Want to know how many people will click on the new Facebook ad that you are creating? Now you can. Over the past few weeks Facebook has been testing out advertisement click estimates for campaigns and it appears it is back. While it doesn’t work for all campaigns, it’s an extremely useful feature. However it appears that there are still a few bugs.

In the process of creating one of my own ad campaigns I found that reducing my ad’s click bid would result in an increased volume of clicks. Does that really make much sense? Not really unless Facebook is also incorporating some sort of warped relevance algorithm. My guess is that it’s a minor bug in their ad click through estimate calculator. This is extremely valuable information for somebody running a campaign though.

Advertisers can back out of these numbers to calculate approximate daily impression volume as well as daily ad spend. While I’m not sure how long this feature has been around, it’s useful for someone looking to come up with projections about how their campaign will perform over the history of the ad. There are of course many variable involved in ad performance so my guess is that these are extremely rough estimates.

For the first day my campaign ran I was able to attract 27 clicks but the ad creator projected approximately 61 clicks. Obviously the time that the ad was created in addition to daily traffic variations will impact ad performance. So enough about the benefits of ad click projections. How can you get click projections for your campaigns?

Step 1: Create Your Ad
All you need to do is configure your advertisement as you’d like it to be displayed. Once it’s created you will have user count projections.

Step 2: Set Up As A New Campaign
When you go to configure which campaign you are placing this under and the CPC bid rates, you’ll want to select “Create a new campaign”. At this point you’ll be able to view click projections.

You’re Done!
While I haven’t been able to figure out how the click projections are calculated, they are most definitely useful to know. My guess is that it has something to do with user count numbers and then various limits which were calculated by overall usage patterns. In other words, these are probably fairly rough estimates. They’re most definitely useful though so check it out!