The Benefits and Boundaries of AI in Market Research: An Introduction to Qualibee.ai
It’s hard to go on LinkedIn or check industry news these days without reading about AI in market research. But what does that actually mean, how is it currently being used, and how should it be used?
What is AI?
The recent conversation around “AI” tends to be around what is known as “generative AI.” A future blog post will go deeper into the differences and similarities between the different types of AI/machine learning, but for now, the key feature of generative AI is that it turns input into content. Generative AI identifies patterns in existing content (e.g., text, visual images, software code) and then applies those patterns to produce something new.
For market research, generative AI is currently being used primarily in qualitative research to analyze transcripts, offer moderation help, enhance open-ended questions, and even engage with respondents in data collection. However, while AI can bring amazing value in particular use cases, it also comes with qualifications that potential users need to be aware of. We will discuss the capabilities of Qualibee.ai and the value delivered, but also address the shortcomings of the current generation of AI tools.
What is Qualibee.ai?
Qualibee.ai delivers both data collection as well as analytics capabilities all in one platform. For security and customization purposes, we are NOT using OpenAI’s ChatGPT. To get qualitative insights at scale, Qualibee.ai allows a user to program a discussion guide of questions that will be seen by all respondents. We then leverage our internal AI models to generate relevant follow-up questions based on an interviewee’s responses. These can be further tailored by prompts that will direct the follow-ups based on certain aspects of a response. For example, if an interviewee responds to a question in a positive manner, further probe in one direction. If they respond in a negative manner, probe in a separate direction.
This conversational style provides respondents with a more engaging process compared to traditional surveys while still allowing them to complete the study at a time convenient to them. This alleviates the scheduling problems that are inherent to in-person interviews. Using voice and long-form text, a respondent is not held to set response options which enhances the richness of the data collected.
After data collection is complete, a Qualibee.ai user has many analysis options at their fingertips. Using prompts, they can ask the model for a wide variety of information. Here are only a few:
An executive summary of the most important themes
Marketing recommendations
Product design recommendations
Potential use cases
Pain points
Predicting future trends
Recommended survey questions and response options for a follow-up quantitative study
The model can also provide supporting data points for any of its insights/recommendations along with the relevant Respondent ID. This allows for easy confirmation and deeper dives into the underlying data.
We also wanted to provide quantification capabilities to help users gauge the relevant strength of themes and entities uncovered by the generative AI. To do this, Qualibee.ai incorporates a machine learning based classification tool. This tool allows the user to enter classes (e.g., use cases like marketing, sales, customer service, etc.) and then it automatically categorizes the data to see how important these classes are to respondents. This capability is intended to help strengthen findings when making decisions or influencing other research methods.
Things to consider before using AI
However, there are important qualifications to consider when using an AI platform. Qualibee.ai is intended to ENHANCE a researcher’s capabilities and speed to insights without replacing traditional methods in all use cases. Below are a few points to consider when deciding whether or not to use AI in a project:
Even if a tool has classification capabilities, this is not a replacement for quantitative research. If you need statistical significance testing, then a survey is still your go-to for a study.
While generative AI is already capable of delivering very accurate results, you still need a human to “look under the hood” to confirm findings as well as turn those insights into action.
AI engagement provides a researcher with the ability to query a large number of respondents in a target market in a short amount of time, but it does not replace genuine human interaction. For example, AI cannot read the in-room dynamics of a focus group, meet with people in their home or place of work, or connect with an interviewee in the same way a human moderator can in an in-depth interview.
Benefits of Qualibee.ai
While there are qualifications and shortcomings with AI platforms, Qualibee.ai is still an extremely valuable tool to market researchers in the correct situations. For example:
Before launching an expensive quantitative or qualitative study, get better insight into things like what questions to ask, which survey responses options are most appropriate, or which groups have the most interest. Qualibee.ai provides you with insights as fast as interviewees can be recruited. This saves time, money, and potential inaccuracies in larger studies.
Do you have an important meeting and need fast, accurate insights? While large decisions should include mixed method studies, Qualibee.ai is the best way to deliver the information you need in the time that you need it and at a price that won’t hurt the bottom line.
Qualibee.ai can be customized for a client and run behind their own firewall. Our models can be trained on your data and reports to customize everything from the interview experience all the way to how output is structured. All of this on your own servers without your data going outside the organization.
Conclusion
In conclusion, Qualibee.ai is not here to replace us as researchers. Rather, it's here to enhance our capabilities, to help us delve deeper and reach further in our quest for insights. It's about embracing a new method in the future of market research—a future that's faster, more efficient, and rich with potential. As researchers, we have an exciting opportunity to lead this transformation, harnessing the power of AI to elevate our work and define the value our industry provides.
