What is this funny looking formula you may ask? Well its still a hypothesis I’m working on. Its dedicated to the dreaded question asked by clients to social media strategists about how much fans should I have on Facebook to be adequate.
Its my fault really. I was asking for it.
I like clients that understands how social media works and how to generate leads or even sales from it through the right conversation and guerrilla tactics. How to generate fans from targeted ads, getting the message across through reach marketing, influencing the friends and friends of fans, and optimizing posts for great impression performance. So I taught them about it.
Understanding all that, they’ll surely end up asking: “So how much fan do I need to get my message across to everyone?”
When you are able to optimize your message, boost it to reach your fan’s friend of friend, you do come to a conclusion that you don’t need to have all the fans in the world. So how much is enough or how much fan should I least have? Thats a hard question to answer. Not saying that its impossible to answer, but there is no absolute number you can pull out of a hat, and you need to be ready to back that up son.
So I started googling for answers and there was none. So I guess I’ll just make one. Started researching about Frigyes Karinthy’s “six degrees of seperation” theory, Robin Dunbar’s hypothesis about how a human can only have a maximum of 150 close friends at one time, to Facebook’s guidelines.
and collaborative cheat sheets
Through a dozen theory and hypothesis I started to piece my own hypothesis:
- Those considered potential fans should be those that fit the product/brand’s target market; age, gender, interests, etc.
- Individual reach is measured by its closest friends, meaning that each users is only accounted for 150 of their friends, even though they have more than that number.
- The number of reach per individual fan is 3, as it is the number you can effectively reach friends of friends of fans on facebook marketing.
- Possibility of overlapping friends is taken out of the equation as in social media, the more you receive a story from friends, the higher the probability of friends trusting that information.
- Scores should be evaluated at least once every year to adjust to new data and changes.
So to determine the number of User Population (U.Pop), we determine the number of active facebook users in a specific country or area, and calculate that with the targeting data to come with a result. So lets say we’re targetting all women in Indonesia between the age of 25-34, that would be (52.700.000 x 47%) x 68% = 16.842.920
So roughly there are almost 17 million Indonesian women aged between 25-34 who have facebook accounts. You can add other specific variables like interests to the equation.
The number of U.Pop is then divided by the individual reach. So its 150 (close friends) x 3 (reach through boost). Why 150? Well you know how facebook only shows updates on the home timeline from friends you have good interactions with, CMIIW, well they didn’t release any data on how many friends updates they show to you. Manually counting from my own home timeline scrolling down and getting unique users updates I receive from the past 5 days, I counted 129 unique accounts. So Robin Dunbar’s theory should fit here, after all Path is using it.
So, 16.842.920 divided by 450 equals 37,429, meaning that this year the brand should at least gain that much fan, and recalculate those numbers again in the next quarter to new data.
As I have said before, this is a hypothesis. Its not exact or proven science. Its open to testing, ridicule, dispute, modifications and discussions. Feel free to voice what you think on the comment section below.