Website task completion: a linguistic approach?
(Originally featured @ Turn up the Silence)
In recent posts, we've touched on 5 reasons why task completion is the ultimate survey question, as well as discussing the visitor segments for whom task completion is the most potent predictor of visitor loyalty. But these posts were both predicated on the notion of a company/brand's attempt to measure the effectiveness of its online presence through an online survey. But what if a company wants to apply the logic of task completion to feedback that occurs organically (on the web or elsewhere), feedback that cannot easily be stuffed into the "yes/no" binary of a standard online survey question? I'm thinking tweets, blogs, forum posts, Facebook wall posts, and the like.
As it turns out, there may in fact be a useful linguistic approach to measuring task completion, also. An upcoming iPerceptions white paper will examine the open-text responses from thousands of online survey respondents who indicated that they did not complete their primary onsite tasks. One of the conclusions will be that there is a cyclical, staged logic to these pieces of verbatim commentary. These stages in the task completion journey can be described in terms of ways of speaking:
Intention -> Attempt -> Restriction -> Frustration -> Start again (hopefully!)
A real world example of this progression would sound like:
"I came to your website to book tickets (Intention). I tried using the booking engine (Attempt), but I got persistent error messages (Restriction). I was really upset and I'm disappointed in your website (Frustration). I'll try again later this week (Start again - you're lucky if you get this one!)."
As the white paper will show, these patterns repeat themselves across verbatim comments with a high degree of consistency. Perhaps this is a key, then, that will open up the ability to measure task completion outside the purview of online surveys--in places where open-text data occurs organically, places like social networks, user forums, call-center recordings, even buzz on the street.
Stay tuned for this upcoming white paper. The findings promise to be quite exciting!
In recent posts, we've touched on 5 reasons why task completion is the ultimate survey question, as well as discussing the visitor segments for whom task completion is the most potent predictor of visitor loyalty. But these posts were both predicated on the notion of a company/brand's attempt to measure the effectiveness of its online presence through an online survey. But what if a company wants to apply the logic of task completion to feedback that occurs organically (on the web or elsewhere), feedback that cannot easily be stuffed into the "yes/no" binary of a standard online survey question? I'm thinking tweets, blogs, forum posts, Facebook wall posts, and the like.
As it turns out, there may in fact be a useful linguistic approach to measuring task completion, also. An upcoming iPerceptions white paper will examine the open-text responses from thousands of online survey respondents who indicated that they did not complete their primary onsite tasks. One of the conclusions will be that there is a cyclical, staged logic to these pieces of verbatim commentary. These stages in the task completion journey can be described in terms of ways of speaking:
Intention -> Attempt -> Restriction -> Frustration -> Start again (hopefully!)
A real world example of this progression would sound like:
"I came to your website to book tickets (Intention). I tried using the booking engine (Attempt), but I got persistent error messages (Restriction). I was really upset and I'm disappointed in your website (Frustration). I'll try again later this week (Start again - you're lucky if you get this one!)."
As the white paper will show, these patterns repeat themselves across verbatim comments with a high degree of consistency. Perhaps this is a key, then, that will open up the ability to measure task completion outside the purview of online surveys--in places where open-text data occurs organically, places like social networks, user forums, call-center recordings, even buzz on the street.
Stay tuned for this upcoming white paper. The findings promise to be quite exciting!
Comment
© 2010 Created by Jonathan Levitt
You need to be a member of The 4Q Survey Community to add comments!
Join The 4Q Survey Community