LinkedIn Brand Lift Test: What Advertisers Need to Know
Written byLewis ShirfieldAccount Manager
Have you ever wanted to know how your LinkedIn ads have impacted members’ perception of your brand?
Launched recently, the Brand Lift Test does just that. According to Microsoft...
"Brand lift testing makes it easy for advertisers to measure the impact of your ads on brand metrics that you care about – like awareness, consideration, familiarity, favorability, and more. This helps you close the loop on your brand marketing efforts and better optimize for future brand value."
This testing feature runs in conjunction with your LinkedIn advertising, and is now available to all advertisers.
Creating a Brand Lift Test
Once you get through to the set-up stage, you will be presented with the specifics of your Brand Lift Test, and a preview of what your test will look like as an ad.
You can measure between 2-6 metrics, across either the whole account or specific campaign groups. You then get to decide your survey questions. You can choose:
Ad Recall (required)
Aided awareness (have you heard of [brand/product]?)
Brand familiarity (how familiar are you with [brand/product]?)
Brand favourability (how favourably do you view [brand/product]?)
Recommendation (how likely are you to recommend [brand/product] to someone else?)
Product consideration (how likely are you to consider [brand/product] for your next purchase?)
All of these questions come predefined with basic responses, which reflect the question. Some are yes/no answers, and some are more qualitative and are graded on a scale.
When your ad runs, it will appear as an ad run by LinkedIn, and not by you. Preview below:
There is a catch, though, and for a lot of advertisers, it may be a big one. There is a minimum cumulative budget in either the account or campaign group, which you must be over before you’re allowed to run brand lift surveys.
However, you won’t be charged for running these surveys themselves – the more your campaigns deliver, the more survey data you’ll collect, as these surveys run in unison with your campaigns.
If you do run a Brand Lift Test, you’ll want to learn how to accurately measure the results.
These surveys are delivered by surveying members in test and control groups and then analysing the difference in how they reply to questions about your brand.
They then assign a statistical strength rating, which essentially indicates how reliable your results are. You can also click into this rating, to find out some more statistics about your results:
Brand Lift Test Statistical Strength
If you like the data side of things then you will want more information about how your statistical strength is calculated.
When you click on the statistical strength rating, as shown above, you will see additional details such as the p-value and power.
The statistical strength of your Brand Lift Test will be determined by the p-value. The p-value represents the probability that your result – or a more extreme result – was caused by random chance.
For example, if the p-value of your Brand Lift Test is 0.05, then there’s a 5% probability that your result was caused by random chance.
The p-value is calculated by looking at the number of members who responded with a desirable answer in test and control groups, alongside the overall number of members who responded in test and control groups.
The p-value will range from Very strong to Very Weak, with Very strong (obviously) being the highest rating. You should only consider making any further decisions about your Brand Lift Test if they are rated Very strong, Strong or Medium.
If you have a Very week p-value and overall statistical strength it might mean that you’re jumping to a conclusion based on data that’s from random chance.
If you make a decision based on high statistical strength, then you’ll be able to take further action that will be more beneficial for your business in the long run.
The statistical strength is Very strong if the p-value is less than or equal to 0.05
The statistical strength is Strong if the p-value is between 0.05 and 0.10.
The statistical strength is Medium if the p-value is between 0.10 and 0.20.
The statistical strength is Weak if the p-value is between 0.20 and 0.30.
The statistical strength is Very weak if the p-value is greater than 0.30.
LinkedIn also provides a measure of power. This measurement would indicate how likely you are to gain the same test results if you ran the test again under the same conditions.
LinkedIn strongly suggests that your results will be more reliable if you follow best practices for campaign setup, while also running the test for at least two weeks.
In conclusion, this tool would be really useful for any advertisers looking to spruce up their top-of-funnel marketing strategy, with the results giving useful indicators to ensure you meet your KPIs.
In a broader sense, this shows LinkedIn is rapidly catching up with other social media platforms like Facebook in terms of features, which is great news for advertisers, especially in the B2B space.