LinkedIn Ads Performance – How A/B Split Tests Help Improve Output
First thing that comes to mind with online advertising is social media being the most common medium. Paid social media posts are the next thing.
At the top of your sales funnel, social media marketing works more effectively in reaching new audiences and increasing their engagement. While paid digital campaigns are great for capturing potential consumers – your social media audience with buying intent that’s mandatory to feed your sales funnel closure.
So, when the phrase ‘digital marketing’ or ‘online advertising’ is mentioned, LinkedIn Sponsored campaigns poses a great challenge for marketers.
As a marketing person, you need a good understanding about maintaining the level of user engagement and yielding the required click-through-rates.
And, that’s where you need to focus on A/B split testing.
A/B Split Testing:
In your LinkedIn marketing efforts, this is the fundamental technique you must use to determine the performance of differing elements such as ad copy, image, target audience or demographics, etc.
Comparing two versions of your ad or campaign with one opposing element will help you determine which variation of differing element performs better. Accordingly, you can optimize your campaigns depending on the impact of varied elements – integrate the version in your future campaigns that can return a higher ROI.
Pro Tip: At least three rounds of the same split test appear conclusive. Moreover, to rule out the probability factor, statistical difference must be significant enough in A/B split testing.
What Can You Test?
The best way to start testing is to begin with ONE element only, which means Campaign A and Campaign B should be identical except for that ONE variable you are testing.
Differing two elements or more will make it impossible for you to understand which variable actually made a difference.
Moving forward, let’s take a look at what elements you should test and that can make a significant difference in your LinkedIn marketing campaigns.
1. Ad Copy:
Copy style is the best way to clickbait your audience. So, it should be the first element to test as you run your LinkedIn ad campaigns. The aim is to determine which copy style significantly triggers a desirable action from your target consumers.
Most commonly occurring types of copy style include;
- Question-led copy
- Empathy-led copy
- Benefit-led copy
- Statistic-led copy
Each ad campaign with any of these styles becomes self-explanatory. All you need to figure out is how your audience reacts to a specific clickbait.
For instance, a question-led copy contains a question that addresses the pain point of your target audience and ends with an appropriate call-to-action that follows the solution to their pain point. While, benefit-led copy states the value for your consumers that will get from the sponsored content before it ends with a call-to-action phrase.
Pro Tip: Try a combination of split tests with a few or all types of ad copies and find out how the audience engagement varies.
Usually, question-led copies perform better than empathy-led copies; however, this is no thumb rule. Things may also vary depending on your target industry and audience selection. For instance, targeting business owners and managing directors of SMEs may swap the results and your empathy-led copy may perform better than your question-led copy.
Different groups of the audience react in a different way to varying copy styles. Therefore, it is highly advisable to run multiple split testing campaigns catering to the varying preferences with the same opposing elements until you get meaningful data – to determine which variation works the best to draw a conclusion.
2. Audience Selection:
Now, this is the best way to reach and engage your potential consumer base. The best thing about LinkedIn is that it offers a comprehensive range of targeting options that can be filtered to reach your audience.
You can filter target audiences by groups, skills, job titles, company size, designation and industries, etc. – whatever suits your LinkedIn marketing strategy. For audience-based A/B split testing find your sweet spot in filtering options for your LinkedIn ads.
For instance, if you are targeting software developers, using job titles and job functions you may get thousands of people in the pool. However, broadening this sphere for the same audience by using more filters like geography, job title or function, job seniority, and company size, you may get millions of people.
Briefly, try different combinations of audience segmentation for your various clients across multiple industries.
Besides, audience segmentation using filters, budget also plays a vital role. We suggest trying;
- Same audience segmentation with different budget.
- Different audience segmentation with same budget.
Pro Tip: To avoid data corruption and overlap of your audience pool, run your split test campaigns based on different audience segmentation in different time frames.
3. Bid Strategy
Different bidding strategies perform differently for different types of campaigns. And, A/B split testing helps you determine which campaign is worth pursuing to get desired ROI.
Try any of the following bidding strategies;
- CPC (cost-per-click)
- CPM (cost-per-thousand-impressions)
Pro Tip: Run your LinkedIn ads using both bid strategies for the best ROI.
Here, you must understand that the bid amount you enter doesn’t determine the amount you end up paying for ad clicks or impressions. Remember, you bid against your competitors to capture the same audience and that may not certainly coincide the total cost of your ads.
Lastly, never forget that even little variations can leave huge impacts on your paid marketing campaigns. So, continue testing, evaluating and optimizing your ad campaigns to achieve the desired results that are clear and conclusive – helping you make your future campaigns more productive.