Question

Topic: Research/Metrics

Customer Loyalty Index From Survey Questions

Posted by Anonymous on 1/16/2006 at 1:43 AM ET 25 Points
Dear Experts.

As I know from my humble experience that if I would like to calculate customer loyalty index from survey questions all the questions should has the same scale e.g. Very Satisfied, Satisfied, somewhat satisfied, Dissatisfied, very dissatisfied.
Now most of questioner questions has the scale above.
The problem is, I would like to add the three questions beneath in the questioner and I think the scale above is wrong for using with the questions below. what is the egression?
1. How likely are you to buy from us again?
2. How likely are you to recommend our service to a friend (or colleague)?
3. How likely are you to recommend our company to others?

Please advice and hope I was clear enough.

Thanks.
Oamr.
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RESPONSES

  • Posted by darcy.moen on 1/16/2006 at 2:28 AM Member
    Why? Information is information. Sure, its nice to be statistically valid, but business is not always an exact science.

    Are you doing more than 300 surveys? If not, do what you need to do to get as much information as you need. You can base your decisions from a handful of responses if need be.

    Sometimes half the battle is to know when you are chasing too much information.
  • Posted on 1/16/2006 at 8:00 PM Member
    You might want to check out a white paper entitled Customer Care Cube (C3)TM A Customer Satisfaction and Retention Methodology on my website at https://www.marketware.biz/white_papers.htm . It seeks to address some of the issues you raise and calculates a Customer Satisfaction Index (CSI).

    Let me know what you think.

    Regards

    Pat Divilly
  • Posted on 1/18/2006 at 2:00 PM Member
    Hi,
    I think you can assign to these 3 questions values like these:

    - not likely at all
    - quite likely
    - I will do it for sure


    And you even can use weight index to attribute required importance to these questions.
    The main thing here is for your questions to fit properly among the other ones and to be weighed correctly.


    Good luck!


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