Facebook Ads Case Study

Henry Fleisher
Aug 26, 2017 · 4 min read

Intro

Facebook Ads is one of the most widely used sites to advertise online. A large portion of Facebook’s revenue comes from advertising and they have over a billion users. What makes Facebook Ads really stand out is that you can target audiences based off numerous characteristics ranging from age, gender, location, income, marital status, pages liked, etc. Let’s take a deeper dive into what you can learn from advertising on Facebook.

Goal

For this experiment, I advertised this previous article (http://henryfleisher.com/startup-institute-why-did-i-choose-you/) on Facebook to see how many people would be click through. The Key Performance Indicator (KPI) was to have a click-through rate (CTR) of 1% or greater.

Audience

Every marketing experiment must begin with who you want to target. In this case, I created an audience which included the 22–35 age range living in Boston and New York (25 mile radius for both cities). Startup Institute has locations in Boston and New York so I felt like those locations would be most relevant. I also ran this ad for two weeks:

Facebook Ad

Findings

These were the results:

Performance for Facebook Ad

Facebook Ad Filtered By Time

Device & Platform for Facebook Ad

Age & Gender for Facebook Ad

Location for Facebook Ad

What do the numbers tell you? First, the campaign did not reach its KPI of a 1% CTR and had a CTR of .60%. This is due to numerous factors. One is that the ad only had a relevance score of 4. Had this ad been targeted to a better audience, the relevance score would have been higher therefore making it more likely the CTR would be higher. The one good thing is that the ad only cost $.48 per result. The times with the highest CTRs were 10:00–10:59 pm, 12:00–12:59 am and 6:00–6:59 pm.

There is even more to learn from this through segmentation of Device & Platform as well as Gender & Age. The Audience Network had the best CTRs and and the two highest CTRs were on a Android operating system. Another interesting find was that males age 35–44 had the highest CTR. That age range could have click through the ad more because sometimes, they are settled into a career and want to do something different. Users living in New York also had the highest CTR.

Next Steps

What did I learn? It is best to be granular as possible to find the right target audience. The wider net the audience causes, the more possible it is that your ad will show up to irrelevant users. This makes for money wasted on users who will not convert. Not only that but I am going to try to run another experiment with a higher budget but for a shorter amount of time. Another thing I would do differently is to A/B test the ad. Keep the audience the same but change one aspect of the ad whether its the image, headline, ad copy or call-to-action (CTA). This can improve your chances of reaching the KPI. The other variation of the ad copy should have been something about Startup Institute. I would also change the audience to include males aged 35–44 in New York who also used mobile devices.

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