Common Marketing Research Survey Errors

Surveys and polls are two little tools that are widely used and often incorrectly. They’re tools that look easy enough to create and, after all, with apps like Survey Monkey, Zoomerang and others widely available they are vastly easier to prepare than in days gone by.

Yet, despite the ease and availability of tools to help in the process, far too many surveys and polls contain very easy to avoid errors that can cause the results attained to be of questionable value. I work with both students and clients on the development and use of marketing research instruments, and I often review and provide feedback on survey instruments. Some of the most common errors I see include:

  • Not having a very clear idea at the outset of what your marketing research objectives are — e.g. what is it, specifically, that you need to know and how will you use that information in some meaningful way?
  • Not having a very clear idea of who you need to gather information from. Seems basic, but I’ve seen many instances where companies will point to research based on customer feedback to support their belief that they are the “preferred choice.” But there’s a key audience whose input might provide a different perspective–non-customers!
  • Using qualitative inputs to make major decisions. Focus groups are a commonly used tool to gather input and can be very effective. They do not provide statistically valid input, though, and the results should never be used to make decisions that represent either potentially high risk or potentially high reward.
  • Believing that you are conducting a random sample when you are not. A true random sample requires that you can literally create a list of every member of your population of interest and select randomly from the members of that list. While this could, conceivably be done with your customers, for instance, it probably can not be done with all members of a service area that might be interested in your services. Not all surveys are based on a random sample and that’s okay — but it’s important to know the difference when analyzing and acting on results. Again, when making major decisions, you want valid, reliable data to boost the odds that your decisions will be sound.
  • Poor survey organization and display. A survey is a communication tool. As with any communication, it’s very important to think of your audience and how you can most effectively engage them in the survey. This may involve everything from getting them to open your email (many surveys are sent online these days) through the use of a compelling subject line and clear, concise indication of what the survey is about, why you are sending it to them and how you will use the information. And that’s just the beginning! The survey itself should be well organizations, starting with broad, general questions and moving into more detailed questions that require more thought and ending with demographic questions (about age, sex, income, etc.). In addition, the length and look of the survey should also be considered — again, you’re hoping to connect and engage with respondents so they open and complete your survey.
  • Using the wrong kind of scales on the survey. Those with little experience have a tendency to use what are called “nominal scales” — basically just checkboxes that people would mark, rather than scales that allow respondents to rate or rank their responses, providing the ability to do higher-level analysis on the results.
  • Asking “double-barreled” questions — any question that is asking about two different things. For instance: “Indicate to what extent you feel our services are of high quality and are reasonably priced.”
  • Not sharing the results of the survey with those you sought input from. This is commonly done and can lead to decreased response over time.

These are just a few of the many potential pitfalls you may run into when attempting to gather useful input that you will rely on to make decisions that impact your business. Minimizing errors can help to maximize the ability to rely on the data you receive to make sound decisions.

As with many business endeavors, conducting effective research is often not as easy as it looks!

 

 

 

 

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