Key Aspects of Survey Coding

Here are the key terms and techniques you’ll encounter when coding surveys:

1. Open-Ended Responses: These are the text-based answers or comments that participants write in their own words. Also referred to as “customer verbatim” or “verbatim comments”.
2. Thematic analysis: Responses are grouped into themes or categories, called “codes”, based on their content and meaning. For example, “The customer service rep I spoke to was helpful” may be tagged with the code “Good Customer Service”.
3. Verbatim coding: Mapping each response to one or more categories or codes using a table (In Excel or a dedicated verbatim coding software), each category or code is assigned a numerical value to help with statistical analysis.
4. Codebooks: A codebook is a detailed document that outlines the rules, categories, and codes used for analyzing and organizing the survey responses. It serves as a reference to ensure consistency and accuracy in the data coding and analysis process and helps keep analysis consistent to track changes over time.
5. Sentiment analysis: Sentiment analysis identifies the emotional tone of responses (positive, negative, or neutral) to gauge customer satisfaction and uncover key insights. It can be done manually or through AI-powered tools that analyze text at the document, sentence, or aspect level for actionable feedback.
6. Manual vs Automated Coding:
   
   • Manual Coding: Analysts read responses and assign codes based on predefined categories or emergent themes, manually, one at a time.
   • Automated Coding: Text analysis tools like Blix use AI to assign codes automatically, removing the grunt work of manual coding and allowing you to create actionable insights quickly & easily.
     ‍

Benefits Of Survey Coding

Survey coding offers a powerful way to transform unstructured data, such as open-ended responses, into structured formats that can be turned into actionable insights. 

By categorizing qualitative feedback, survey coding allows researchers to identify trends and recurring themes, providing a deeper understanding of customer sentiments and preferences. These insights are crucial for supporting data-driven decision-making and guiding strategies for product development, marketing, and overall business improvements. 

Through this process, businesses can uncover valuable patterns in the data, enabling them to make informed choices and stay aligned with market needs.
‍

4 Steps to Code Your Survey

There are four steps to survey coding:

1. Prepare your data for coding
2. Identify common themes
3. Assign codes
4. Extract insights

To help you better understand the process, we will walk you through it with an example. Dark Essence, a perfume company with a Batman-inspired scent, asked the following questions:

1. Why do you like the Batman perfume?
2. What is your favorite Batman character?

Step 1: Prepare Your Survey Data for Coding

Before you begin coding, ensure your survey data is ready for analysis. This includes:

• Gather the Data in a Spreadsheet: If it’s not already, organize your data into a spreadsheet with clear column headings.
• Clean the Data: Remove duplicate responses, incomplete entries, or irrelevant data. 
• Understand the Context: Familiarize yourself with the survey questions and objectives to guide your coding process.

Here is the spreadsheet of data we will be using in our Batman perfume example:

Step 2: Identify Common Themes or Categories

Review the survey responses to find recurring themes or patterns. This involves:

• Read Through the Responses: Skim the data to get a sense of common topics.
• Group Similar Ideas: Cluster responses with similar meanings or themes together.
• Create Categories, AKA ‘Codes’: Define broad themes or categories (these will be your codes) that represent the content of the responses, such as "Customer Service" or "Product Usability."
• Create Your Codebook: Put all of your codes and their assigned numerical values into a codebook. This can be created using a spreadsheet, or done automatically with Blix.

For our example, we created the following codebook for the responses to the Batman perfume survey:

Step 3: Assign Codes to Responses

Assign codes from your codebook to each survey response, one line at a time.

Here is a sample of the codes we assigned to the responses for the Batman perfume survey:

This is a tedious and time-consuming process, but it is the bulk of the work of survey coding. If you want to save a lot of time, consider using Blix to automatically assign the codes for you at the press of a button.

Step 4: Analyze the Coded Data for Insights

Now that your survey data has been coded, it’s time to extract meaningful insights. This is where the true value of coding comes to light, as it allows you to understand patterns, trends, and key takeaways from your data. Here’s how to do it:

1. Quantify Your Data: Count the frequency of each code in your dataset. This will show you which themes or categories are most prevalent among your respondents. For example, if many responses mention "unique scent," you can identify it as a key selling point of the Batman perfume.
2. Identify Relationships: Look for correlations between different codes. For instance, if respondents who love the scent also frequently mention their favorite character is Batman, it suggests a connection between brand affinity and product appeal.
3. Highlight Trends: Examine changes in responses over time or by different demographics. For example, if younger respondents are more likely to mention "modern vibe," it may indicate a generational preference that can guide marketing strategies.
4. Summarize Key Findings: Create a report summarizing the main insights from the data. Highlight areas of strength, like the perfume’s "bold and mysterious scent," and areas for improvement, such as respondents mentioning "too expensive."
5. Visualize Your Data: Use charts, graphs, or word clouds to present your insights in a clear and engaging way. For example, a bar graph could show the most frequently mentioned themes, while a pie chart could display the distribution of favorite characters.

By analyzing your coded survey data, you can gain actionable insights that inform your business decisions. In our Batman perfume example, Dark Essence might discover that most customers love the "Bold and unique scent" because it reminds them of Batman’s persona. They could use this information to refine their marketing campaigns and product development.

Here’s a chart showing the distributions of how often each code appeared in the perfume survey, created by Blix: 

11 Survey Coding Best Practices

While learning the survey coding process, here are some best practices to keep in mind to help you avoid unnecessary extra work and make survey analysis more accurate and useful:

1. Define Clear Objectives

• Understand the purpose of the survey and what you want to achieve with the coding.
• Align coding categories with your research questions or business goals.

2. Develop a Comprehensive Codebook

• Create a detailed codebook with clear definitions, examples, and rules for each code.
• Include instructions on how to handle ambiguous or complex responses.
• Update the codebook as needed to reflect emerging themes.

3. Familiarize Yourself with the Data

• Read through all responses before starting to code to gain a holistic understanding.
• Take notes on recurring themes, outliers, or unique responses that might need special attention.

4. Use a Combination of Predefined and Emergent Codes

• Start with a set of predefined codes based on your survey design or hypotheses.
• Be open to adding new codes as themes emerge during analysis.

5. Ensure Consistency in Coding

• Apply the same rules and logic to all responses to maintain uniformity.
• If multiple coders are involved, conduct training sessions to ensure everyone understands and applies the codes consistently.

6. Start Broad, Then Refine

• Begin with broad categories and progressively narrow them as patterns and nuances emerge.
• Avoid over-coding (too specific) or under-coding (too vague).

7. Use Coding Software When Necessary

• For large datasets, use a tool like Blix to streamline the process and reduce manual effort.

8. Document the Process

• Keep detailed records of the coding framework, adjustments made, and reasons for changes.
• This transparency ensures reproducibility and allows others to understand the methodology.

9. Validate and Refine the Coding

• Periodically review coded data to check for consistency and accuracy.
• Adjust codes or the codebook if new insights or recurring issues arise.

10. Balance Automation with Human Judgment

• Use automated coding tools cautiously, as they may lack the full context that you have as a researcher.
• Combine software efficiency with human insight for the best results.

11. Summarize and Analyze Thoughtfully

• Focus on interpreting the patterns and trends revealed by the coding process.
• Include quotes or examples to add depth and context to your findings.