5 Minutes 
During Sago’s recent webinar, “Harnessing AI in Research: A Roadmap to the Future,” Raj Manocha, Chief Client Officer of Sago, delved into the current state of AI in market research and how to leverage its capabilities to enhance insights and drive forward-thinking strategies. During the webinar, we had a lively Q&A session with our audience, but unfortunately, we ran out of time before we could answer all the questions. We appreciate your engagement and enthusiasm, and rest assured, we have compiled all the unanswered questions into this blog post. Keep reading to discover Raj’s insights on the latest developments in AI and how it can be used to revolutionize market research.
Concerns and Ethics in AI Research
Q: How do users measure bias in AI insight research tools if that’s their primary concern?
A: This is more about how the tool is built. It really comes down to using multiple tools and benchmarking, understanding the data that helped build the tool, and knowing where that data came from.
Q: Can Generative AI be leveraged to ensure respondents are who they claim to be?
A: Potentially. The AI would need to be built as a quality tool and trained to suss out fraud.
Q: How can companies experiment with AI without investing excessive resources too early?
A: You should look at the companies, including Sago, who are starting to build AI tools and pilot. The industry is heavily invested in seeing how this all works, so everyone is motivated to partner to get case studies, whether good or bad. It’s really about the learnings.
Q: Are there any concerns about hallucinations?
A: There are always concerns with every new technology; that’s why we continue to pilot. Testing and learning are integral to making sure we, as an industry, can alleviate these concerns.
Impact and Applications of AI in Market Research
Q: How are AI tools currently being used in qualitative research?
A: It’s being used to enhance the moderator experience and jump start qualitative analysis.
Q: How is the use of AI impacting sample providers in market research?
A: Companies are using generative AI to create different types of respondent personas; AI is being used for optimization of sampling and for doing bids.
Q: What is the potential impact of AI in healthcare market research and outreach?
A: Tougher audiences will, most likely, have generative personas created so these groups have more accessibility. This will allow anyone to be able to engage with healthcare professionals in a more streamlined and ubiquitous way. You’ll be able to have healthcare professionals in your pocket and can have conversations whenever you want.
Q: How can market research professionals stay updated on AI advancements related to their field?
A: It’s really important to look at publications like Quirks, Insights Association, ESOMAR and MRS. But it’s also important to look outside our industry as well – there have been great advancements outside our industry that are backing their way in, so explore more generic AI groups on LinkedIn or X (Twitter).
Q: How is the validity of AI applications in market research measured?
A: This is still an ongoing process, and all the associations are trying to figure out the right approach here; we are still in early days.
Q: How can we ensure the accuracy and credibility of AI findings?
A: We need to come together as an industry and do more testing and learning. Just as when online panels formed and we needed to benchmark for accuracy, we now need to apply the same sort of rigor and logic to AI.
Q: What happens to our data when uploaded into an AI platform?
A: This varies based on the tool. In some cases, it will analyze the data. In other cases, you may be looking for supplementary data to add to your current data – it all depends on what you are looking to do with the AI tool, and what the capabilities are.
Q: What methods can be used to reduce AI responses in quantitative research studies?
A: Data collection firms need to adjust their quality checks and implement AI to make sure fraud isn’t occurring in this capacity.
Practical Use and Efficiency of AI in Market Research
Q: Has any progress been made in using AI to code open-ended responses in a meaningful way?
A: Yes. AI does much better with unstructured data vs. structured data, so you’ll see much more progress in this area over the next couple of months.
Q: Are there sources for market research prompts for AI?
A: There are lots of prompt guides on LinkedIn and X.
Q: Can AI help detect fake responses and respondents?
A: Yes, it just had to be taught and implemented in the quality checks done by data collection firms. This will become a normal feature over time.
Q: What are the risks and implications of using generative AI for customer simulations/feedback in market research?
A: It’s really about how and when to use it. It will not replace everything, but it does give you a great early check within your research process.
Q: What are the latest AI tools for market research and how can researchers leverage them for efficiency and accuracy?
A: There are tools being developed to create questionnaires, personas, analysis, and reporting. Researchers should engage their partners and ask them about their AI tool sets and see if they can pilot with them.
Q: Where do you see the most value-add of AI for qualitative researchers?
A: Faster analysis, scaling yourself as a moderator, and reporting.
Q: How can AI be utilized to write more efficient qualitative reports?
A: You can ask AI tools to simplify your reports or condense your writing. It’s all about how you prompt the tool.
Looking for more information on the intersection of technology and market research? Check out Sago’s Eye on Innovation Series.
