Social Media & Content Marketing Blog | Drop & Hook

Paid That Performs: Tips For LinkedIn Ads Testing

Written by Taylor Gant | Oct 25, 2022 1:13:00 PM

With the chance to reach over 850 million professionals on the world's largest professional network, LinkedIn advertising is a great way for transportation and logistics marketers to reach target audiences. Whether you’re selling freight tech or promoting a new trucking service, the fact that 50% of buyers turn to LinkedIn as a resource for making B2B purchasing decisions is an enticing reason to curate a LinkedIn ads strategy. But with so many choices available via LinkedIn’s ad platform, measuring success can be overwhelming. That’s why we’re sharing our best tips for LinkedIn Ads testing that will ensure you’re achieving successful results.

Whether you’re trying to discover the best target audience for your ads, which creative resonates best, or what type of CTA gathers the most clicks, there are some LinkedIn testing best practices you should keep in mind.

Here’s what you need to know when testing your LinkedIn ads:

Run Tests for at Least Two Weeks

We know that running a test and analyzing results is exciting, but it’s a process that shouldn’t be rushed. When running LinkedIn ads tests, it's best to let your test run for at least two weeks. Why so long? If your sample size is too small, things like the weekend, holidays, and current events can make outliers affect your results more significantly.

For example, if you run a test on LinkedIn for three days and one of those days is a national holiday where people are not working, this will skew your results. Your audience would not only be smaller in this situation but also vastly different from the audience you may encounter on a regular working day. Running your test for an adequate amount of time helps assure things like this don’t result in outliers that skew your results.

Select ONE Variable to Test

A best practice we’re all familiar with is to ABT – always be testing – but you should still only be testing one variable per test. For instance, if you want to find out which call to action (CTA) text brings in the most clicks, you would change the text in the CTA of your ads and keep all other variables exactly the same. This means your ad creative, audience, and headlines should all be the same in every ad.

If you run a test with multiple variables changed, there is no way of knowing which one affected your results. If you change the CTA text and headline in your LinkedIn ad, how will you know which of these variables resulted in more clicks? 

Pro Tip: To ensure this isn't a mistake you have to deal with, duplicate your ads and change only the variable you are testing. This way, all other elements will stay identical.

Run at Least Three Variations

Once you’ve selected a variable to test, you can then give LinkedIn multiple options to test within. For example, in a single image traffic ad, you can run a head-to-head test of up to ten image options at once so long as all other options remain the same. Try to run at least three different variations when testing to see which resonates with your audience best, and consider keeping three to six ad high performing variations running in your campaign over time.

When you have multiple variations to work with, you can shift the budget towards top performers, turn off underperformers, and bring in new variations to run against your winners. You may be surprised to see that your winner up against your original variations does not take the crown against different competitors.

Show All Variations Evenly

It’s important to tell LinkedIn that you want to show all of your ads to your audience evenly. While it sounds like a good idea to show top performers to your audience more frequently when running a test, you want to give all ads a fair chance. Some ads will take longer than others to show results, so you want to make sure they are evenly distributed to your audience for the most accurate test.

In the example of testing for which CTA variation produces the most clicks, you would want all ads to be shown evenly because any ad that is shown more often would have more opportunities to get clicks.

Analyzing the Results

When analyzing your results, you want to go back to your original hypothesis to see if it was confirmed or denied. It’s exciting to look at the top-performing metrics when running a test, but it’s important to stay focused on your hypothesis and base your next steps on those results. Also, remember that just because your hypothesis was accepted/rejected does not mean that testing is over. 

You should always be testing, as your results will constantly change. What worked last year may not work this year. Your winning creative may not perform as well with all of your audiences. That same creative might not perform as well up against a different competitor.

 

There’s always room for testing and improvement regarding LinkedIn advertising. If you want more testing tips or assistance in creating and running your campaigns, contact drop & hook for a strategy session.