Cutting through the qualitative noise to find customer insights.
Market research is booming. The market grew from $102 billion in 2021 to $140 billion in 2024, an increase of 37.25%.
There’s a catch…
A big part of this growth is being driven by qualitative research. Open-ended survey answers, focus group transcripts, and customer feedback, all the juicy stuff.
The problem? There’s a ton of unstructured data like this. It needs to be coded before it can be analyzed. It all needs to be labeled so it’s quantifiable and usable.
Here’s What You’ll Learn:
- Why Market Research Coding Services Matter
- The Custom Coding Advantage
- How AI Is Changing the Game
- Choosing the Right Coding Solution for Your Needs
Why Market Research Coding Services Matter
Market research coding is the process of taking open-ended survey responses or verbatim data and labeling it in a way that you can draw conclusions from it.
Think about it…
When someone fills out a survey and has the option to write a paragraph about their experience with a brand or product, that freeform feedback needs to be interpreted.
Coding makes that happen.
Without coding, we’d drown in walls of text data with no way to quantify trends or measure sentiment. A solid market research verbatim coding service converts raw customer feedback into business insights.
Why that’s important right now:
A survey by Qualtrics found that 57% of market researchers have experienced increased demand for qualitative research from clients.
Ask any client and they’ll tell you the number one thing they love about qualitative research is all the juicy insights that live in open-ended data. And they want those insights in high quantities.
It’s why open-ended questions are all the rage these days.
So, where does all of this data go? It needs coding.
If the coding is inconsistent or inaccurate the entire research project is in jeopardy.
The Custom Coding Advantage
Not all coding solutions are created equal.
Generic coding services and frameworks are fine up to a point. If the research is simple enough and everything being asked about is a standard you can code against, basic solutions are fine.
When it comes to more complex research with more nebulous topics, industry-specific lingo, or more subjective sentiment, generic coding solutions just aren’t enough.
That’s when custom coding solutions come into play.
The language in a survey for a pharmaceutical product is much different than the language in a survey for a sandwich shop. The categories that a consumer might mention in these two surveys is going to vary wildly. A one-size-fits-all coding approach will miss much of the most important nuances.
Here’s where a custom solution is key.
Custom solutions offer several big advantages:
- Industry-Specific Categories: Custom code frames and dictionaries are built to be used in a particular business vertical or research area
- Flexible Frameworks: Instead of being locked into a pre-built static set of categories, custom solutions can be adjusted as the analysis uncovers new themes
- Better Accuracy: Coders that are trained up on specific project requirements are going to catch more nuance and make fewer mistakes
- Contextual Understanding: A custom solution can be built to take into account regional language differences, colloquialisms, and other important cultural contexts
The difference between a generic and custom approach is significant. One will only offer surface-level insights. The other digs deep and finds the hidden patterns that lead to better business decisions.
How AI Is Changing the Game
Coding is going through some big changes at the moment.
Manual coding has been the gold standard for decades. Human coders go through each open-ended response, category it, and are tasked with maintaining quality assurance across the board.
The challenge with that?
Manual coding is slow. When you have thousands of open-ended survey responses to categorize it’s not uncommon for this process to take weeks. This creates bottlenecks that can slow entire research projects.
Enter AI coding solutions.
AI-powered tools that use large language models are being developed that can read responses, understand context and intent, and code these at scale. In seconds, not hours.
The field has made some big advances in the last couple of years.
But here’s the thing, these AI models are not just fast, they don’t get tired. They can look at thousands of responses and still maintain consistency across the entire dataset.
The proof is in the data:
Globally 47% of researchers use AI at least sometimes as part of their market research process. That number is increasing year over year.
But there’s one key point that most miss…
The most accurate results are often achieved with a hybrid approach. AI takes care of the heavy lifting and speeds everything up. Human experts are used to step in on the tricky edge cases and validate accuracy.
Pretty smart right?
Choosing the Right Coding Solution for Your Needs
There’s no one-size-fits-all when it comes to coding solutions.
Your project scope is key. Small projects with a few hundred responses can get away with manual coding services. Projects that reach into the thousands of responses need automation to keep on schedule.
If you or the client are working with tight turnaround times AI becomes the obvious choice because of the speed improvements.
On the flip side, some projects have extremely high accuracy requirements. Others have more flexibility. Match the solution to the accuracy requirements of the project.
Budget also plays a role here. Manual coding with experienced human coders comes with a higher price tag per response. AI solutions have better scalability and cost efficiency.
Take a look at this quick reference chart:
| Factor | Manual Coding | AI-Powered Coding |
|---|---|---|
| Speed | Slower | Much faster |
| Cost per response | Higher | Lower at scale |
| Nuance detection | Excellent | Improving rapidly |
| Scalability | Limited | High |
The reality is that 33% of researchers across the world outsource work because their team lacks the research skillset to support it. Finding the right market research coding partner is key.
Take your time. Evaluate options. Choose the partner that best fits your needs. The right partner can make or break an entire research project.
The Future of Market Research Coding
Market research coding is on the cusp of some big changes.
AI is improving each month. We’re getting closer and closer to human-level accuracy in market research coding with machines.
The problem is that nuanced qualitative analysis is a job for human experts.
The leaders in this space are those that are able to merge technology and human expertise to create solutions that have the best of both worlds.
The formula is simple:
Custom code frames that are built for a specific research project, powered by the AI tools that are now available, and then finally put through a human QA and quality assurance process.
That combination allows for both rapid turnaround and high-quality data.
Companies that leverage these advanced coding solutions in their market research are the ones that are going to come out ahead. Because they’re going to be able to extract insights faster, make better decisions, and stay ahead of market trends.
Bringing It All Together
Market research coding services are a necessary evil if you want to extract value from all of the qualitative data out there.
The trend towards qualitative research is here. More and more clients are asking for open-ended questions to be added to their surveys to collect this unstructured feedback. The problem is there’s nothing you can do with it until it’s coded.
Keep these takeaways in mind:
- Custom solutions will outperform generic approaches for nuanced research
- AI-powered tools can dramatically improve speed and scalability
- Human oversight is still needed to ensure the quality of complex categorization
- The right solution depends on your specific project scope, timeline, and budget
The market research industry is only going to continue to grow. Qualitative data is only going to keep increasing. The organizations that will be able to succeed at coding this data are the ones that will be able to extract the insights that will lead to more intelligent business decisions.
That’s the real competitive advantage.
