29 Sep LinkedIn Conversion Tracking and Its Value
LinkedIn has announced and released a conversion tracking system that will allow universities advertising on the platform to track the performance of their ads beyond the standard reporting available on the LinkedIn advertiser dashboard. This will provide deeper understanding of user behavior and allow for the creation and configuration of targeting personas as well as optimization of ad copy.
Why Your University Should Be Advertising on LinkedIn
LinkedIn advertisements in the form of Sponsored Content are a popular and effective way for marketers to reach their target audiences.
The more detailed a prospective targets profile, the more information LinkedIn is able to provide advertisers for the purposes of targeting. Since most users are on LinkedIn to showcase their skills, networks, and experience, they tend to openly provide the most detailed background they can in order to appear desirable to potential employers or clients.
This level of insight into users’ experience and skills allows one to create personas that are intrinsically conducive to conversion. For example, let’s create a theoretical persona whose background would make them a valuable target for an advertisement featuring a healthcare-focused MBA in Tennessee. We can then review the audience size that results from our targeting.
Sample LinkedIn Persona and Audience
For our audience, we want an individual who has completed a four-year degree, preferably in a field of study that is contextually relevant to our Healthcare MBA. This individual would live in Tennessee, have 4+ years of work experience, and fall within the ages of 25-54. Technically, we would want our target to skew lower in age, from 24-44, but LinkedIn clusters ages in groups. Our target would not have completed any post-undergraduate degrees, as this would make them less likely to matriculate.
When we create this audience in LinkedIn, we are given an estimate of the total amount of users who meet our criteria. In this case, we have a substantial audience to target.
Here is the resulting audience available with our targeting parameters:
Audience Size: 173,000+ LinkedIn members
Work Experience: 4+ years
Age: 25-34, 35-54
Include: Bachelor’s degree, Bachelor of Applied Science (B.A.Sc.), Bachelor of Arts (B.A.), Bachelor of Business Administration (B.B.A.), Bachelor of Education (B.Ed.), Bachelor of Medicine, Bachelor of Surgery (M.B.B.S.), Bachelor of Pharmacy (B.Pharm.), Bachelor of Science (B.S.), Bachelor of Technology (B.Tech.)
Exclude: Master’s degree, Master of Architecture (M.Arch.), Master of Arts (M.A.), Master of Business Administration (M.B.A.), Master of Computer Applications (M.C.A.), Master of Divinity (M.Div.), Master of Education (M.Ed.), Master of Engineering (M.Eng.), Master of Fine Arts (M.F.A.), Master of Laws (LL.M.), Master of Library & Information Science (M.L.I.S.), Master of Philosophy (M.Phil.), Master of Public Administration (M.P.A.), Master of Public Health (M.P.H.), Master of Science (M.S.), Master of Social Work (M.S.W.), Master of Technology (M.Tech.)
At 173,000 potential users in our audience, we are below the LinkedIn suggested audience size of 300,000, but, since our audience is targeted well, our higher potential for conversion should make up for the small size.
With our newfound audience, we are now prepared to create a series of ads to entice our audience into seeking further information. As our audience engages with our ads, LinkedIn will store the data and we will be able to view this in what is known as a “Click Demographic Report.” These reports can be filtered by a number of variables.
After analyzing our click demographic report, we can create additional audiences that speak specifically to our best performing personas from the first. Prior to the launch of conversion tracking, this is where the reporting metric buck-stopped within the LinkedIn platform. After this launch, we will be able to make use of even more detailed conversion info.
How LinkedIn Conversion Tracking Helps
With conversion tracking, we can not only see which demographics interact with an advertisement, but we can also more accurately understand the level of engagement outside of the LinkedIn platform.
Since your conversion pixel will be placed in your webpage code, when users interact with your ad in the LinkedIn platform and visit your site, you will now be able to see which ad and audience netted you a conversion on the site itself.
Here are some of the new metrics the tracking pixel will enable advertisers to measure:
- Conversions – The total number of times people took a desired action after clicking on or seeing your ad.
- Post-click conversions – The total number of clicks on your ad(s) that led to a conversion.
- View through conversions – The percentage of impressions of your ad(s) that led to a conversion.
- Conversion rate – The percentage of clicks that led to a conversion (conversions divided by clicks.)
- Cost per conversion – The average amount you spent on each conversion (total spent divided by conversions.)
- Total conversion value – The total dollar value of all conversions (value per conversion times conversions.)
- Return on ad spend – The percentage of revenue generated for every dollar spent (total conversion value divided by spend.)
Making use of this additional data will allow a deeper understanding of the true value of each ad click and impression, and will help inform budget decisions. From a first perspective, this addition is LinkedIn keeping up with the Joneses, but the additional demographic reporting into the funnel that this feature ads should not be overlooked.
Typically, the next step in an ad platform will be to enable re-marketing. It’s possible that a future iteration of this conversion tracking/pixel addition will include a new method to reach users on LinkedIn who have already visited your site, or for whom you have email addresses.
If LinkedIn follows in the footsteps of Google and Facebook, we will likely see both website re-marketing and email list marketing that will allow advertisers to reach new subsets of users with strong potential for conversion.