Chun-Yuen Teng and Lada A. Adamic from the School of Information at the University of Michigan have just published some interesting research on user retention in the virtual world Second Life ®.
The researchers observed that a high percentage (95.4%) of users who had made some financial investment in SL were likely to remain. From there, they set out to determine which factors were the best predictors of retention. The findings are quite interesting and I'll summarize, but please read the detailed report for the analysis.
Linden Lab provided the research team a dataset on user activity including snapshots of the social network, group affiliations, as well as summary interaction data such as first and most recent login, user-to-user transactions and pairwise chat frequencies. The researchers focused on the slice of data spanning May-June 2009 and evaluated four different facets of the user experience: usage (time spent), networking (number of contacts, groups and social cohesion), interactions (frequency and regularity), and financial transactions (selling and buying).
1) On Usage
The total length of time spent in SL was not a significant predictor, however the intensity (total time spent in world) was a strong predictor.
2) On Networking
While all parameters of networking (# friends, # active friends, % active friends, clustering, # groups, group overlaps) were highly correlated with retention, the number of raw contacts and groups, were key to identifying which users stay. The diversity of those contacts was a positive predictor but not a strong correlation.
3) On Interactions
For this I will quote directly from the report:
We observe that almost all chat parameters are more predictive that the static network measures above. Furthermore, one need not resort to complex metrics because the best predictions are also the simplest, e.g. the number of chat partners (not necessarily friends), or the number of days on which the user chatted.In other words, talking with people matters.
4) On Financial Transactions
Here, the researchers looked at data on purchases, sales, and transfer of goods as well as proximity within the social graph. The results indicated that while economic activity was correlated with retention, it was less so than chat. Spending money was more highly correlated than making money. Having a high proportion of free transactions was highly predictive. Profits did not improve the predictions of whether a user would stay. The amount of money paid to Linden Lab versus other users was only weakly predictive.
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