Choosing a Thematic Coding and Text Analytics Tool for Market Research

A Buyer’s Guide to Thematic Coding, Open-Ended Analysis, and Human-AI Collaboration

This guide is designed to help agency and brand-side researchers evaluate tools for coding and analyzing open-ended data at scale. This guide helps researchers navigate the trade-offs and choose a solution that balances depth, speed, accuracy, and transparency.

There are eight key drivers of value to evaluate when choosing a thematic coding and text analytics tool — and three major trade-offs that can shape your decision.

8 Drivers of Value to Look For in a Text Analytics Solution

1) Adaptability & Customization

Every research project is different — and your analysis tool needs to give you the control to account for that. Look for a platform that supports custom code frames based on your data, stable code frames for longitudinal comparison, and analysis grounded in your context and goals.

Key Questions to Ask:

• Do you have control to customize code frames based on your data at goals?

• Can you revise, refine, or reapply codes to meet your needs?

• Does it support stable themes for longitudinal analysis?

2) Scalability & Speed

Scale shouldn’t come at the cost of quality. The right tool should allow you to analyze thousands of responses quickly, without compromising control, accuracy, or depth.

Key Questions to Ask:

• How quickly does the tool take you from raw data to trustworthy insight?

• Can it scale to handle thousands of responses without loss of speed or quality?

• How much time do you spend fixing what the system gives you?

Scale shouldn’t come at the cost of quality. The right tool should allow you to analyze thousands of responses quickly, without compromising control, accuracy, or depth.

Key Questions to Ask:

• How quickly does the tool take you from raw data to trustworthy insight?

• Can it scale to handle thousands of responses without loss of speed or quality?

• How much time do you spend fixing what the system gives you?

3) Nuance, Detail & Accuracy

4) Transparency, Auditability & Trustworthiness

Some tools offer only summary-level outputs, making it impossible to trace insights back to real responses. Look for platforms where every insight is auditable — and every code traceable.

Key Questions to Ask:

• Can you trace each theme or sentiment back to specific verbatims?

• Are stats and data paths visible, or are you guessing at the process?

• Can you adjust or audit coding, insights or query results to understand the source?

5) Versatility Across Data Types, Workflows & Languages

Some tools offer only summary-level outputs, making it impossible to trace insights back to real responses. Look for platforms where every insight is auditable — and every code traceable.

Key Questions to Ask:

• Can you trace each theme or sentiment back to specific verbatims?

• Are stats and data paths visible, or are you guessing at the process?

• Can you adjust or audit coding, insights or query results to understand the source?

6) Analytics & Reporting Power

Once your data is coded, powerful analytics should help you uncover deeper insights, and communicate them clearly to stakeholders and clients.

Key Questions to Ask:

• Can you segment open-ended themes by any attribute to compare segments with statistical confidence?

• Can you query your data within a single project or across multiple projects?

• Can you share insights easily and seamlessly with stakeholders?

7) Ease of Use

A great tool is one that everyone on your team can use — from junior analysts to senior stakeholders — without a steep learning curve.

Key Questions to Ask:

• Is the tool easy to learn and use for both junior analysts and senior stakeholders?

• Does it support quick onboarding, role permissions, and team collaboration?

• Can users easily return to past data for follow-up questions or re-analysis?

8) Data Security, Privacy & AI Ethics

A great tool is one that everyone on your team can use — from junior analysts to senior stakeholders — without a steep learning curve.

Key Questions to Ask:

• Is the tool easy to learn and use for both junior analysts and senior stakeholders?

• Does it support quick onboarding, role permissions, and team collaboration?

• Can users easily return to past data for follow-up questions or re-analysis?

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Tradeoffs In Choosing a Text Analytics Solution

In addition to the seven drivers that maximize the value of any open ended analysis platform, there are three key trade offs to consider in choosing a solution for market research or customer insights:

1) Quality vs. Speed in Thematic Coding

Many tools prioritize speed at the expense of nuance — or demand full manual labor to achieve accuracy. The best solutions strike the right balance between depth and efficiency.

Key Questions to Ask:

• Does the tool sacrifice nuance for speed?

• Can it handle large volumes *and* detailed analysis?

• How much of the process is automated, and do you have the control needed to maintain quality?

2) Focus vs. Versatility in a Platform Solution

A jack-of-all-trades tool may lack the precision you need for open-ended analysis. Prioritize excellence in core capabilities over tools that try to do everything.

Key Questions to Ask:

• Is the tool built specifically for open-ended analysis, or is it an afterthought that’s tacked on?

• Does it go deep in the areas that matter most for your work?

• Are you compromising on core functionality for breadth?

3) ROI vs Cost of the Tool

ROI is more than just software cost — it’s about time savings, analyst efficiency, and net-new value delivered to stakeholders. To truly account for your ROI, you need to account for both hard costs and these somewhat intangible costs.

Key Questions to Ask:

• How many hours of human labor does it eliminate or redirect?

• Can it replace other tools or reduce reliance on external partners?

• Does it accelerate time to value for insights and impact?

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Want to give Fathom a try?

The right thematic coding, text analytics or open-ended analysis platform doesn’t just help you analyze responses — it unlocks more value from your research, faster. Use this guide to evaluate your options and ask the right questions.

Want to see how Fathom delivers on these drivers? Book a demo to learn how human-in-the-loop AI transforms your open-ended analysis.