Strategies for online communities

How can companies interact successfully with consumers in online communities?

For a lot of people, if not all of us, our opinion depends on those in our social context. Whether unconsciously or not, we want our choices to reflect who we are and that we belong in a certain community with similar interests, preferences and beliefs (Churchill and Halverson, 2005; Miller, Fabian, and Lin, 2009; Swann, Rentfrow, and Guinn, 2002). Online communities are not necessarily different. Even though it can be anonymous and it is more accessible than face-to-face meetings, the opinions posted there can be equally or even more influential in the choices that you make. And people are spending an increasing amount of time online, so a lot of the opinions that our opinion is based on, are coming from online communities.

This also increases the interest from companies, because while it was hard to engage in the face-to-face and physical word-of-mouth exchanging opinions about your products or services, it is relatively easy to engage in an online discussion. Maybe not even to check out the opinions that there are, but being actively involved and promoting your product in order to achieve increased sales.

That is what the article by Miller, Fabian and Lin (2009) is about, how can companies shape their strategies to consequently increase the demand for their product, within online communities. They evaluate three strategies, namely; support the weak, support the strong, and uniform strategy (Miller, Fabian, and Lin, 2000). Respectively, they refer to allocating advocates in the online communities based on the amount of unfavorable postings, favorable postings, or to community size.

So what should companies base their decision for a strategy on? Choosing a strategy depends on the switching assumption. The switching assumption refers to the behavior of people within that online community, who generally switch because of one of these two reasons: random, or because the preferences in another community are more aligned. Furthermore, there could occur no switching when loyalty or switching costs are high (Miller, Fabian, and Lin, 2009). Switching is important, as it enables the flow of values and beliefs between communities (Miller, Fabian, and Lin, 2009).

So the recommendation of the article is for companies to assume one of the three possible switching behavior groups, and consequently develop their strategy. In addition, a company’s strategy should favor those communities that 1) have many undecided members, 2) low posting rates, allowing for high visibility and a broad influence (Miller, Fabian, and Lin, 2009).

Another interesting research area would be Instagram as a social community specifically, and to study how companies are positioning themselves within these different communities by providing the influential people with free stuff and paying them to post something about it, or even only post a picture with the product. Whilst the pricing of this seems a bit of a black box, there are already unofficial calculators online that calculate based on the amount of followers and the level of engagement. I believe it would be interesting to study this from an academic perspective and consequently provide managerial recommendations.

Churchill, E.F. and Halverson, C.A., 2005. Social Networks and social networking. IEEE Internet Computing, 9(5), pp. 14-19.

Miller, K.D., Fabian, F. and Lin, S.J., 2009. Strategies for online communities. Strategic Management Journal, 30(3), pp. 305-322.

Swann, W.B., Rentfrow, P.J., and Guinn, J.S., 2002. Self-verification: the search for coherence. In Handbook of Self and Identity, Leary M., Tagney, J.P. (eds), pp. 367-383. Guilford: New York.

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