Transforming Open-Ended Survey Responses into Actionable Insights

Introduction to Verbatim Coding

In the world of market research, verbatim coding is the process of organizing and classifying open-ended survey responses to support quantitative analysis. While it’s possible to code these free-form responses manually using spreadsheets, purpose-built platforms—like Codini—offer a far more efficient, streamlined, and accurate approach. By leveraging advanced coding tools or professional coding services, you can seamlessly categorize and interpret qualitative feedback, turning it into valuable, data-driven insights.

What is Survey Research?

Survey research is a fundamental approach in market research. By asking questions to customers, employees, or other audiences, organizations gain clarity on their opinions, preferences, and experiences. These insights fuel strategic decisions, from improving product design and customer satisfaction to fine-tuning marketing strategies.

Market research comes with its own set of specialized terms. If you encounter unfamiliar concepts, resources like the MRA Marketing Research Glossary can help you navigate the industry’s language.

Why Ask Questions?

Every business ultimately aims to boost sales and generate profits. Improving customer happiness—both among existing clients and potential new ones—is a critical step in that direction. One of the most effective ways to understand what customers want is to simply ask questions and act on their feedback.

For example, consider an open-ended query in a product survey:

• Q: “What do you think about our new packaging design?”

• A: “It’s difficult to hold the container securely, and I end up spilling the product.”

This sort of candid feedback guides organizations in refining their offerings. Sometimes these insights arise directly through surveys, while other times they emerge from help desk interactions, social media comments, or review platforms. In all cases, the fundamental goal remains: gather authentic responses and use them to drive improvement.

Keep in mind that “customers” doesn’t just mean buyers. If you’re an HR manager, your “customers” are employees. By collecting their feedback, you can improve internal policies, engagement, and satisfaction.

Open, Closed, and Other Specify (O/S) Questions

Survey questions typically fall into three categories:

1. Closed-Ended Questions: Predetermined response options, such as multiple-choice answers. For example:

“How would you rate our customer service?” with options like “Excellent,” “Good,” “Fair,” or “Poor.”

2. Open-Ended Questions: These invite respondents to answer in their own words, capturing a breadth of opinions and ideas. For example:

“What suggestions do you have for improving our customer service?”

3. Other Specify (O/S): A blend of the above, offering predefined answers while allowing respondents to add their own if none of the listed options fit.

We often refer to free-text answers to open-ended or O/S questions as “comments,” “responses,” or “verbatims.” To analyze these effectively, researchers use coding to categorize the feedback into meaningful themes.

Answers vs. Verbatims (Comments)

For closed-ended questions, “answers” are straightforward—respondents choose from given options. In contrast, open-ended queries produce “verbatims”: raw, potentially unstructured text responses. While these verbatims are rich in detail, they aren’t immediately usable for quantitative analysis. The coding process transforms these verbatims into structured data—turning raw feedback into actionable “answers” that can be measured and compared.

Outside of the research industry, these inputs are often simply called “comments.” In professional market research contexts, we typically use the term “verbatims” to emphasize that these responses are captured exactly as given by the participant.

Collecting Survey Data

“Fielding” a survey means distributing it to respondents and gathering their input. Surveys can be conducted through various methods:

• Paper: Mailed questionnaires, in-store forms, feedback cards.

• In-Person Interviews: Street intercepts, focus groups, or mall kiosks.

• Telephone Interviews: Outbound calls to households or follow-ups after reservations.

• Mobile Device Surveys: In-app feedback, in-store mobile surveys, or image-based responses.

• Web Surveys: Links on websites, email invitations, or surveys accessed after a purchase.

The diverse range of collection methods leads to equally varied data sources—typed text, handwritten notes, audio responses, images, and more. Regardless of format, you need participants who are willing to share their experiences and a reliable method of recording their input.

Survey Logic: Branching and Looping

Modern survey platforms often use logic to personalize and optimize the respondent experience:

• Branching: The path of the survey changes based on earlier answers. For instance, if someone identifies as a loyal customer, they might answer a different set of questions than a first-time buyer.

• Looping: The same set of questions might repeat for multiple products or scenarios. This reduces repetitive manual input and ensures consistent data collection across various items.

These features ensure respondents only see relevant questions, making the process more efficient and the data more meaningful.

Understanding Sample and Panels

A survey’s “sample” is the group of respondents who provide feedback. Researchers often work with sample providers that maintain panels—groups of vetted participants ready to respond to surveys. Panelists may receive incentives (cash, gift cards, discounts) in exchange for their time, influencing the total cost per completed survey. Reputable sample providers uphold strict quality standards, ensuring their panels accurately represent the target audience and deliver trustworthy data.

Trackers and Waves

Surveys can be one-time projects or part of a longitudinal approach:

• Trackers: Surveys repeated periodically (monthly, quarterly, yearly) to monitor changes in attitudes or behaviors over time.

• Waves: Each iteration of a tracker survey is called a wave. Comparing multiple waves reveals trends, shifts in sentiment, and the long-term impact of interventions.

The Power of Verbatim Coding

Responses to open-ended questions capture nuanced, detailed perspectives. However, to convert these free-form comments into actionable insights, you need to categorize them through a process known as verbatim coding.

Imagine a company is testing new packaging for their products. After sending out samples and surveying customers, one open-ended question might be:

• Q: “What issues did you encounter with our new container?”

• A: “It’s awkward to handle, and I’ve spilled product on my countertop twice.”

By reviewing multiple responses, coders develop categories (codes) that represent common themes, such as “Hard to hold,” “Leaks or spills,” and “Awkward shape.” Assigning codes to each verbatim helps quantify feedback and identify patterns:

• “Hard to hold” might apply to 25% of respondents.

• “Leaks or spills” might be mentioned by 15%.

These findings become powerful data points guiding product improvements and strategic decisions. Coding transforms qualitative feedback into quantifiable results.

Codebooks, Codes, and Nets

A codebook (or code frame) is a structured list of codes representing the patterns found in verbatims. Codes are often organized into thematic groups called “nets.”

For example, if respondents talk about desired flavors for a beverage, you might have a “Flavor Preferences” net with individual codes like “Apple,” “Cherry,” or “Peach.” Another net might be “Health/Nutrition” for comments like “Sugar-Free” or “Natural Ingredients.”

This hierarchical structure ensures you can quickly identify and quantify the most popular themes or issues raised by respondents.

Downstream Analysis and Tabulation

Once coding is complete, the data is ready for further analysis. The tabulation (or “tab”) phase involves using statistical tools to examine frequency counts, cross-tabulations, and advanced analytics. Each code typically gets a numeric identifier, which analysts use to run reports and generate insights. This numeric approach allows for robust statistical exploration, turning open-ended feedback into clear, comprehensible summaries.

Codini: Your Partner in Verbatim Coding

Codini streamlines the entire verbatim coding process, offering advanced technology and expert services that empower researchers and organizations. Our coding solutions save time, ensure consistency, and allow you to uncover the rich stories hidden in your survey responses.

If you’re pressed for time or need additional assistance, our dedicated coding team can step in, ensuring a seamless and high-quality coding experience. We also offer AI-enhanced coding with human oversight, as well as translation services for multilingual projects. Leading research firms and global organizations trust Codini for their verbatim coding needs.

Get Started with Codini

Transforming open-ended responses into actionable insights doesn’t have to be complicated. Contact Codini today to learn how our platform and services can help you harness the full power of your qualitative data, guiding smarter decisions and more impactful strategies.