logo f

Contact  | About |

  • explore resources 2014
  • join social trax 2014
  • Reap the benefits with our cutting edge Social Media network partners...
  • Dive into the Social Trax Discussions - enlighten others, or get enlightened...

Sign up for the Newsletter

Exactly How Do You Value a Facebook User ‘Like’?

112987077

I am the farthest thing from a Quant that you will ever meet so I polled some experts in interactive advertising to help me figure out this question: how do you value a Facebook user 'Like'? Is it based on hard data, like purchases, or softer metrics such as user engagement, time spent, referrals, shares or what? There are a lot of data points to consider when working out a specific value.

Fortunately, I belong to a private email list of highly experienced professionals in senior management positions at ad agencies, ad networks and major brands that are a lot smarter than me when it comes to data and metrics. I asked them how to establish a baseline value.

A small firestorm erupted and a number of these experts disagreed with each other and fired opinions back and forth. Here's an extract:

"....It was out of that love of numbers that I began work on the value of a like (VOAL) formula.
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.

It is relatively easy for any marketer with decent analytics software (like Google Analytics or HubSpot's Marketing Analytics) to track the traffic from social networks and assign lead or customer acquisition values. It becomes more difficult when we want to understand how much time or money we should feel comfortable spending to build our reach.

The first part of the formula uses UpM and L to calculate a churn rate for your social media following. This will allow you to derive the average length of time an individual user will be subscribed to your social network profile.

The rest of the formula calculates the VOAL metric for each follower using the number of links they're exposed to over the length of time they follow your brand and the values from your conversion funnel......"

But then came this immediate response:

"Well, I think they are getting warmer, but not quite hitting the mark. The issue I keep seeing with most social analytics is that everyone keeps trying to apply one-to-one attribution and not accounting for all other communication touch-points, which is never going to work. The root word is "social" or community, and its relationship to something. Therefore, it must be measured as a collective. This is just another example of using past effects to predict future effects without understanding causation.

We are starting to take our clients down a different path. We started using KPIs around social capital value and using attribution scoring to assign value to all social connections. Regardless, of whether it is media exposure, a like, a share, interaction with content, a purchase, a registration, etc.; they are all social connections. Even a viewable impression is a social connection. Each will just hold a different value in its contribution to a brand's social capital. However, not all social capital is equal. It varies depending on the ultimate objective for driving a collective action."

Which was followed again almost immediately by this:

"I hate this stuff. Why do people allow it to get published? (BTW - the negative comments at the bottom are basically spot on)
This formula has two major problems:

1) It does not give the value of a like - just check the units. The result should be $/like. This is not the case
2) Most irritatingly the formula tries to disguise itself with complexity (this makes me angry). There's only three variables in the formula!

Lets take it apart shall we?

The formula given in the blog post is

value of a like = (L/UpM)*(LpD*30)*(C/L)*(CR)*ACV
Start with LpD*30 = LpM (Why some units are in days and some in months? Why would you do that? Why? Why?)
value of a like = (L/UpM)*(LpM)*(C/L)*(CR)*ACV

Rearrange...

value of a like = (LpM/UpM)* (L)*(C/L)*(CR)*ACV

Clean

value of a like = L/U* C*CR*ACV

Restate in english

value of a like = (Likes/Unlikes) * (total conversion value of clicks on social links)

This makes no sense."

Wow! They lost me at (L/UpM). The formula looks like the stuttering of an autistic calculator to me. But what I discovered in reading through this is that, fundamentally, it is impossible to define an exact value for that user, but you can assign a value based on your other business metrics.

What does that mean? Well, if you have a B2B product or service and your metrics are based purely or primarily on sales, then you should have a well-articulated LCV (Lifetime Customer Value) based on past experience. If so, common sense should tell you that new customer acquisitions will have a par value. In this case, A = A. If you segment your users and those Facebook users prove to buy less, then you have A = A- and you adjust your marketing valuations accordingly.

When it comes to B2C, it becomes an unholy mess if you try to calculate a specific value that includes vague metrics like pass-along referrals, interactions or brand mentions in forums and blogs, etc. There are hundreds, if not thousands of variables that can be considered, but – and this is the important part – those variables differ from one individual user to another. So someone who may be a regular buyer and has very distinctive purchasing patterns (average purchase, time spent, etc.) will very likely have a higher perceived value than another user who is a key influencer but doesn't buy. This influencer may actually spend zero dollars but direct the spending of dozens of others. TechCrunch, Mashable and dozens of other blogs prove that every day.

So, bottom line: how do you determine the value of that Facebook user 'like'? Make it up. That's right. Just take a stab at it based on your business model. You may be right or nearly right or you may be entirely wrong. It doesn't really matter. What DOES matter is that you look at your total investment in Facebook and the tangible returns in terms of revenue and total new users against your marketing investment. You can trend this in a reasonably short period of time and decide if it is going the direction you want. No, it's not scientific and no, the Quants in your organization will scream bloody murder. But I can almost guarantee you that the results will be obvious much faster with a whole lot less experimentation and optimization cost.

Now I'm going to go hide in the closet before the Quants come looking for me.

 

About the Author: Michael Crosson is currently the founder and publisher of SocialMediopolis.com, a private community for social media marketers, as well as the founder and moderator of the largest social media group on LinkedIn, (Social Media Marketing) with over 500,000 members.

quote 1

quote 2

quote 3