From Add-On To Essential: The Gradual Shift In AI Market Research Adoption

Once a concept of science fiction movies, Artificial Intelligence, or AI, is increasingly becoming a common aspect of our daily lives. Over the last few years, AI has been treated as an intriguing add-in in the world of market research, allowing researchers to speed up analysis or manage repetitive tasks. However, we are increasingly seeing AI-driven market research becoming more heavily adopted.

While most still prefer to combine it with a more traditional approach, the perception of AI is swiftly moving from a novelty to a necessity. Of course, this shift isn’t happening overnight as market research professionals are understandably careful and protective of their data quality. Yet AI and market research are becoming closely entwined, and in this latest article, we explore how this technology is no longer just a supporting act…

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Why are researchers cautious about artificial intelligence?

To understand why the adoption of AI-powered market research has been gradual, it is first important to appreciate the culture of market research and, in particular, the research community. Accuracy and reliability are everything in this field, so when AI tools first started to emerge, many professionals felt that they were unreliable and untested, which meant that they were simply too unpredictable to trust with high-stakes projects.

That opinion is not unfounded, and the early role of AI-powered market research was predominantly functional. Researchers would use it to code open-ended survey responses, clean up data, or to run basic sentiment analysis. While this was still useful and saved time, it was still limited, and few saw AI as capable of handling the nuanced and interpretive tasks that human researchers performed.

In particular, there was a lot of scepticism around AI-driven market research for those projects that required comprehensive qualitative methods, such as in-depth interviews or ethnographic studies. This cynicism stemmed from early AI tools, which struggled to capture the cultural context, tone, and subtleties of human language, and the risk of misinterpretation significantly outweighed any speed benefits AI provided.

How hybrid research turned the tide

Over the last few months, there has been a big shift in opinions as more professionals understand how to use AI for market research. Hybrid approaches that combine AI-powered market research with more traditional human-led approaches have revealed that AI is not here to replace humans but to partner with them and empower their work.

Hybrid AI-driven market research approaches are gaining traction across the globe, with artificial intelligence able to handle the scale and speed while human researchers are able to bring nuanced interpretation, empathy, and domain knowledge. For example:

• Artificial intelligence can process thousands of survey comments in a matter of minutes, identifying patterns and clusters within the responses. Human researchers can then review those clusters to understand the “why” behind the numbers.

• Equally, conversational AI tools can conduct interviews at a far greater scale than their human counterparts, generating instant transcripts and analyzing responses. Researchers are then able to review, refine, and validate these insights.

How AI is working with conversational research

When it comes to using AI for market research, one of the most exciting areas has been its use in conversational research through AI-powered moderators that interact directly with respondents. Many see this as moving closer to qualitative research as it involves dialogue rather than straightforward static survey forms.

Yasna, for example, embraces the qual first approach:

As opposed to AI conversational platforms that do survey first approach, Yasna is qual first. Yasna is governed by algorithms that mimic human moderation which include context and topics which set the boundaries for conversation. - Anna Krazhan, Chief Commercial Officer, yasna.ai

However, few researchers are ready to hand over an entire qualitative project to artificial intelligence on its own. Instead, conversational tools are often positioned as extensions and a way to scale interviews, collect more diverse data, and speed up transcription and coding.This hesitancy reflects a broader theme in AI and marketing research: the technology is respected for its efficiency, but hasn’t fully earned a reputation for independent credibility.

Why AI should be seen as essential, not optional

While there is still a lot of caution within the industry, the pace of AI development is astonishing, and it is rapidly outperforming perceptions. The capabilities of AI-powered market research has expanded dramatically over the last few years, and it has evolved from simple text analysis to multimodal research that can process not just written responses but also images, videos, and voice notes.

Platforms like Yasna are able to support richer, human-centered data collections. That means respondents can record video testimonials, upload photos, or share audio feedback to create a rich context for analysis. Our AI technology is then able to extract meanings from these diverse formats and identify patterns across text, visuals, and speech simultaneously.

Yasna uses human moderators techniques such as icebreakers, probing, laddering, redirecting making each interview experience seamless for the respondents which results in quality controlled moderation and truly meaningful insights. - Anna Krazhan, Chief Commercial Officer, yasna.ai

When you start to compare this with the more traditional methods, it is clear that AI is no longer just a helper when it comes to market research. It is capable of producing insights that would be nearly impossible or prohibitively expensive if just using manual approaches.

Practical ways researchers are using AI

If you are wondering how to use AI for market research, we thought we would explore at some of the most common ways researchers are using the technology today:

• Automated coding of open-ended responses

  One of the most common methods for using AI for market research is within automation, especially for scaling qualitative feedback into quantifiable themes.

• Real-time sentiment analysis

  AI is also able to detect how people feel about a brand, product, or ad campaign in real-time.

• Conversational surveys

  Artificial intelligence is now able to gather responses through natural dialogue rather than through rigid questionnaires.

• Multimodal analysis

  This includes interpreting video reactions, audio, and written responses together to create a holistic view.

• Predictive modelling

  Finally, using AI for market research also allows for predictive modelling, using past data and current insights to forecast market shifts and consumer behavior.

How to address the trust gap

Of course, there still remains a large amount of distrust around the use of AI, as researchers want to know that the insights being produced are valid, unbiased, and transparent. That is why building confidence is not something that will happen overnight, but several trends are already helping to shift opinions.

Many platforms are now clearly outlining how their AI models are making decisions, allowing human researchers to review logic and check for bias. For many, it is also important to keep a human researcher in the loop to oversee, validate and refine the data.

Finally, as more projects demonstrate the success of AI-driven market research, case studies are helping to ease the skepticism and encourage more organizations to embrace the technology.

What does the future have in store?

As the last few years have shown, artificial intelligence is evolving at breathtaking pace, and the future is seemingly limitless. In the short term, it is clear that AI powered market research is going to become more common and embraced as an essential part of any project.

Whether that is conducting preliminary conversational interviews, analyzing vast swathes of data, predicting trends and behaviors or any number of other tasks that can streamline and improve traditional methods, AI is here today.

Final thoughts

The adoption of AI in market research has followed a gradual path and at first, researchers were rightly cautious, only utilizing the technology for small, supportive roles. However, hybrid models are now dominating the sector, with humans and machines working side by side.

But the technology is quickly evolving, and AI is now able to process text, images, videos, and voice with proven success. This is placing it at the core of market research; however, it’s not about replacing traditional tools but embracing these new ones to form a new approach to the sector.

Here at Yasna, we know how beneficial artificial intelligence can be when it comes to market research. That is why we’re on a mission to make it easier to embrace these tools and discover the benefits yourself.

If you’d like to learn more about how we handle AI–powered research, book a private demo.

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