Is there a mathematical formula to calculate the value of a “Like”?
Dan Zarella from Hubspot seems to think so, but I’m not sure the math works. Let’s take a closer look at Dan’s (VOAL) “Value of a Like” formula and dig a little deeper.
The VOAL formula ends up looking like this:
L (Total Likes): The total number of audience members connected to your social media account. On Facebook, these are Likes of your page, and on Twitter, these are followers.
UpM (Unlikes-per-Month): The average number of fans who “unlike” your social network account each month. On Facebook, this is an “unlike,” and on Twitter, this is an “unfollow.”
LpD (Links-per-Day): The average number of times you’re posting links, and potentially converting links driven from your social media account. On Facebook, this is the number of posts you’re making, per day, that lead to a page on your website. On Twitter, this is the number of times, per day, you’re Tweeting these kinds of links.
C (Average Clicks): The average number of clicks on the links to your site you’re posting on your social media accounts.
CR (Conversion Rate): The average conversion rate of your website, from visit to sale or visit to lead. This can be an overall average, but for increased accuracy, use the conversion rate measured from traffic coming from the social network you’re calculating.
ACV (Average Conversion Value): The average value of each “conversion.” In this context, a “conversion” is the action you’ve used to measure CR for. It could be average sale price or average lead value. For increased accuracy, use the average conversion value of traffic coming from the specific social network.
Although this seems to be a valiant effort to calculate a dollar value for a “Like”, it falls short of being fully vetted and has some major flaws and holes that we will look into. Before we dig into the math, I think one of the biggest omissions is the cost to generate the Facebook “Like”. It’s all well and good to be able to try and calculate the value, but without knowing the cost, how could you determine if it is a profitable venture. Whether you believe it or not; there is an associated cost with garnering a Facebook Like. Is the ROI of the time, effort and associated cost it takes to generate Facebook Likes worth it? That’s probably a good topic for another blog.
The value calculations used above are more in line with calculating the “Value of a Network” versus “Value of a Like”, although still problematic. Firstly, there should be a limit of time greater than 30 days. You can set the lifetime length to 12 months, so uninterested fans of your page aren’t skewing your value per “Like” based on a 5 or more year span. This would be calculated as (L/UpM).
The one very simple but critical flaw in the equation: if you have “L” in both numerator and denominator, it cancels out and doesn’t play any role at all. So the number of likes or the number of followers is not at all a factor in the calculation of “value”.
The formula used in this calculation has some major problems. Looking at the value of a “Like” or “Follower” is highly flawed logic. It really is not the right way to think about Facebook “Likes” or ROI at all. The inherent value of a “Like” is zero. An engaged community creates brand value, not an individual “Like”.
I used the formula above in an effort to determine the value of Email Answers 9,900+ Facebook Likes. Based on this formula, the value of a “Like” is $4.35. This would place the value of our total Facebook Likes at roughly $43,000. Besides the fact that this amount is so far from the true value, I am not quite sure what else to tweak to make it work. Email Answers tracks all inbound lead sources and where new visitors come to our website from. Tracking referrers is extremely important so you will know the source of you new lead, inquiry or sale.
Conclusion:
So, what is the value of a Facebook “Like”?
For most small businesses, a Facebook “Like” is not worth the time, effort or cost involved. The ROI, or lack thereof, should be the only factor in determining the effort.
I think Einstein might have said it best; “Just because something can be measured doesn’t mean that it should”.