It’s an honor to have your comments. Thanks.

The ‘recommend questions’ (have you, will you) would be scored/valued as follows:

Will you recommend in the future:
Definitely 10
Probably 8
Might or Might Not 5
Probably Not 2
Definitely Not 0

Have you recommended in the past:
Yes, without being asked 10
Yes, after being asked 8
No 0

These scores would also baked into a respondent’s ‘total score’ for the entire question set. It’s also used to comprise combined scores for a number of cross tabs we do. For example:

1-10 scores for Data Value (ROI)
frequency of use
+ length of use
+ would you recommend
+ have you recommended
= sum (sort of a panoramic “Uber-NetPromoter” scores that can be parsed to see if longer term or frequent users are responding much differently than new customer)

I’ll talk about my ideas about trying to profile personality types in future a post. This is where scoring of other types of engagement behaviors (other than survey, e.g. SLA report card meetings, social computing mix, etc.) comes into play.

Thanks!

Our research has shown that even those that are classified as “Promoters” 9-10, not everyone actually refers. This is due to many factors including personality and brand category. In the credit card industry we found that 53% of Promoters actually referred and in the Computer Hardware industry 78% of Promoters actually referred.

If you are interested in more information on our research in this area and how to build an economic model for Net Promoter, you can download white papers at: http://satmetrix.com/satmetrix/resources.php?page=4.

It may be interesting to evaluate whether your 19% of customers that have not referred are classified as Promoters on the 0-10 scale and if they have the personality to recommend without being asked.

In any case, looks like you are doing something right if 73% of your customers report that they have actually recommended and 92% would recommend if asked! That’s good word of mouth.

Deb Eastman
CMO, Satmetrix