Online intercept surveys are all over the place! Marketers are thriving on their customers’ feedback.  The feedback a survey provides is powerful. This type of data provides insight that digital metrics can’t. When surveys aren’t designed and executed correctly, it is common to find inconclusive results. That’s why it is important to avoid common pitfalls when developing a survey. The following best practices are critical to getting the most out of your next project that incorporates a survey.

Establishing Your Team:

Ensure your team consists of a project manager, account person, (market) researcher/strategist, an analytics team member and a technical developer.  It will be important to map out the project and develop the roles and responsibilities of the project.  Involve your analytics group at the onset of the project for their input in the survey reporting and analysis.

Establish Goals With Client or Other Key Stakeholder:

Your client’s or other stakeholder’s input is critical to the success of the project.  Work with them to understand their customers.  Request previous research studies and web metrics.  This information will aide in the survey development.

Visualize:

The key to a good survey is anticipating ahead of time how the data will be analyzed and reported. Think about how you want the survey captured for reporting.  Think of segments to report on.  Use this information to help develop your survey.

Develop a Solid Questionnaire:

There are several ways to develop a questionnaire, but there are common mistakes people make. Keep the survey questions to a minimum – This will help the response rate, reduce survey fatigue and straight lining answer choices.

Use skip logic whenever possible as it will keep the survey length to a minimum.  Skip logic is a way of following up to people who answered a certain way.  For example, say within your survey you would like to know if someone had a bad experience visiting your website.  If the person responded yes, then skip logic can be applied to present follow-up survey questions to only the people who responded yes.  Skip logic allows you to ask more questions to a particular group based.  It is a cleaner way of capturing data where follow-up questions are needed.

When doing scaled questions, use a Likert-type scale (1-5 answer choices).  Ensure the weighting of the scale is clear in the question.  Also, ensure there is a N/A option included.

Use an open end text box as a way to capture open ended feedback.  This is an area where an analyst can dive deeper for insights.

Make sure the questions are written so there is no room for interpretation.  Make sure the questions are current, relative and answer choices are available.

Avoid allowing users to select multiple answers. This should be avoided because it is harder to analyze and interpret the data.  If this type of answer choice is necessary, be certain the question is not the only way to segment on a critical group.

Understand the Importance of Your Sample Size:

Many forget the importance of having a solid sample size of survey responses.  You will want a sample size where you can provide segmentation and still have statistical significance.  As a very general rule of thumb, you typically do not want a sample size below 300.  If you run into a situation where you know you won’t get a sample size of 300, it is very important to warn your client or stakeholder the data will only be directional.

Engage Analytics:

It is crucial the analytics team is engaged at the beginning of the project.  Analytics should aide in the writing of the questionnaire, assist in determining the sample size, test the functionality and provide the analysis.

Understand Technical Implementation Process:

Your technical contact should have a good understanding of how to implement survey code.  The technical contact is responsible for dropping the survey code, testing the code and ensuring the survey execution is done correctly.

Following these guidelines and best practices will put you well on your way to delivering solid results and analysis.

Rachel Blair is a Senior Analyst, Marketing Intelligence at Organic