Multichannel Forensics For Social Networks

99% of the time, the Multichannel Forensics examples I offer are related to what you might loosely call "retail" --- physical stores, online businesses, catalog brands.

When we deal with retail, we deal with long periods of time. We measure repurchase rates over the course of a year, or in some brands, four or five years.

In subscription-based businesses, we often convert churn rates into the Multichannel Forensics framework --- a 4% monthly churn rate yields a 60% percent annual retention rate, while a 7% monthly churn rate generates a 40% annual retention rate.

But what about something like Facebook, an application where half of users visit every single day?

Social Networks are best measured on a daily or weekly basis. All the laws of Multichannel Forensics still apply, but the timeframe is seriously compressed.

This becomes important for the Social Network, because you can quickly identify the amount of time that passes before the "user" is about to defect --- you can build "KPIs" around a "time to defection" metric generated by the Multichannel Forensics framework.

Also important is the type of activity the user participates in --- you want to measure which activities are in "Equilibrium Mode" or "Transfer Mode" with each other. For instance, are a ton of folks in Friendfeed following Robert Scoble, only to slowly defect to another social media evangelist? If this happens, you'll notice because Robert Scoble is a "micro-channel" that is transferring users to a new individual. You'll be able to react to the fluid dynamics within your social network.

So, what are the key takeaways?

1. For most social networks, reduce the timeframe to a daily (Facebook, Twitter) timeframe, or a weekly timeframe, measuring retention and user acquisition over short intervals.
   
2. The definition of a "channel" changes. Micro-channels in a social networking framework include various activities (e-mail, search), widgets, or even key individuals (Robert Scoble) that attract or cultivate users.
3. These activities can be simulated over time, to understand the long-term trajectory of your social network.