
Customer feedback loop: importance and how to create it
Customer feedback loop: importance and how to create it SHARE THE ARTICLE ON Table of Contents What is customer feedback loop? Customer feedback loop is
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We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
Steve Male
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Find the best survey software for you!
(Along with a checklist to compare platforms)
Take a peek at our powerful survey features to design surveys that scale discoveries.
Explore Voxco
Need to map Voxco’s features & offerings? We can help!
Find the best customer experience platform
Uncover customer pain points, analyze feedback and run successful CX programs with the best CX platform for your team.
We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
Steve Male
VP Innovation & Strategic Partnerships, The Logit Group
Explore Regional Offices
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You ever interact with a brand’s customer service for some reason and come across their customer support feedback survey asking questions like:
Q1. Our customer service agent had the necessary knowledge about your query.
In survey research, these types of questions are called agree/disagree survey questions, clearly named after the answer options they have. Agree disagree questions allow the respondents to select their level of agreement and disagreement to a stated opinion in the question. Generally, agree disagree questions have a range of answer options ranging from strongly agree to strongly disagree. So, the more detailed options you include, the more specific response you can get from the respondents about their feelings.
Although it looks like an easy question to frame and lay out, despite that, we will be discussing more about what tips and tricks you need to keep in mind while asking a disagreement question.
In 2010, Lietz put forth a study on questionnaire design issues, concluding that between a 5-option scale and a 7-option scale, 7-option scale is more reliable. The 7-option scale gives more options for the respondents to choose from.
Her study advised using “weekly agree and weekly disagree” to the previous answer options. In contrast to Lietz’s study, in 1971, Jacoby & Mattell suggested that 3-point scales are enough when it comes to gathering responses to close-ended questions. More options bring in more noise, hence making it difficult to make sense out of closely related answer options like “Somewhat agree” and” weekly agree” have a very thin line between them.
Studies have proved that, including a middle option like “Neither agree nor disagree” or “Neutral” attract 6-23% of respondents. The key concern with such middle options is that people tend to choose this option as a resort to just answer the question which will satisfy the researcher by limiting cognitive effort.
In 2010, Sturgis highlighted the real meaning behind “Neither agree nor disagree” can either be that the respondents “Don’t know” their opinion or they don’t have an opinion of agree or disagree. After researching the respondents who opted for “Neither agree or disagree” and asking them what exactly did they mean by that, the majority of them said that they did not have an opinion and “Don’t know” would have been a better categorization.
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People tend to choose the “agree” option because they think it makes them likable. When you look at a crowd, most of them prefer to have an opinion that will align with the majority, rather than having an opinion of their own. This can bring in bias in your responses.
Another challenge with agree disagree questions comes up when the researcher decides to compile all the small questions into a matrix of agree disagree questions. The main question will ask the respondents to rate the below statements based on their agreement or disagreement with them individually. Although, the grid design makes the respondents less aware of what they are selecting. This phenomenon is called straight-lining where the respondents move through the statement selecting the same answer options for all of them without giving it a thought.
Rating subject for every question depends on what you are asking for. Assume, you are asking for respondent’s satisfaction with customer service, the rating scale for the same would be “very satisfied, somewhat satisfied, neutral, somewhat unsatisfied, very unsatisfied”.
Another scenario can be where the researcher asks the respondents their opinion on the time spent by the healthcare provider with them. Where the respondents can choose answer options from “Too much time” to “Not enough time”
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