There have been many reports trying to calculate the value of a Facebook Like, with a wide range of results. The problem is that even when you use good science and research practices, the conditions for each situation are so specific that the value is useless when applied elsewhere. However, that does not excuse bad science. Which brings us to a report we recently found which claimed it could give you a hard number for a Like, using research that would make an 8th grader cringe. A chart of the results is included at the bottom of this article. The 70-page report examined a variety of social media research and then tried to convince us that Facebook Like is worth $8.
You heard correctly: Every time someone clicks a Like button it generates $8.00 US.
It’s a pity I wasn’t more popular in high school, I could have made bank. Needless to say, we found these results fishy. What follows is a list of the problems I found with the research.
Bias
To start, all the sources cited in the piece have an inherent bias; ChompOn, SumAll, Eventbrite, Spork Marketing, Syncapse. They are all businesses that make a living selling social media measurement and/or metrics. It’s in their best interest to show that a Like is worth money and that you must therefore hire them to measure yours.
Apples to Oranges
The studies had very little overlap and used different methodologies to calculate the value of fans, Likes, shares, follows, and retweets across five different SM platforms. Meaning there were very few points where you could compare the studies to each other. Or determine if each method would produce the same results. Wouldn’t it be better to have studies that measured the same things? If I calculate the boiling point of water in five different studies with five different methods and they all come out with 100 degrees C, then I can probably trust that number. There were only three items that were compared in multiple studies and all three had huge discrepancies in their results:
- 1 Facebook Share =$4.15-$14 (109% difference)
- 1 Facebook Fan = $174.17 -$214.81 (21% difference)
- 1 Tweet =$5- $25.62 (135% difference)
Science vs. Guesswork
The FAQs section even brings up these discrepancies, stating, “There are only three areas of conflicting data.” This is interesting, because those were the only 3 cases where the metrics could be compared. The statement could be reworded as, “Every time we compared the data we found conflicts.” The report’s helpful suggestion for dealing with the discrepancies is to calculate from the low end of the scale. Which is useful in that it allows you wiggle room when you talk to your boss: “Don’t worry that the numbers are low, we calculated from the low end of the scale,” or, “Our numbers are huge, check out how we calculated that from just the low end of the scale.” Even if you are getting great results calculating from the low end of the range, you’re still not sure what the real value is. Accurately measuring how well something is doing is just as important as measuring how poorly it’s doing. What good is it when your numbers can be off from anywhere between 21 to 135%? That stops being science and becomes guesswork.
Which study is most at fault?
The fact that the ChompOn study, that calculated the value of a Like, was in 2/3rd of the overlapped data and those two had the highest percent differences suggests it’s the biggest problem. If the ChompOn study is correct (and Likes are worth $8) then the Eventbrite and SumAll studies are at fault. If that’s the case this calls into question the values they calculated, which are:
- Re-Tweets ($20.37)
- Tweets ($25.62)
- Facebook shares ($4.15)
- Twitter shares ($1.83)
- LinkedIn shares ($0.92)
- Instagram Followers (scientifically listed as “10X Value of Twitter Follower”)
Other contradictions:
- If someone re-tweets something it loses $5.25 off its initial value as a tweet. Because the act of people reading and reposting content is less valuable than if one guy makes a single tweet that no-one reads?
- A Facebook share, people reading and then spreading content to others, is worth $3.85 less than someone clicking a like button.
What can we conclude from this: If the ChompOn study is wrong then the value of a Facebook like (plus three other metrics) are off. Or the value of a Facebook like is correct, in which case it means six metrics and 2/5 of the studies in the report are wrong. That’s not even looking at the (smaller) discrepancy between Syncapse and the Nonprofit Benchmark Report. There is the possibility that all the studies are wrong.
And there is another conclusion. Each study could have correctly calculated the value of their metrics. However, as was stated in the beginning, those numbers would only apply to the situations measured. ChompOn could have correctly calculated the value of a Like for Company X, but that doesn’t mean that same number can be applied universally. In which case the fault lies not with the data, but the conclusions the report inferred from it. ∞
Thanks to Dennis Yu at Jon Loomer for the image, where you’ll find a very informative article on Facebook marketing.
