Fishing Where the Fish Are (with Your Influencers’ Help)
The Evolution of Online Communities
What is an online community?
As defined by its key elements — people interacting around common interests or shared goals and having that interaction supported by technology — online communities have existed for a long time. You could say they began in 1975 with listservs, which handled subscription requests to mailing lists and distributed new messages from the list's members to all subscribers. They continued to evolve with the appearance of bulletin board systems in 1978, and exploded in 1991 with the release by CERN (the European Organization for Nuclear Research) of the World Wide Web, which facilitated the development of online community groups supported by Web pages and communications software.
The early online communities supported by these technologies, however, continued to be relatively isolated from each other; even if the organizers wanted to allow users and content to flow from one to another, they faced a lot of friction — technical limitations that resulted in the development of very narrowly focused communities.
Within the context of these isolated online communities, we witnessed the development of the peer influencer. The metrics to identify this influencer were well defined and included aspects such as frequency, recency, and volume of participation; speed and tone of the responses generated; etc.
Today, we are witnessing a dramatic decrease in the friction that prevents users and content from flowing easily from one community to another. Efforts such as OAuth, Facebook Connect and Open Graph, Yahoo! Social Platform, and others reflect the fact that we will soon be able to count on an underlying social operating system that allows these niche communities to connect and contribute content and participants from one to another. In this new world, we need to rethink not only peer influencers and their behaviors, but also the metrics we can use to find and track them.
The Distributed Online Community
What is a distributed online community? As described above, online communities originally developed in isolation; not really by design, but due to the friction that was imposed by limitations in the technology.
Distributed online communities are about people interacting around common interests and supporting that interaction with technology that is available to them anywhere and at any time they choose; today, it is common to have an online conversation begin inside a brand-hosted community, spill over to Twitter, and continue onto Facebook - with the same or different individuals participating across all of these platforms at one time or another.
To identify peer influencers among the participants in these distributed online communities, we need new metrics. What's more, there are many different types of peer influencers; each of these types should be valued and leveraged on its own merits (more on this in the next section).
The Peer Influencer in the Era of Distributed Community
How do we recognize them? What are our influencer metrics in this new world? The metric set includes most of the same ones we have been using for some time now, but there are some extended aspects to them, and there are a few new ones.
Metrics to track peer influencers in distributed online communities (extended aspects and new metrics highlighted in bold):
- Frequency of participation: The user has participated x out of y days in the period under evaluation, for each of the relevant social network channels being monitored, and in total.
- Participation volume: The user has generated x level of volume of entries (participation) for each of the relevant social network channels being monitored, and in total.
- Speed and tone of the response generated: How quickly does the user participation generate other users' responses for each of the relevant social network channels being monitored? Are these responses negative, positive, or neutral?
- Number of new users generated: How many new participants has this user generated, for each of the relevant social network channels being monitored, and in total? (This assumes that there is a specific online destination where users can be brought.)
- Number of repeat users generated: How many repeat participants has this user generated, for each of the relevant social network channels being monitored, and in total? (This assumes that there is a specific online destination where users can be brought.)
- Impact endurance: The average period after a user participates that they continue to draw responses and new user acquisition.
Tracking and analyzing these metrics gives you the opportunity to identify different types of peer influencers across your user community. Here are a few typical patterns you can look for, and suggestions on how best to leverage each type:
What you can do with them
Users with a high frequency and volume of participation generating positive responses, high numbers of new participants and repeat users, and high impact endurance.
These are the users who can help you ‘fish where the fish are,' by helping communicate your messages in the right places and in the right context. Engage them and establish a relationship. Create programs to listen, communicate, and agree on what you can do for them and how they can help you.
Users with a low frequency and volume of participation generating positive responses, high numbers of new participants and repeat users, and high impact endurance.
These are potentially high-value peer influencers; reach out to them and bring them back. Devise programs to encourage them to increase the frequency of their participation and (as appropriate) bring them into the same programs as the influencers described above.
Users with a high frequency and volume of participation generating positive responses, low numbers of new participants and repeat users, and low impact endurance .
These are candidate peer moderators and keepers of your community at the different locations where they like to operate. Devise programs to thank and reward them, and recognize their activities.
This list is far from comprehensive, but it should provide some understanding of the power of these concepts.
- As online communities continue to evolve, we have the opportunity to employ new metrics that identify and engage key influencers among our user base in much more compelling ways. This enables more relevant and effective programs, but also requires more thinking and more resources.
- Review the systems and platforms you are using today. Do they allow you to track these important metrics? Make sure you are in a position to get the data that you need to run peer influencer programs.
- This article addresses the impact of the advent of distributed online communities, but these implications do not end there; consider the impact that location-based and real-time technologies are having and it becomes clear that these concepts will continue to evolve and expand.
As you go about identifying and engaging peer influencers remember these basics, from The Cluetrain Manifesto:
- Markets consist of human beings, not demographic sectors.
- Conversations among human beings sound human. They are conducted in a human voice.
- Whether delivering information, opinions, perspectives, dissenting arguments or humorous asides, the human voice is typically open, natural, uncontrived.
§ History and emergence of online communities (Jenny Preece, Diane Maloney-Krichmar, Chadia Abras) http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118.244&rep=rep1&type=pdf
§ The Cluetrain Manifesto (Levine, Locke, Searls & Weinberger. ): http://www.cluetrain.com/
§ CBBS, Wikipedia: http://en.wikipedia.org/wiki/CBBS
§ Spotting the Creators of Peer Influence, Josh Bernoff: http://adage.com/digitalnext/article?article_id=143372
 We define "peer influencer" as a person with no specific differentiating characteristic from the rest of the community except the demonstrated ability to galvanize and sway the attention and action of others in her community.
 OAuth: An open protocol to allow secure user authorization, supported by Twitter, Facebook, and many others.
About the Author
Filiberto Selvas (firstname.lastname@example.org) is the product director at Crowd Factory (www.crowdfactory.com). His personal blog can be found at http://www.socialCRM.net.
Please note that the Viewpoints listed in CRM magazine and appearing on destinationCRM.com represent the perspective of the authors, and not necessarily those of the magazine or its editors.
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For the rest of the June 2010 issue of CRM magazine — our second annual Social Media Issue, this year focused on communities — please click here.
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