per day with your lower bid, but now that you’re bidding higher, you’re qualifying and winning a lot more of these auctions. But of course, as you’re bidding higher, it means those auctions that you do win and when a user actually clicks, you will pay quite a bit more for that, click, go back and check out Episode Six, that was all about bidding, if you want to become an absolute ninja Jedi Master or whatever, on the whole topic of bidding. If we look at the other platforms, especially like Google and Facebook, who are much much more advanced in tech, it might afford us a bit of a glimpse into what relevancy score will be in the future, or maybe what it’s already developing to be. Google, for instance, has so many advertisers and so much competition, that just deciding someone’s quality score based off of the click through rate of their ads, it doesn’t tell the whole picture. So think about the other kinds of factors, which might tell the platform, how successful you are as an advertiser. Some of those things might be when you are sending traffic to a landing page. If that landing page loads really slowly, you could tell that people who are clicking on those ads probably are not going to have the best experience and they may end up bouncing before the page even loads. So it’s much better for them to reward the advertiser with a higher quality score, whose pages load near immediately. With Google, it’s really simple because they’re searching by keywords and so Google can take into account how relevant the keyword is that someone clicked from, to the keywords that are actually found on the page. Who knows if LinkedIn is using something like this, but they certainly could. So my recommendation to you is whether LinkedIn or using any other factors other than your historical and current click through rates or not, I would go and look at things like content of my landing page and how fast it loads. Because you can guess that if Google and Facebook had been doing something for lots of years, LinkedIn is sure to follow. Something else we have to talk about is how LinkedIn reps talk about pausing your campaigns or pausing your ads. There can be lots of great reasons to pause a campaign or pause ads, but if you’re working tightly with a LinkedIn rep, you’ve probably heard them say, “Don’t pause your ads or your campaigns, because it will affect your relevancy score, or it will reset your relevancy score.” And we’ve done a lot of testing because this sort of sounded like an empty threat to us. And largely, I think it is, we’ve had several reps tell us that if you pause your campaigns for more than two weeks, then when you go to turn them back on, your relevancy score is totally reset. And I definitely don’t think that his reps are lying. But I understand if they are bonused, based off of how much their advertisers are spending, and we pause things like over the weekend or at nights, then the campaign’s will likely not end up spending as much as they’re budgeted for. And so of course, the reps would want to caution us away from that. So in all of our testing, we found that pausing campaigns does not seem to affect us in the auction at all. That means if we pause a campaign with its ads for a full two weeks, and then turn it back on, if the relevancy score were reset, we should see action that was very much like the campaign was newly launched, which means it would probably enter a learning phase for the first one to one and a half days, where we either got fewer impressions or more impressions, as the system is just testing to see what relevancy score we actually deserve. So we haven’t seen this action take place. But I’d love it if any of you have done this same test, if you’re seeing anything like this, that would show to you that your relevancy score is being reset, then please do reach out to me and let me know. I’d be really curious to hear about that test. So let’s say that LinkedIn is actually resetting our relevancy scores after pausing. If we’re not seeing a big effect come from that. One reason could be that if LinkedIn shows your ads, and it’s earned a certain relevancy score and place in the auction, and then you pause, and then start again, that audience is just as likely to interact with your ads the same way that they did before. And in fact, maybe even slightly higher, because they haven’t seen the ads in two weeks. So those who have already interacted and seeing them, they have probably forgotten about seeing them, and it looks new to them. So that’s a possible reason why even if your relevancy score does get scrubbed, after two weeks of pausing, why performance can still look good. But again, that’s just a hypothesis. I’d love to hear from you guys, if you’ve seen any sort of effect like this. All right, I’ve got the episode resources for you coming right up. So stick around.
Thank you for listening to the LinkedIn Ads Show. Hungry for more? AJ Wilcox, take it away.
All right, I mentioned Episode 59 of the show. For those of you who are curious about how to improve click through rates, definitely check that one out. It is the key to getting lower costs on LinkedIn. There’s also the LinkedIn Help Center article about LinkedIn’s Ad auction, and how it’s calculated. That is sincerely interesting and I would recommend it as a read. There’s also the article that we sampled out of here, the campaign quality scores for sponsored content help article. There are some great insights there. It’s really awesome when LinkedIn is so transparent about how their system works. It sure helps us advance advertisers not put on our tinfoil hats and assume the worst. There’s also LinkedIn’s privacy centric page that talks all about their new initiatives around privacy. Definitely worth checking out, especially after Episode 70 all about the cookie pocalypse, you’ll probably understand that one quite a bit better. I mentioned Episode Six all about bidding. That that one’s definitely worth going back to have a listen, if you’ve missed that one. Or it’s always worth a read, listen, because it’s honestly one of the most important things from your whole. So go back and have a listen of that. In case you missed it. Or even if you’ve already heard it, it’s super important. It is the basics of advanced LinkedIn Ad strategy. So make sure you know it like the back of your hand. If you or anyone else, you know, is looking to learn more about LinkedIn Ads, check out the link in the show notes for the course that I did on LinkedIn Learning all about the basics of LinkedIn Ads. It’s incredibly inexpensive, and really high quality. The LinkedIn Learning folks really know what they’re doing. If this is your first time listening, welcome, we’re excited to have you here. Make sure you hit that subscribe button. Of course, that’s only if you liked what you heard. If this is not your first time listening, please pay us the fee of leaving a review on the podcast. It really, really helps. I’m not just saying that. And of course I’d love to shout you out for leaving a review. For any questions, feedback or suggestions on the show, reach out to us at Podcast@B2Linked.com. And with that being said, we’ll see you back here next week. Cheering you on in your LinkedIn Ads initiatives!