Facebook ditches the Relevance Score
And rolls out 3 new metrics to give you better tools to succeed
Adweek just reported on changes to Facebook's advertising metrics:
Starting April 30, the social network is replacing the relevance score—which it introduced in February 2015 as a way to help measure whether ads run by brands were relevant to the audiences they reached—with three new diagnostics metrics.
- Quality ranking: How the ad's perceived quality compared with ads competing for the same audience.
- Engagement rate ranking: How the ad's expected engagement rate compared with ads competing for the same audience.
- Conversion rate ranking: How the ad's expected conversion rate compared with ads that had the same optimization goal and competed for the same audience.
These changes are being brought about to help advertisers better diagnose issues with ad effectiveness and provide for better optimization. Facebook believes that the current ‘Relevance Score' does not provide enough actionable insight for the advertiser and is now replacing it with more granular metrics.
Paying attention to the current Relevance Score, and the future 3 rankings, is important to optimize your campaign and ultimately lower your ad costs. Much like Google Ads' Quality Score, having a higher ranking can lower your costs per click for displaying an ad to your target audience.
There are several takeaways. First, realize that these new metrics will start to roll out over the next few weeks and by April 30, the Relevance Score will go away entirely.
Let's breakdown each key metric to understand how you can gain maximum value from these changes.
Facebook is going to score an ad's ‘quality' relative to other ads targeting the same audience. Possible scoring could include:
Below Average (Bottom 35% of ads)
Below Average (Bottom 20% of ads)
Below Average (Bottom 10% of ads)
You obviously don't want to be in the Bottom 10% of ads, which basically means that 90% of other ads targeting the same audience are scoring better. You might wonder how Facebook derives the score. According to the methodology, it includes a number of factors, such as whether users are actively ‘hiding' your ads, negative feedback (recall that every ad has drop-down options in the upper right to elicit feedback), engagement rates, poor user experience, etc.
So what if your ad is scoring below average? Consider two optimization strategies. First, evaluate and change-out the creative units to make them more relevant to your audience. Perhaps different imagery, more compelling headline/copy, use of video, etc. This is a perfect test-and-learn opportunity. Second, perhaps a low-quality score is telling you that you are targeting the wrong audience? This may be by design, of course, but worth considering whether you should tweak your audience targeting to match the message.
Engagement Rate Ranking
According to Facebook, the expected engagement rate calculates the likelihood that a person will click, react to, comment on, share or expand an ad. Engagement-baiting (For example, asking for likes, comments, and so on) will not improve your ad's performance.'
Some of the same optimization steps (creative and audience targeting) are similar to the Quality Ranking. But, here, an important consideration is your ‘Call to Action' (CTA). Is it compelling? Is it actionable? Tried-and-true CTAs move you away from passive calls (‘More Info') to active calls (‘Learn more', ‘Try it now'). Also, ensure your post-click experience is compelling as well as one of the user-experience factors which Facebook may consider.
Conversion Rate Ranking
This is a tricky metric as conversion rates vary relative to the product you are selling. For example, luxury, high-end purchases will have a lower conversion rate, on average, than a cheaper item. Here's where you can benchmark your expected conversion rate score versus what FB may be telling you. And perhaps you can glean insights on your pricing, audience interest and especially offer-based ads.
Each of these new metrics provides a more granular view of your ad performance. Consider each separately but also as a whole. Take a look at a optimization grid which Facebook provides as an example of a scoring and improvement matrix, which can be easily replicated for your campaigns.
And remember basic optimization procedures: first improve the below average rankings and get them to at least an average position, as compared with focusing on already-average ads and trying to make them better. In other words, always stop the bleeding first.
What's missing here? Feel free to leave a comment.