Stop Wasting Your Ad Budget; Use LinkedIn Matched Audiences
Hot take: LinkedIn Matched Audiences is better than LinkedIn’s audience builder.
Less-hot take: It’s better for us, and maybe it’d also be better for you.
A while back, we decided to run an experiment to find an answer to the age-old question, Which is better, LinkedIn Matched Audiences or LinkedIn’s audience builder?
To get an answer to that question, we needed two audiences. To ensure we didn’t just create one fantastic audience and one less-fantastic audience to skew the data in the direction that suited us best, we decided to get some outside help.
So, we got a digital marketing agency to create an audience using LinkedIn’s audience builder and pitched it against an audience made using LinkedIn Matched Audiences. These audiences were designed to be as true to our ideal customer profile (ICP) as possible.
And the results speak for themselves:
- Cost per view with Matched Audiences: 0.70€
- Cost per view with LinkedIn’s audience builder: 1.10€
That means the cost per view was 36% cheaper with our Matched Audiences audience than with the audience created using Linkedin’s builder.
Okay. Cost per view is cheaper, which is excellent, but how does that translate to LinkedIn Matched Audiences necessarily being “better”?
That’s a great question, and understanding the answer to that requires just a little knowledge about what affects LinkedIn ad costs.
LinkedIn advertising costs
Based on our research, four factors affect LinkedIn Ad costs:
- Target audience
- Bidding strategy
- Objective
- Linkedin ad relevance
I will not be diving into all of them because it’s only that last factor that is relevant (pun intended) for this experiment.
LinkedIn ad relevance
LinkedIn ad relevance refers to LinkedIn giving your advertising campaigns a quality score.
So, if your ads are performing well, which LinkedIn tracks by measuring factors such as CTR rate, video completion rate, and engagement rate, your quality score will be higher. And the higher your quality score, the lower the cost of your ads.
This is how LinkedIn “rewards” good, relevant ads and “punishes” bad, irrelevant ads.
Our advertising audiences
As I mentioned, both audiences represented our ICP as faithfully as they could and were shown the same ads. Here’s what our audiences looked like:
Matched Audiences audience
Inclusions:
- ICP list
Exclusions:
- Irrelevant seniority levels
- Not decision-making roles
- Existing customers
Comparison audience
Inclusions:
- Relevant seniority levels
- Decision-making roles
- Relevant member skills
- HubSpot, Salesforce, Pipedrive, Microsoft 365
- Relevant job functions
- Sales
Exclusions:
- Existing customers
So, we targeted people of the same seniority level, and the only difference between the two audiences was that one included “ICP list,” and the other included “Relevant member skills” and “Relevant job functions.”
Which begs the question, what did we include in our ICP list? Hint: It wasn’t more demographic information; it was more company information.
Our ICP list was all the companies in our database that fit the following criteria:
- Country of operations: USA, UK, Germany, France, Italy, Spain, Australia, Canada
- Industry: SaaS [Based on our Vainu Custom Industry taxonomy]
- Technology: HubSpot
The difference in the results between these two audiences would suggest that it’s not enough to be targeting the “right” people; you need to be targeting the “right” people at the “right” companies.
This really can’t be all that surprising. Even if your solution can help all companies, it’s doubtful that all companies will find it equally helpful. An often overlooked element of successful sales and marketing is the focus, focusing on the companies that are the most likely to find your solution helpful.
Using company data when creating your LinkedIn ad audiences lets you focus on the companies that find your content the most relevant and engage with it the most, leading to lower ad costs.
Your marketing messages still get sent out to the “right” people, but don’t get sent out to the “wrong” people who don’t find your content interesting, which means a more efficient allocation of your limited company funds.
In case I’ve written many words but haven’t communicated very much, here’s a pair of simple equations that a colleague sent me to help illustrate the point:
- Message A + audience built using just people data = bad/expensive campaign
- Message A + audience built using people and company data = good/cheap campaign
Want to try building a list for LinkedIn Matched Audiences yourself?
With that, you should hopefully have an idea of why we boldly stated that LinkedIn Matched Audiences is better than LinkedIn’s audience builder at the start of this blog.
If you want to try and run a similar experiment yourself and see whether you can get your LinkedIn ads to perform better using Matched Audiences, here’s a video showing how to build a list for Matched Audiences with the help of Vainu.
To create a good list, you might need some company data. If that’s the case, signing up for a free trial is an excellent next step.
You’ll get unlimited access to our database and search platform and be able to try creating some company lists that you can use in your Matched Audiences campaign.
Until next time 👋
