LinkedIn Ads testing and strategy pivots - Ep 57
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AJ Wilcox
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Show Transcript AJ Wilcox You're running and testing your LinkedIn Ads. But how do you know when your test is complete? When something isn't working? How do you know when it's time to pivot? We're covering deep testing strategy on this week's episode of the LinkedIn Ads Show.
Welcome to the LinkedIn Ads Show. Here's your host, AJ Wilcox.
AJ Wilcox Hey there LinkedIn Ads fanatics. So we've all been told that we need to always be testing with our ads. Well, sometimes it can be hard to know when our tests are conclusive. Or when it's time to move on to a new test, or even what do we need to be testing? Well, if you test too long, you end up missing opportunities for more learnings. And if you test too short, you risk coming to the wrong conclusion, which can really be costly on your future performance. So this week, we're gonna dive deep, we're going to talk about the different types of tests that you can run, and how to tell when they're complete. Make sure to listen to the end, because I'm going to be sharing my methodology for deciding which tests to run next, after you found conclusive results from your previous test. So first off in the news, I got a chance to talk to a friend who's part of a really cool beta for LinkedIn right now. It's called the audience insights beta. And essentially, what it is, is a really granular breakdown of the audience makeup of the attributes from a matched audience. You can think of it as a really helpful analysis of your target audience, as well as a great tool for understanding the ways that LinkedIn targets better. The way that it works is you'll go into your matched audiences section, and you'll select one of those audiences, then this can be any sort of a matched audience, it could be a website retargeting audience, or anyone who's submitted a form, or anyone who's visited your company page, you get the idea. Then you click a button that says, generate insights and it will open up a dashboard about that audience. And what you get here is a whole bunch of different facets and breakdowns of what makes up your audience. It'll show you your existing audience size. And it will tell you how many of those people fit into different categories. There's interests, so this is where you can find out which interests that your target audience are tagged with. And this can help you with your interest targeting, determining whether to use it, or how many or which types of interests to use. As a side note, I hardly ever use interest targeting because it's such a black box. But now with this, I actually feel a lot more comfortable in finding and using interest targeting. There's organic content, so you can see the trending content that is most engaging to this exact audience. You can see the location, and this is the profile location of where members of that audience are located. There's demographics, there's education, there's job experience. And this gets really exciting because it'll show you the seniority breakdown of your target audience, your job functions that fit within them, your years of experience, and even more. And as you probably know, when you're building a campaign over in the right rail, we get a little bit of an audience size breakdown, but this is really that on steroids. It's a supercharged version of audience Insights. And then as you're exploring here, it's really quick to create a campaign based off of the targeting you're exploring, which is pretty cool. When this feature sees full general audience release, we will definitely let you know more about it. But for right now, I wanted to give you a quick heads up on what's likely coming and how excited we are about it.
AJ Wilcox 3:36 Okay, on to the testing topic. Let's hit it. So first off what is pivoting? You may have heard the Silicon Valley term to pivot. A business needs to pivot. When a business doesn't have product market fit, companies can pivot or adjust their strategies to find the right fit. You've probably also heard the axiom of fail fast, and that originates from Silicon Valley as well. And the concept is that by taking too much time doing the wrong thing, or a less effective thing, you risk so much more than if you were to just make a quick painful one time adjustment and get to that product market fit much quicker. The same risks are present in our ad testing. If you're testing two different ad concepts against each other to the same offer, but that offer is bad, what you're doing is you're wasting weeks of good potential performance that you could have from running a better offer. So definitely, we should always be testing something. And to be clear, not every test will be exactly what you...
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