LinkedIn Ads is among the best marketing platforms for advertising to B2B audiences. This is due to both extensive user base and functional capabilities offered by the platform. However, with the multitude of tools available, we sometimes opt for the most straightforward out-of-the-box techniques, failing to adjust our tactics for the specific task at hand. This, in turn may lead to data inaccuracies and overspending.

Below we examine an approach to audience prospecting that will allow you to find and reach out to the right decision-makers in your chosen niche. Not only will this help you focus your marketing efforts and ensure the success of your campaigns, but it will also allow you to optimize ad budget and advertise to more specific target groups.

Often, the most intuitive way for marketers to conduct search and advertise to the desired audiences is by utilizing search attributes such as Job title, Company industry, and Job seniority. Unfortunately, the results won’t always be 100% accurate.

Based on the attributes you enter, LinkedIn will try to match what it considers to be the right audience. However, the algorithm can sometimes fail, which is especially prominent when working with larger audiences.

How do we see it? Consider an example. 

Let’s say, we’re trying to advertise to an audience of small-medium business decision-makers in the retail industry, located in the USA. Based on the common approach, the ideal setup within the LinkedIn Ads campaign manager would look as follows:

  • Location: United States
  • Company industry: Retail
  • Company size: 2-10 Employees
  • Member Age: 25-34, 35-54
  • Job Title: Owner, Founder, Chief Executive Officer etc.

As a result, LinkedIn forecasts 83,000+ audience for the mentioned criteria. But how can we be sure that this will really allow us to target the right group? The following step helps verify this.

Take the resulting range, and apply additional search criteria to exclude the audience with the following attributes:

  • Industry: Add all the other industries besides the one you want to focus on.
  • Job Title: Exclude all the irrelevant titles – Sales, Developer, Designer etc.
  • Member Skills: Exclude the skills that are less likely to be added by the decision-makers – Customer service, Design, Microsoft Office etc.
  • Member Traits: Add “Job Seeker” and “Open to Education”

After applying the additional criteria, you end up with a much more manageable audience list of 27,000+ entries.

To further make sure that you are targeting the right people, check the “Functions” of the audience under the Forecasted Results.

Note: You can also use LinkedIn Sales Navigator to see details of your targeted audience.

The described approach is a simple yet very effective technique that can be used to prepare LinkedIn Ads campaigns, targeting audiences of any size and composition. By applying exclusion of irrelevant attributes from the initial bulk of estimated results, you can narrow down your search and ensure you target the right audiences.

Additionally, since LinkedIn Ads is known to be a rather expensive ad platform, a poorly optimized targeting approach will result in unnecessary (and totally avoidable!) spendings. Thus, narrowing down your target audiences the right way, will make sure you get the best out of your ad budget.

In the same way that audience prospecting affects the overall success of your ad campaigns, reliable data sourcing and representation help guide the bulk of other marketing efforts. 

The household name for compiling and building insightful easy-to-read data reports is Google Data Studio. However, reporting with it can be tricky, since it requires a certain amount of previous experience with the tool to use it effectively. 

As a great starting point, you can check out this free webinar to get a thorough understanding of the basic principles and best practices of building great-looking data-rich reports with Google Data Studio.