Localized Survey Scales

Design of interval scales for surveys is a vital part of survey questionnaire design. How many points on the scale, odd number or even number, presenting the scale from high to low versus low to high, endpoint anchoring or fully anchoring each scale point are all design issues. Most important is the choice of anchors, which are those terms that describe the dimension of measurement. Importantly, a scale designed for American English audiences must be localized for other variations of the mother tongue.

We practice scale design in my survey workshops, and in a recent workshop, one attendee decided to create a localize scale for measuring relevancy, in this case for Texas: (my apologies in advance for offending anyone’s sensitivities.)

localized-survey-scales-Texas

I leave it to you to add in the proper Texan accent!

A Minnesotan colleague has submitted these for the quality of service dimension:

localized-survey-scales-Minnesota

A Massachusetts friend added these:

localized-survey-scales-Massachusetts

For non-Bostonians, “Stahted” translates to “Started”.

Have one to submit? Contact us!

Survey Scale Design: The Impact on Performance Measurement Systems

The choice of a survey scale impacts setting performance goals. Scale choice and question wording will affect the way people respond. The article also discusses why (artificially) high scores are not necessarily good — if your goal is to use the survey results for continuous improvement projects, requiring Pareto Analysis.

The Importance of Measuring Importance — Correctly — on Customer Surveys

Frequently, when business surveys try to measure importance of various factors the survey generates useless data. Everything gets rated as important, so nothing is important. This article covers methods of measuring importance showing the advantages and disadvantages of each. The key is getting the respondent to think about the trade-offs across the factors.