Most people who work in the social media or digital media (web, social and mobile) space saw last week’s article about Facebook losing 80% of its interest level by 2017. The internet responded in a comical and resounding way expressing, often comically, how flawed the model was.
I’ve been following their premise since 2011 not as a forecasting model but as a method to identify preference, affinity or trends in social networks. Most social networks have not survived (thrived is a better word) beyond six years. Facebook, Twitter and others have broken the mold and are defining a new generation in communication. There is much to be learned but there is even more to come as we see the maturity of social media as a legitimate communication method and strong business model. The cycle resembles what we saw with search, with several years of mediocre products and finally a stable, reliable solution (Google, if you live in a box) which helped define the industry.
So how does one go about predicting the future of Facebook, social media or any online app or technology? Let’s look at a fuller spectrum of the information required to build a semi-accurate model of social media dynamics.
There are plenty of things to consider. In short, follow the money and masses and then see if they can mature into a long-term solution. There are plenty of 250M-user social networks who have come and gone. Today, it’s the huge networks with at least 500M users, or a very targeted audience (like LinkedIn), who survive.
Here are some of the theories and models that could be used to more accurately predict the lifetime of a social network:
- The Technology Adoption Lifecycle – Developed in 1957 by Joe M. Bohlen, George M. Beal and Everett M. Rogers (I know, don’t you wonder if they all have the same middle name also ) at Iowa State University. The team developed the diffusion process and later published the Diffusion of Innovations. Ironic to the Princeton study, the original publication (below) included a graph that actually didn’t graphically decline over time. The Innovation Adoption Lifecycle chart below, is an updated version which shows (graphically) a decline in adoption, which may not be the case with many technologies.
- Business as usual, the product lifecycle – One of the most common models for any business is identifying their product lifecycle (graphic below), a theory developed by Rayond Vernon in response to a model by Heckscher-Ohlin, which attempted to explain the observed pattern of international trade. You can take the chart and pontificate Facebook’s future based on what appears to be its current maturity. Fortunately, Facebook has launched several products (each with their own lifecycle) since launch, including their most notable and profitable ad platform which I would still call in its growth phase. If you were to map out all of Facebook’s products according to the model, you may be able to see some trending but the length, speed and size of each of the stages changes for each product so an accurate prediction will be tough.
- Organizational life cycle – Corporate culture, stability and growth in innovative companies is what makes them successful and what helps them continue to be successful. You have to also include the organizations life cycle to help determine an overall model of the organizations health, longevity and stage of stability.
- The Hype Cycle – What John Cannarella and Joshua A. Spechler (authors of the Epidemiological model of online social network dynamics) had right was the impact of social media hype and the impact that hype can have on an internet website or social network. There is some truth to the hype that exists but where they erred was the impact of that hype on an actual business. Google Trends is a great site for monitoring trends but Google search trends tend to be more indicative of hype than health (although, not always). If we look at Gartner’s hype cycle below, it tends to follow a pattern closer to what Cannarella and Spechler came up with to produce 2017 as the end-date for Facebook, if you compress their chart it will look closer to this on its downward slope. Gartner’s analysts have since written a book on how to leverage the “hype cycle” which I’m sure are intentionally (or not) part of any PR and Marketing team’s strategy.
- Virality – How viral and the structure of that viral impact is another factor that can help determine the life of a post but also the health of a social network. Social networks that optimize the ability to maximize the structural virility of online diffusion have a fundamental advantage (SEO, reach, velocity of reach, etc.) over networks that do not. If you include the “Wiener index” (Wiener 1947) we can define the structural virality v(T) as the average distance between all pairs of nodes in a diffusion tree T; that is, for n>1 notes, where dij denotes the length of the shortest path between nodes i and j.2 Equivalently, v(T) is the average depth of nodes, averaged over all nodes in turn acting as a root. (Microsoft Research & Stanford University)
- Active Users Over Time – One of Facebook’s data scientists, Mike Develin posted data (below) exposing Facebook’s active user stats and you can see they definitely aren’t declining (anywhere), although they are starting to level off in the U.S. and Canada. To determine the growth, velocity and to model potential we can use this data to forecast future active users and the speed at which they are increasing or decreasing.
- Demographics over time – all businesses are impacted by demographics. The impact that one generation can have on a social network can be huge or largely insignificant if there are enough users in other, stronger demographics. If you look at Facebook, even in 2010, their largest users base was between 18-54. Today the youngest generation is using FB less but almost every other generation is still growing. To build a model you would have to determine the change in demographic profiles over at least a decade, preferably several. You would have to span several generations and includes inflation in older generations (who pick up technology and online sites/networks slower) over time and the rise of a younger generation who may or may not be interested. In Facebook’s case, the youngest generation may not be interested but what happens when they mature and does it really impact that much change when all other generations are still growing. To decline, you would have to see multiple generations lose interest, including one of the most impactful online the 18-34 demographics.
If we were to prepare a very rudimentary demographic equation to a social network it might look something like:
Population Growth (P1, P2), Births (B), Deaths (D) and Social Adoption (Adi) and Social Non-adoption (Ad0)
FB Demographics in 2010
Facebook Demographics Jan, 2014
- Money, Money, Money – the financial health of a company has a lot to do with their ability to survive the good and bad times. Here’s more Facebook financial data than you care to review. Although not very relevant during a social sites early stages, how much money they have to survive does matter. Look at Yahoo!, they would have died long ago if it weren’t for their publishers and their large pot of money:
Stats to support the potential for continued growth or stability at Facebook:
Current FB Highlights (from them):
- 874M/mo. active users who used mobile since 9/30/2013
- 727M daily active users on average in 9/2013
- Approx. 80% of our daily active users are outside of the U.S.
- 1.19B/mo. active users as of 9/30/2013
- 95% of user log in daily
- 73% of user access Facebook via mobile
What Does The Future Hold For Facebook, It’s Not ALL Good:
There are several things we can watch that may negatively impact all of the above charts and increase the timeline for Facebook’s decline or demise to meet or preempt a 2017 doomsday. Some of these include:
- Product innovation – a big part of staying relevant is creating new products to meet missing demands, reach demographics and to remain competitive. Will FB continue to stay on top or are they being eaten alive by their competition, what do you think? I think there are valid reasons why they have lost that competitive feeling (I’ve blogged about it if you need more to read in your life)
- A flawed ad platform – Facebook has an ad platform different from most. Everyone is an advertiser; any consumer can promote a post, the same as a corporation or anyone else. How long will people put up with everyone and their dog having the ability to overtake their newsfeed with promoted posts? It really depends on the next point, how their algorithm matures.
- Newsfeed and search algorithms make and break companies – we all watched Google take over the behemoths, Yahoo and MSN Search over a decade ago. Today we have yet to see Facebook perfect their algorithm. The reason they started being successful and the reason most of us loved FB is because we could see everything (or almost everything) our friends were doing by scrolling through our newsfeed. Today, Facebook has trimmed down our newsfeed to a mere 7% of the total content posted by our friends and “likes,” and is injecting more and more paid posts, ads and promotion into our newsfeed and pages. Time will tell but it’s not looking good right now, the algorithm is not making everyone happy and I hear it from almost all demographics daily. This leads to the next issues…
- The value of engagement – A like shows intent and action but a comment and share, in my opinion are worth far more. I’m curious to see where they go with the algorithm and how the prioritize these engagements. How advertisers, companies and page owners use FB is heavily dependent on how it benefits them. If creating stronger relationships is Facebook’s future, they will have to improve their scoring and analytics to help non-consumers succeed.
- The value of relationships – There is a major flaw in who Facebook thinks our friends are and who they really are. FB is going to have to fix or improve how they determine who our friends are or give us more control over what we see. I would like to see about 25% of my friends posts which is a far cry from the current 7%. When I don’t see enough of my friends on Facebook, I use it less, that’s already happening. There has been recent research on group dynamics and what makes a group successful and healthy.If Facebook starts to decrease the value and availability of reciprocity and transitivity, they’re in for a rough road ahead. Read the Science Magazine article on group formation and dynamics
- APIs, Content Producers, Advertisers versus Garbage – Facebook had to create a display algorithm simply because of the massive volume of content loaded to their site every day. Thanks to the FB API, those with enough knowledge or money can plug right into the FB system and feed all kinds of ads, posts, content and “crap” that most people could care less about. One of the biggest issues I have with the site is I don’t see everyone’s post but it would really annoy me if they went back to the old days where I actually saw everyone’s post. An algorithm can solve some of this problem but at some point they are going to have to decide, is sheer volume more important than the quality of content being posted. If quality matters, FB is going to have to lock down their API and find a way to filter out the garbage. Algorithms can fix some of this but some of it is their open API. Don’t get me wrong, I love their API but having one introduces gray-hat and black-hat authors as well.
- Sex appeal – I’ll admit it, when MySpace came back under Justin Timberlake, I logged back in and was impressed. Unfortunately the impression didn’t last when half of the cool featured didn’t work or there was nobody else on the site to connect with. Simplicity is what sold people on Facebook but simplicity also gets old fast. Facebook is going to have to make strategic, updates or improvements that are HOT. Major changes annoy people, it’s the subtle change that creates buzz, interest and excitement for the future. I’ve already talked about innovation which is important but so are the occasional graphic updates which give the site a pulse and sign of evolution.
Personally, I do think there will be an 80% decline by 2017 but it will be a decline of 15%-40%, not 80%. The range of 15-40 is large because their opportunity for risk is great, in such a competitive and finicky marketplace. I do feel Facebook could have an 80% or greater decline if they make a major mistake in their product road map or continue to have massive user information security issues. Losing their audiences trust, for whatever reason, could cause a mass-mutiny because there are, or will, be plenty of alternatives with strong product, security and feature offerings.
I’m sure after I post this there will be several additional suggestions on how to forecast and predict the future of social media. Personally, I love data and love to investigate how the world works based on that data but I also appreciate Warren Buffets test for determining the health and success of a company: is everyone using it and are they happy with it?