I’ve been re-reading Jakob Nielson’s Participation Inequality essay on useit.com, and the suggestion to some how show wear marks on content struck me this evening for some reason. I guess it’s because I’ve been working on Drupal recently, and discovered that Drupal documentation contains site recipies in the Drupal Handbook. What a nifty idea. Stick with me, these two concepts are related through a recipe and cookbook angle.
Part of Jakob’s treatise on inequal participation in online communities is that you can do little to overcome the typical contribution stats of 90-9-1, although one of the suggestions is to make participation so easy that you don’t even know you’re contributing. Case in point – Amazon’s “people who bought this book, bought these other books” recommendations. Sounds like the easiest contribution ever – data mining and analyzing, then giving the data back to the shopper in an understandable format.
Jakob says, “Will Hill coined the term read wear for this type of effect: the simple activity of reading (or using) something will “wear” it down and thus leave its marks — just like a cookbook will automatically fall open to the recipe you prepare the most.”
What are some similar examples of displaying read wear from the online help or user assistance world? The first example that comes to my mind is a wiki’s “most active pages” feature that shows the page with the most edits. However, the page with the most edits may be more controversial than truthful, so the most popular pages would be more useful than touting pages most active.
How else can you show read wear on a website? You could also show the most searched-for terms when the user searches. Concepts may be more easily connected when you understand what others were searching for.
Or, rather than showing search terms, show the most recently viewed knowledgebase articles or most popular articles. I know I’ve found that useful in the past when searching through BMC Software’s rich knowledge base.
Just like CNN and other news sites offer a listing of the most emailed stories per hour, you could show the most emailed online help topics if your system offers the ability to email topics.
The ability to rate an article is included in many online help systems, and exposing the ratings to the reader would help in determining how “well-worn” a help topic is.
Tag clouds can display read wear as well, as I just realized while looking at the WordPress FAQ starting page – tonight, the largest tag is “Images.”
I’ve distilled it down to popularity, time spent on the page, rating on a page, and number of edits from strongest to weakest indicators. What other factors matter in an online help system?