Over the past few months I’ve been thinking about how social platforms move from trial to habit in our daily lives. The trigger for this thinking was a self-awareness of how I first tried foursquare and then migrated that trial to a habit. Foursquare was a perfect test bed because the act of checking in to a location does become habit and can reinforce behaviors such as going to the gym in the morning or showing brand allegiance to, say, Starbucks.
So, how does social media gain more mindshare as users become immersed? My thinking followed a life cycle of social platform adoption:
- Discovery of platform
- Initial trial
- Self education on platform nuances
- Integration with rest of life
- Achievement of expert status
- Abandonment for other platforms
During the middle segments of the life cycle there is recommendation and promotion (advocacy) for the platform because of the network value (more people on the platform makes it more valuable to the participant).
However, each platform has to survive an ROI assessment by the individual. I don’t think that most people consciously think about the ROI in those terms, but they do decide whether they think the time spent on the channel is worthwhile.
Calculation of ROI, use of platform is only viable while value > investment:
U > 0 while U > (V - (R + I) + f(momentum))
- U = usage of the channel
- V = value the channel brings to the user’s life
- R = risk inherent in the channel, for example posting your home on foursquare
- I = investment required to use the channel, including time, money, reputation
- f(momentum) = the resistance of the channel to abandonment
Here’s an example of the calculation with my own use of foursquare:
- Value = ambient awareness of friends + record of attendance of places I like and trips I take + unlocked value of merchant offers + authority position of mayorship for places I frequent + points ranking with my friends + kudos for gym attendance when I share that on my other social channels.
- Investment = minutes spent on check ins.
- Risk = the considered risk of sharing information, this varies by type of data released and topics associated with my account. I’m likely to share a location of the gym, a comic shop, or a bar. I’m unlikely to share a visit to the proctologist.
- Momentum = habit and placement in routine of tool. For example, I always check in as I’m walking to the front door of the gym (and the tool is fast enough that the time frame works) or at work when I’m waiting for the coffee to pour from the Starbucks machine.
So, while I haven’t applied numeric values to these variables, it turns out that Foursquare has a positive Usage value… for now. It’s main threat would be a good Facebook mobile app that worked fast enough to actually use (hey, it could happen).
So, how does health use of social media modify this calculation? Health topics, such as the proctologist example above, are treated differently than more casual actions such as getting a coffee or going to the gym.
Value = increased by ability to connect with others and potentially have material effect on individual’s health and lifespan plus emotional health by talking with others who really understand. This increased value can then withstand higher investment and risk.
Investment = isn’t materially higher than non-health social usage. Unless we have those who use the social channel as a PHR (although this seems unlikely). Then investment is higher but so is perceived value.
Risk = much higher for health social. Stigmatized conditions (Hep-C, AIDS, constipation, obesity, etc.) carry social risk that can effect relationships and work progress. There is risk from insurance coverage re: being dropped or clauses that limit treatment for pre-existing conditions. (The ACA may change this risk calculation, but it will take a while before US citizens trust the insurance companies to adhere to the law.)
So, we come back to the equation:
U = V-(R+I)+f(M)
An example for the use of Facebook could be:
Usage = (ambient awareness and social persona) – ((others’ posts and employer opinions and privacy) + (time away from productive work, mobile app frustration time)) + f(real-world friends usage, discovery of new friends, checking routine, and messaging routine)
It is possible that there a platform multiplier on the value and investment calculation based on the design and usability built in. This would modify the equation:
U = p1(V) - p2(R+I) + p3f(M)
So, the next questions I have are how can we quantify these variables. Sociology and psychology almost certainly have measurements for the main aspects already: risk, investment, habit, value, etc. so it is a matter of tracking down those measurements and conducting experiments to prove or disprove the value of the equation.
For now, however, it remains an interesting way to think about the value of different social channels.
What do you think? Is this equation useful? or is there a better way to think about the value of different social channels?
Image credit: Rainer Ebert