Turn Survey Responses into Customer Insights: A Step-by-Step Guide

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Determining the right survey questions and reaching the right people can be the most challenging part of the process. However, once you receive the responses, a new phase of work begins. To effectively turn survey responses into customer insights, you’ll need to follow these four steps to create useful, actionable reports that transform your data into insightful information that’s easy to present:

Clean Data
Run Initial Reports
Analyze Data
Create Final Report(s)

The Importance of Clean Data for Quality Survey Responses

When you have reliable data you can be confident that you’re building decisions on a solid foundation. For optimum reliability, you need to clean your survey response data to identify outliers before you start analyzing it.

This process helps ensure that all your data is relevant. It also verifies that the data comes from real individuals who were engaged in the survey.

Survey Response Data Warning Signs

Here are the top five warning signs to be on the lookout for when reviewing your survey responses:

Suspicious Answer Patterns: These responses, sometimes called “Christmas Tree” or “straightlining,” follow a very clear pattern. They do not reflect thoughtful or accurate answers.
Very Fast Completion Times: Know your average survey completion time. Be suspicious of responses that come in significantly faster than this average.
Choosing All Checkbox Options: Whenever someone picks all the checkbox options consistently it’s often a sign that they’re just speeding through the survey without reading all the choices. Typically, you should throw out these responses from your data set.
Red Herring Fails/Logically Inconsistent Answers: Particularly on longer surveys, include a few roadblocks that will throw up red flags. This will help identify poor quality survey responses. Something like, “Please check the box next to the word, ‘red’ below” and then a list of several colors will help you find out who’s really reading your questions.
Nonsense or Missing Open-ended Answers: Examining text box entries quickly reveals which responses are valuable and which should be excluded.

Preparing Your Survey Response Data For Analysis

Now that your data is clean, it’s time to prep for analysis. Hopefully you identified any inconsistencies in response options during the testing and validation phase. If not, keep an eye out for inconsistent numerical values and any breaks in validation that arise.

Whatever problems you find, be sure that you don’t introduce a new source of bias by changing the question text AFTER you’ve collected responses.

Analyzing Qualitative Survey Response Data

As you may remember, qualitative questions allow respondents to type in their own answers. They offer great insight into the “why” behind your survey questions, but they can be challenging to analyze.

Prepare options for how you’ll derive conclusions with qualitative data from open text or essay questions.

Some good choices are:

Track keyword frequency to see how often your respondents use particular terms.
Word clouds, a handy visualization of the words based on how commonly they appear in answers. The more a word appeared in your survey responses the larger it is.
Rate each response as positive or negative based on the emotional words used.
Bucket responses with an open text analysis tool. This software feature will let you categorize responses when they use a certain term or phrase.

Remember your survey learning objectives? Now’s the time to pull them back out again.

You’ll want to run an individual report for each learning objective in order to determine the “highlights” of the data you collected as it relates to future actions.

This approach helps you understand the most significant findings of your research. It also shows you how to turn survey responses into actionable customer insights.

Based on each report, determine what actions you’ll be recommending for each learning objective.

Run Preliminary Reports on Your Survey Response Data

Once you’ve cleaned your data and refreshed yourself on your survey goals, it’s time to do a first pass at creating your reports.

These initial reports help you determine:

If you answered your original questions.
If the data matches the format you expected.
Whether you’re seeing the expected trends and extracting meaningful insights on your customers.

Data Types to Consider

Depending on the purpose of your survey, you may collect demographic details about your respondents, firmographic data, or both.

Demographic data, such as age or income, represent the statistical characteristics of human populations and help identify markets.

Firmographic data, such as a company’s size or location, represent the characteristics of an organization. This type of data is used almost exclusively in business-to-business research.

Often your survey will contain demographic and firmographic questions so you can create segments in your survey and reports.

These segments can give you great insight into relationships among your responses. They should remain the same from start to finish of the survey process.

Is There a Trend in Your Survey Response Data?

When you have data that isn’t statistically sound but is still interesting, you can call it “directional data.”

This data gives you an idea of what your population is saying, thinking, or feeling. However, you cannot use statistics to back it up.

Analyzing Your Survey Response Data: Ratios

If you collected too many responses from a certain segment of the population, sometimes you will need to adjust the weight of your responses in order to keep it true to outside ratios.

For example, if the population of the US is 52% women but your respondents were 54% male, you’ll need to make some adjustments if you want your results to accurately reflect the real ratios of the US population.

Report on Your Survey Response Data Findings

There are four stages of the reporting process, during which you reveal the brilliant findings of your well-designed survey to the world.

Stage 1: Write a summary
Stage 2: Write a mini-report for each individual learning objective
Stage 3: Reveal interesting and unexpected trends
Stage 4: Conclusion

Stage 1: Write a Summary

In this section, recap the information you gathered while defining your survey goals and objectives. Also, review the criteria you used to select your respondents.

Use this section to clarify any confusion about your data collection method. Explain why you chose this particular method.

Be sure to include these points:

What was the ultimate goal of this survey?
Who was surveyed?
Who was the population?
Who responded?
Include basic highlights of the survey audience and your data to introduce the findings and how they contribute to customer insights.

Stage 2: Write Mini Reports

Each learning objective gets its own mini report so you can specifically address the goals and outcomes for each one.

The final section of each learning objective report should outline the recommended actions based on the survey results. These recommendations should not come as a surprise.

Stage 3: Interesting and Unexpected Findings

While optional, this stage can lay the groundwork for future projects and reveal things about your audience that you weren’t specifically investigating.

For example, maybe you found a new segment of your population that could help you to make good business decisions going forward.

This section is:

Good- to-know, not need-to-know
Going the extra mile!

Stage 4: Conclusion

This is the big finish of your report! Recap the actions that you recommend the team take based on your survey’s findings, and include as much supporting evidence as you need to in order to get stakeholders to agree to those actions.

Create a survey for stakeholders to gain feedback on the project and initiate actions. To take meaningful action, ask stakeholders for metrics that will measure the success of these actions.