One of the problems with collecting good data is that customers (and all respondents, really) are prone to not answering with the utmost honesty. Indeed, even if the person thinks they are being honest, things like disinterest, being in a rush, etc., can all cause the individual to choose answers that may not be exactly what they would choose had they taken the time to truly think about it.
It is expected in a large enough sample that these problems will even out, but they are no less misleading when you receive the final number. Another problem, however, and one that can badly affect your data, is the idea of Central Tendency Bias.
What is Central Tendency Bias?
Central tendency bias in survey research occurs when customers become less willing or unwilling to answer with extreme responses, choosing to answer using more towards the middle, even in the event that they would normally be passionate about a particular answer. For example, rather than selecting “Very Satisfied” or “Not at All Satisfied,” they may choose just “satisfied” even if their true feelings should have been more towards the extreme end.
This effect can bias your data, because when someone has an extreme response, but is unwilling to give it the extreme ranking, they end up giving it the same response as something they are much less passionate about.
What Causes Central Tendency Bias?
Central tendency bias occurs most often when a customer is going through multiple items in a survey with the same answer, especially in table form, where all of the answers are compared to each other. The customer may decide, for various reasons, that they are no longer willing to give out extreme responses, and ultimately choose the responses closest to the center.
There are many people that lose interest/passion after filling out multiple items in the same survey with the same answers, and even fewer that are willing to give extreme responses when so many items are provided to them for comparison.
Effects of Central Tendency Bias
Central tendency bias causes your survey responses to blend together in such a way that you lose some of the value of your data. It’s much harder to figure out the actual feelings of your customers when their answers are closer to the center, because the difference between answers becomes much smaller. It’s important that you shorten your survey and look for ways to reduce central tendency bias so that your data is as useful as possible.