A recent piece in The Economist raises a provocative question: social networking sites such as Facebook, MySpace, and Bebo have grown tremendously in usage, but are they viable businesses? In other words, is it possible to monetize these services in an effective fashion? To answer this question, it helps to take a step back and look at the monetizability of social media as a whole.
Since most social media sites rely on advertising revenues, let us restrict ourselves to advertising as the monetization mechanism. Regardless of the model (CPM, CPC, CPA), advertisers value three key measures: reach, frequency, and targeting. Many social media sites certainly score high on reach and frequency, but how do they fare on targeting? Targeting is key, because it determines the CPM rates advertisers are willing to pay. And CPM rates vary very widely: from $16-20 for TripAdvisor to $0.10 for Facebook and MySpace. See, for example, this media plan.
What drives such a wide divergence in CPM rates among social media sites? Are the low rates at social networking sites a transient aberration, with higher rates around the corner as advertisers get more comfortable with the medium? And is there a simple model to predict the targetability of different forms of social media?
Remarkably, there appears to be a single factor that explains a great deal of the available data. Consider the difference between a Facebook profile and a TripAdvisor travel review. A typical pageview on the former is by someone known very well to the creator of the profile – a close friend or acquaintance. On the other hand, a TripAdvisor travel review is seen by people completely unrelated in any way to the person or persons who wrote the reviews on the page.
We quantify this distinction with a measure called affinity. The “affinity” of a social media service is the average closeness of relationship between a content creator and someone who views that content. The affinity of Facebook is very high, while the affinity of TripAdvisor is very low.
Here’s the key observation: There is an inverse relationship between the affinity of a social media service and its targetability. Why is this true? The act of viewing a Facebook profile gives us very little information about the viewer, other than the fact that she is friends with the profile creator; when someone views a TripAdvisor travel review, she is definitely interested in traveling to that location.
I estimated the affinity of several forms of social media, and plotted affinity aginst CPM (which I used as a proxy for targetability). The resulting graph (click for a larger image) shows the landscape of Affinity versus Targetability for several forms of social media. Some of these data points are from published data and others are extrapolated. We can see that there is a strong inverse proportionality, with a couple of outliers. We’ll get to the outliers in a moment; for now, note that Social Networks and Photo Sharing sites are even higher affinity (and therefore lower targetability) than email. This is because we often email people we don’t know or know only in passing. Instant messaging has the very highest of affinities: my IM buddy list includes only my very closest friends, who I trust with the ability to interrupt me any time of the day.
What about the outliers? Video sharing sites, such as YouTube, have low affinity, because the majority of people see videos posted by people they don’t know. However, the targetability is lower than we would expect, because of a compensating factor: herding. Most people see videos featured on lists such as “Most Popular”, which reduces the targeting value of such videos. This is also true of social news sites such as Digg.
A couple of caveats:
- This is a broad brush-stroke, and individual services might well differ from the overall category. For example, popular blogs have much lower affinity and therefore much higher CPMs than the typical blog.
- Targetability is not the only factor determining CPM; there are others. For example, certain viewer intents are inherently more valuable than others.
But with these caveats, this simple model is highly instructive. We may conclude that, when all the dust settles, the CPM rates of instant messaging services will not exceed those of social networks, which will not exceed those of email. These are inherently low CPM businesses.
What can social media sites do to increase their CPMs? There appear to be two options:
- Create sections of the network that are more topic-oriented, and less about individuals. For example, band pages and groups on MySpace, and Facebook groups.
- Mine individuals’ profiles, or their off-site behaviors, to target them behaviorally rather than contextually. This approach carries with it dangers of privacy violations, as the Facebook Beacon fiasco demonstrates.
If social networks are to become a viable business, they need to pursue aggressively one or both of these approaches. Of course, it may be possible for some services to sidestep this question entirely and develop business models that don’t depend on advertising. We haven’t seen such a model emerge yet, but there is so much creativity and ferment in this space that it might just happen.
Update: I received some questions about the affinity versus targetability landscape. Here's a brief description of the methodology. I used published CPM numbers where they were available; e.g., Yahoo Mail ($3-4), TripAdvisor ($16), Facebook ($0.10-0.15). Note that published CPMs are generally to be taken with a pinch of salt, since they may apply only to small portions of the overall publisher inventory and not represent real market-clearing prices e.g., Google's stated goal of $20 CPM for YouTube -- only a very small number of YouTube videos show ads today. I've used Metacafe's $5 net CPM payout to video producers as a more reasonable benchmark -- this likely represents a gross CPM of $10 assuming a 50% rev share. For blogs, the numbers are all over the place: BlogAds ratecards for various blogs vary from $1-$4CPM, Valleywag reports $6.50-$9.75, and Federated Media has ratecards charging $7-$40. I took $10 to be a median for blogs with reasonably high traffic. Some of the other data points are based on guesses and informal conversations, since these sites typically don't publish their CPMs. Please email me if you have additional data on these; I will update the graph accordingly.