Unlike traditional media, digital marketing platforms provide the capability to generate immediate feedback and track the results of advertising campaigns.

Metrics can be reported in digital marketing dashboards almost instantly and can help advertisers know how a given campaign and its ads are being received by their target audience, what is or isn’t performing well, and what may need to change to improve KPIs and ROAS.

That said, when it comes to LinkedIn Ads, there are additional measures advertisers can take to deepen the insights they gain from their ad performance reports. It’s this level of insight that can help you to mitigate costs, increase control over your campaigns, and improve efficiency.

Three tips we recommend to improve your LinkedIn Ads reporting are to segment your target audience, name campaigns strategically, and A/B test.


Step One: Segment Your Audience


LinkedIn offers some incredible targeting options within Campaign Manager, and it can be tempting to lump everyone you want to target into one big campaign and hit the ground running. But, taking the time from the beginning to segment your audience into smaller, specific groups can create more accurate reporting in the end.

There is an extensive variety of targeting options and filters available to choose from on LinkedIn, from job titles to job functions, skills, groups, industries, etc. And each of these types of targeting are available for just about every category you can think of. So, how to begin?


Segmentation Example


Let’s consider a medical tech company advertising on LinkedIn to raise funds by targeting potential investors. They believe that doctors, lawyers, and MBAs may have the most interest in investing.

Now, instead of creating a campaign including all doctors, lawyers, and MBAs on LinkedIn (plus any additional targeting requirements applied such as location, seniority, or company size), we can create three separate audiences: one audience of doctors, another of lawyers, and a third of MBAs.

Breaking out the audience into these three segments will allow us to launch ads and monitor performance separately to each type of individual. This way, we can identify which type of audience is actually interested in investing in the medical tech company.

If all three were grouped into one audience, we wouldn’t know with pinpoint accuracy if it was the doctors, lawyers, or MBAs who were interested and clicking on the ad. But by segmenting our audience, we can identify which persona(s) are most interested in our offer and can then drop those audience segments that are uninterested and scale those that are.


Additional Segmentation


LinkedIn also creates natural segmentation by requiring separate campaigns to be created for running different ad types(such as single image ads, video ads, message ads, etc) to the same audience. This level of segmentation allows you to build reports based on different ad types, so ad performance can be analyzed based on differing benchmarks.

In order to run campaigns more efficiently, we’ve found the ideal audience size to be between 20K – 80K. Proper segmentation also allows you to narrow targeting to this recommended size.

In total, LinkedIn offers 30 different categories of targeting criteria to play with. This can result in a lot of audience segmentation strategies and combinations. We’ve really only scratched the surface here.

Lucky for you, we recently wrote a whole article on LinkedIn Ads audience segmentation strategy. Check it out!



Step Two: Name Campaigns Strategically


Though it may not initially seem like the name of an individual campaign matters all that much, systematic naming conventions make it easy to generate reports based on ad performance data. Using a consistent system makes it possible to easily compare data and determine statistically significant variation to improve performance. 

Specific campaign naming conventions also make it easier to identify the ad type and the segmentation filters used when creating the campaign audience. Rather than opening up a campaign to review the various audience filters, advertisers can simply look through the campaigns listed on the home “Campaign Performance” page on campaign manager and identify the pertinent information.


Campaign Naming In Action


For example, at B2Linked, our campaign names typically follow this pattern:

Ad Type | Specific Audience Category | Industry | Seniority | Company Size | Geo

If we were to use this process for naming one of the example three campaigns we segmented earlier, it may look something like this:

LF | MBAs | Healthcare Ind | Dir+ SR | 500+ CS | US

A glance at this campaign name would tell us that the campaign is running Lead Gen Form Ads to LinkedIn users with an MBA degree, who work in the healthcare industry, with a seniority level of “Director” equivalent or higher, at a company with 500 or more employees, and who live in the United States.

Naming campaigns this way works in tandem with step #1, as it allows you to easily identify audience segments at a glance, compare results, and optimize off of those segments that are performing well.

You can choose to name your campaigns in any way that you like but creating a campaign naming system like this will offer more efficient reporting.


Step Three: A/B Test Accurately


A/B testing is one of the greatest tools available to advertisers. With it, we can quickly and accurately test a variety of variables to determine the effectiveness of each one and optimize campaigns. In order to glean these insights, it’s important to set up any A/B test in a way that will return accurate data.

It can be tempting to test every possible variation at once, but the only way to determine a legitimate cause and effect relationship from an A/B test is by testing one variable at a time. Testing one variable ensures that you can attribute any variation in performance to that specific modification.

Another method to more accurately identify significant differences in performance is to name each individual ad with an indication of what testing variable it includes. LinkedIn allows separate ad names for every ad launched on the platform. Use the names advantageously to indicate specific information about the ad.


Ad Naming In Action


For example, at B2Linked, each ad name indicates the platform, ad type, date launched, number in the launch set, and test indicator. An ad from the campaign we fictitiously created above could be called:

li (LinkedIn) + lf (Lead Gen Form Ad) + 22/05/31 (launch date formatted by year/month/day) + 09 (# of ad in launch set) + B (test indicator, either A or B) = lilf22053109-B

Like strategically naming your campaigns, naming your ads can help you to identify specific characteristics about each ad at a glance and can help make measuring A/B test results easier, as well.


Summing it Up


LinkedIn Ads reports on ad performance almost instantly as campaigns run and can offer insights into what about your ads could be improved.

Though taking the steps outlined here are going the extra mile at the beginning stages of running LinkedIn Ads, the insights you can get from setting everything up this way can help you make more informed decisions, which can lower LinkedIn Ad costs, improve campaign efficiency, and give you greater control over your campaigns.

Have you tried any of these performance reporting strategies? If not, what LinkedIn Ad reporting strategies do you like to use? What results have you seen? Comment below!

And if you’re currently running LinkedIn Ads but are having trouble generating qualified leads at your desired cost, apply to work with our team of experts.


Written by Shannon Bloom