Continuing our series about lurker behaviors we now look at the next behavior cited in the IBM study: browsing lists and collections of files or viewing the contents of a single collection. The study concluded that users who engage in this factor are focusing on collections of files as a means of finding their desired information (thanks Captain Obvious), but we will call this type of behavior “window shopping” and see if we can devise some ways of creating deeper engagement from this behavior.
The user who is going to window shop in your community is either looking for something specific or just wants to see what’s there. Much like real world shopping, if the user finds something of interest they will want to know more about it; pick it up, look at the price tag, and perhaps ask a sales clerk. In the online world this translates to marking a collection or file as a “favorite,” giving it a rating or a “like,” and perhaps downloading it. These are all behaviors that community management should be able to track and follow up on.
Depending on the size of your community it may be impossible to follow up on every member who downloads something, but for larger communities you want to look at files that get the most downloads and ask yourself these three questions:
- Was there something about the content itself that had a wide appeal or lent itself to high download activity? – this could be a piece written by an influencer, hot topic, or something free that is usually offered at a price
- Is there a similarity in the types of users that downloaded the file? – all from a similar profession or role in a profession, region, or other demographic
- Is there a trend in the downloading? – all at one time, spread out over time, viral hits, etc.
With this information, you can then look to encouraging the posting of similar content in the future (if the file was user generated rather than community management generated). Honing in on what your community wants is something you can do within this lurker behavior. Also, if you can pinpoint individual users who browsed these collections (usually counted as “page views” in an analytic tool), you may be able to follow up with direct outreach too. My suggestion though is to start with the numbers, encourage more content along the lines of what is getting the most eyeballs, and then follow up with more analysis.
