How To Code Open-Ended Questions In Excel

Methods for Coding Open-Ended Data

Analyzing open-ended responses is essential for uncovering deeper insights beyond numerical trends. Whether you’re working with customer feedback, survey responses, or online reviews, choosing the right method depends on your budget, time constraints, and data volume.

Below, we break down three approaches:

1. Fully Manual Coding in Excel

The most straightforward way to analyze open-ended responses is manual coding. This method involves reviewing each response, identifying common themes, and categorizing the data accordingly.

How It Works:

Import the responses into an Excel spreadsheet.
Read through each response carefully.
Identify recurring themes or topics.
Create a codebook (a predefined list of categories).
Assign a code (or multiple codes) to each response based on its content.
Use filtering, pivot tables, or conditional formatting to analyze the results.

Pros:

Full control over coding criteria and interpretation.
No additional tools or software required.
Ideal for small datasets where automation isn’t necessary.

Cons:

Time-consuming, especially for large datasets.
Prone to human bias and inconsistencies.
Difficult to scale efficiently.

Best for:

Small-scale surveys with a limited number of responses.
Researchers who need complete control over qualitative analysis.
Projects with no budget for AI or automation tools.

2. AI-Assisted Coding in Excel (Entry-Level solution, for those on a budget)

AI can dramatically speed up coding by automatically classifying responses into themes. Using tools like ChatGPT and GPTforSheets, you can extract insights with minimal manual effort.

How It Works:

Import the responses into Excel or Google Sheets.
Use ChatGPT to generate a list of common themes.
- Prompt example:
  “Following is a list of open-ended survey responses. Generate a comma-separated list of themes based on the list: {your list of open-ended survey responses}”
Install the GPTforSheets plugin in Google Sheets.
Connect it to your OpenAI API key.
Use a formula to classify responses based on identified themes:
- Example:
  =GPT(CONCATENATE(“Classify the following survey response to one of the following themes: {list_of_themes_here}”, “ Response: ”, A2))
The AI will assign a category to each response, which you can further refine manually.

Pros:

Faster than manual coding.
Budget-friendly (low-cost API usage).
Reduces some human bias in classification.

Cons:

Limited to one code per response, restricting nuanced analysis.
Not ideal for large-scale datasets due to API constraints, errors and quality issues.
Requires multiple tools (Excel/Google Sheets + ChatGPT).
Privacy concerns if using sensitive data.

Best for:

Students willing to pay a few bucks to get things done faster.
People that are willing to compromise on quality to get things done quickly on a low budget.
Those comfortable using AI tools with Google Sheets.

3. Professional Verbatim Coding Software (Blix)

For researchers and businesses handling large volumes of open-ended data who care about quality, ease of use, and fast insights, Blix offers a professional-grade solution.

Unlike manual or AI-assisted coding, Blix streamlines the entire process of verbatim analysis, making it efficient, scalable, and highly accurate.

How It Works:

Import Excel files directly into Blix.
The software guides you through the analysis, automating key steps.
AI-powered coding suggests and refines themes while maintaining accuracy.
Supports multi-code assignments for nuanced insights.
Export results back to Excel for reporting and further analysis.

Pros:

Fully compatible with Excel – Input and output remain in Excel format.
Automated yet customizable – AI speeds up coding while allowing manual adjustments.
Handles large datasets – Unlike ChatGPT, Blix is optimized for high volumes of data.
Quick and easy – Perfect busy professionals, including for non technical users.
Private & secure – Data remains protected and private, making it enterprise-friendly.

Cons:

Not free (pricing varies based on usage and features).

Best for:

Businesses and researchers analyzing high volumes of qualitative data.
Market research teams looking for accuracy and efficiency.
Companies needing secure, scalable analysis solutions.

‍

Choosing the Right Method
‍

By selecting the right approach, you can turn unstructured qualitative data into actionable insights.

If you’re working with smaller datasets, a manual or AI-assisted approach may be enough. But if you need efficiency, accuracy, and security at scale, Blix provides the most robust solution.

Step-by-Step Guide to Manual Coding in Excel

Manual coding in Excel is a fundamental method for analyzing open-ended survey responses.

While time-consuming, it allows for complete control over categorization and interpretation. This approach works best for small datasets where automation is unnecessary, and researchers need to capture nuanced insights.

You can learn more about open-ended survey coding here.

‍

Step 1: Put the Data in a Spreadsheet

Before you begin analyzing responses, ensure your data is structured properly in an Excel spreadsheet.

Column A: Response ID (if applicable)
Column B: Raw open-ended response
Column C (Optional): Notes or additional context
Column D+: Assigned code(s) (to be filled later)

Example:

Click here to download our Google Sheet template with sample data to get started.

Step 2: Review the Data

Go through each response carefully to understand the key ideas and emotions expressed.

Look for patterns, recurring phrases, or common themes.
Note any outliers or unique responses that might need special categorization.
Highlight responses that might need further clarification or interpretation.

Pro Tip: Using Excel’s filtering and sorting features can help group similar responses together for easier analysis.

Step 3: Extract Themes

Now, identify common themes across the responses. This process is known as thematic analysis, where you categorize qualitative data based on shared ideas.

Read through all responses and note recurring topics (e.g., product satisfaction, customer service, app usability).
Write down frequently mentioned keywords or phrases that appear multiple times.
Keep the list broad at first, then refine it into clear, distinct themes.

Example:

Pro Tip: Use Excel’s Conditional Formatting to highlight similar words across multiple responses. This makes it easier to spot patterns.

Step 4: Build a Codebook

A codebook is a structured list of categories and their definitions. It ensures consistency when coding responses, especially if multiple people are working on the data.

Your codebook should include:

Code ID: a number to represent each code
Code Name: A short label for each theme
Description: A brief explanation of what the category includes
Example Responses: A few real survey responses that fit each category

Example Codebook:

Pro Tip: Store your codebook in a separate sheet in Excel for easy reference.

Step 5: Assign Relevant Code(s) to Each Response

Now that you have a structured codebook, you can begin assigning codes to each response.

Enter the category name from your codebook into the "Category" column for each response.
Some responses may fit into multiple categories, so add more than one if needed.
Use Excel’s dropdown lists or data validation to standardize category entry and reduce errors.

Example

Pro Tip: You can use Excel’s Pivot Tables to analyze the frequency of each theme across responses, making it easier to visualize trends in your data.

Pros and Cons of Manual Coding in Excel
‍

Final Thoughts on Manual Coding

Manual coding in Excel is a powerful way to analyze open-ended data when dealing with smaller datasets. While it offers complete control over the categorization process, it becomes inefficient as response volumes grow.

If you frequently work with large datasets, consider professional software like Blix to streamline the process.

Step-by-Step Guide to AI-Assisted Coding in Excel or Google Sheets

AI-assisted analysis can speed up coding open-ended responses while reducing some of the manual workload. By leveraging ChatGPT and the GPTforSheets plugin, you can quickly identify themes and classify responses in a semi-automated way.

This method is particularly useful for those working with medium-sized datasets who need a faster, budget-friendly alternative to manual coding.

Step 1: Put the Data in a Spreadsheet

Before using AI, make sure your data is structured properly in either Microsoft Excel or Google Sheets.

Column A: Response ID (optional)
Column B: Raw open-ended response
Column C: (To be filled later) Assigned category

Example:

Pro Tip: If working in Excel, ensure text wrapping is enabled for readability.

Step 2: Ask ChatGPT to Extract a List of Themes

Before classifying responses, you need to identify themes. Instead of manually analyzing responses, you can use ChatGPT to generate an initial list of themes.

Prompt:

“Following is a list of open-ended survey responses. Generate a comma-separated list of themes based on the list: {your list of open-ended survey responses}”

Pro Tip: If responses are long or nuanced, refine the themes manually before proceeding.

Step 3: Install the GPTforSheets Plugin in Google Sheets

Google Sheets allows you to integrate AI directly into your workflow using GPTforSheets, a plugin that connects to OpenAI's API.

To install GPTforSheets:

Open Google Sheets and go to Extensions > Add-ons > Get add-ons.
Search for GPT for Sheets and Docs and install it.
Once installed, restart Google Sheets to activate the plugin.

Step 4: Add Your OpenAI API Key to the Plugin

To start using the AI features, you'll need an OpenAI API key:

Go to https://platform.openai.com/account/api-keys and log in.
Click Generate API Key and copy it.
In Google Sheets, go to Extensions > GPT for Sheets and Docs > Set API Key, then paste your key.

Note: Be mindful of API costs—usage depends on token consumption.

Step 5: Classify Each Response Based on Themes

Once themes are identified, you can use GPTforSheets to automatically assign the most relevant theme to each response.

Formula to classify responses:

=GPT(CONCATENATE(“classify the following survey response to one of the following themes: {list_of_themes_here} ”, “ response: “, “response_cell_here”))

Example in Google Sheets:

Pro Tip: Manually review AI-generated categories for accuracy, especially for complex responses.

Advantages of AI-Assisted Coding

Faster than manual coding – AI processes responses in seconds.
Cost-effective – OpenAI’s API usage is relatively inexpensive.
Reduces manual workload – Automates theme identification and categorization.

Disadvantages of AI-Assisted Coding

Limited to one code per response – If a response contains multiple themes, it’s challenging to create a standardized format for easy analysis.
Not ideal for large datasets – OpenAI's API has limits on batch processing. Coding hundreds or thousands of responses may still take you hours due to those limits.
Quality issues - This process may result in errors, unexpected responses, variations in response formatting, or AI-generated inaccuracies (called “hallucinations”). It is recommended to monitor the data closely to ensure quality and reliability.
Requires multiple tools – You must switch between ChatGPT, Google Sheets, and OpenAI’s API.
Does not support collaboration – You can’t easily collaborate with a team on the coding.
Privacy concerns – Sending sensitive data to an AI model may not be secure.

‍
Who Should Use AI-Assisted Coding?

Students looking for a budget-friendly alternative to manual analysis.
New market researchers who are just getting started learning how to code.

AI-assisted coding in Excel or Google Sheets provides a balance between manual coding and professional tools like Blix. While it speeds up the process, it’s not a good replacement for a professional tool like Blix for professional analysts and researchers.

Blix – The Verbatim Coding Tool for Professionals

If you’re a professional coder working with high volumes of open-ended survey responses, you understand how important data privacy, scalability, and accuracy are. The last thing you want is to be hodge-podging together different tools, or spending hundreds of hours coding a single survey.

You want quality for your customers, and you want it fast. You want something that just works.

That’s where Blix comes in. Blix is built specifically for professionals who need a streamlined, efficient, and secure way to analyze qualitative data.

Unlike other methods, Blix guides you through the coding process step by step, making it easy to turn unstructured responses into clear, actionable insights.

‍

Why Choose Blix for Open-Ended Data Coding?

Blix is the ultimate tool to extract themes from your open ended data and code it for you with a click.
‍

100% Compatible with Excel

No need to learn a new platform or mess with complicated imports and exports. Blix works seamlessly with Excel, allowing you to:

Upload your survey responses in an Excel format – no conversion needed.
Analyze and categorize responses efficiently with built-in AI-powered tools.
Export your final coded data back into Excel for easy reporting and further analysis.

If you’re comfortable using Excel, you’ll feel right at home with Blix!

Streamlined and Doing the Work for You

Say goodbye to the tedious manual coding process. Blix automates repetitive tasks while still giving you full control over how responses are categorized.

Suggests and refines themes using AI-powered analysis.
Allows you to validate and adjust codes as needed for accuracy.
Saves you hours of work—no more copy-pasting or manually labeling responses!

Imagine having a smart assistant that speeds up your workflow while ensuring accuracy.

Step-by-Step Guided Process

You don’t have to be a data scientist to use Blix. Whether you’re a researcher, marketer, customer experience specialist, or business owner, Blix walks you through every step.

Step 1: Upload your dataset (Excel-compatible).
Step 2: Blix automatically suggests categories based on common themes.
Step 3: You review and refine the categories to ensure accuracy.
Step 4: Once coded, you can analyze trends and export results.

Even if you’re new to coding open-ended responses, Blix makes the process intuitive and user-friendly!

Supports High Volumes of Data

If you’re handling thousands of responses, Blix is built to scale with you. Unlike manual methods or AI tools with API limitations, Blix is optimized for processing large datasets efficiently.

No AI rate limits mean you get results in minutes.
Handles complex responses with multiple themes (not just one per response like basic AI tools).
Designed for research teams, businesses, and organizations that need reliable qualitative data analysis.
Supports collaboration between team members so you can have everyone on the same page.

Whether you’re analyzing a few hundred responses or tens of thousands, Blix keeps up with your needs.

Private & Secure – Your Data Stays Protected

One major drawback of using AI-assisted tools like ChatGPT or GPTforSheets is that your data is sent to external servers, which may not be ideal for sensitive or confidential information.

Blix ensures your data remains private and secure and won’t be used to train AI models like ChatGPT.
Meets industry standards for data protection.
Perfect for organizations that require compliance and confidentiality.

If security and privacy are a priority, Blix is the best choice for professional verbatim coding.
‍