AI and market insights generation
Today, numerous organizations seek new technologies to enhance the quality of their marketing research. According to Deloitte, one in four companies has already initiated the inclusion of Generative AI into marketing operations, showing a turn towards more innovative data methodologies.
While most early adopters are still at the initial stage of using Gen AI primarily as a collector of data, this first wave of organizations is finding that AI is effective at processing collected info for high-quality conclusions about market patterns. A BCG report showed that 70% of CMOs were using generative AI, and the top two use cases were personalization at 67%, followed by insight generation at 51%. Amazingly, insight generation came second, ranking even higher than content creation.
Transforming marketing research with Generative AI. A case study in pharmaceutical insights
Marketing research often involves two broad types of surveys to understand consumer behavior: quantitative and qualitative. Quantitative surveys involve data that can be measured, such as rating a customer's experience in a store based on a scale of one to five. These bounded responses allow for KPI calculations and present insights in a data-driven manner. Qualitative studies, in turn, research consumer motivations and whys by asking open questions. It may be in-depth interviews that center around the main topic but use many angles to delve into meaningful insights.
KHMARKA developed a generative AI solution for a qualitative market study on digestive health conducted by a pharmaceutical company. The goal was to understand how people deal with indigestion, what remedies they use, and why such solutions were chosen. Classic qualitative studies use up many resources: targeting groups, conducting one-on-one interviews, recording conversations, transcribing data, and performing detailed analyses. Our AI-driven platform changed this by carrying out these interviews through an interface with chatbots, asking open-ended questions that could lead to meaningful discussions.
Addressing research pain points with Generative AI
Our solution directly addresses the major pain points for traditional market research methods. Scheduling and conducting interviews individually is extremely time-consuming and is often plagued by logistical problems, like no-shows or rescheduling conflicts. The transcribing of hours, and then reviewing recorded interviews manually, can be extremely cumbersome and, if done by junior and inexperienced staff, will often be subject to potential oversights or biases.
The following are the biggest pain points that were successfully removed by KHMARKA’s solution:
Pain point 1: Qualitative surveys are extremely time-consuming and therefore very resource-intensive.
Solution: The generative AI solution improves this process by automating online interviews with an AI-powered chatbot. No more manual scheduling of interviews and no more in-person interviews; instead, hundreds of interviews can be done at the same time. AI transcription and automatic organization of the data decrease the manual effort for insights derivation. The whole process accelerates.
Pain point 2: Traditional surveys are bound by the number of interviews a human team can carry out.
Solution: AI-driven interviewing will have hundreds and thousands of interviews carried out at scale, where the traditional method is bound. Because AI handles conversations with efficiency and consistency, for the same amount of time taken to interview just a very few people using traditional methods, significantly larger sample sizes can be reached with maintained quality of data collection.
Pain point 3: Manual transcription, coding, and analysis of survey responses can take weeks or even months, which postpones the time to insight.
Solution: The AI system will transcribe and process this data in real-time. It can identify patterns quickly, segment responses, and generate detailed reports. Companies can derive actionable insight in a fraction of the time it would take using traditional methods by automating such processes.
With AI-driven automation, these pain points disappear. Scale interviews are conducted by the chatbot, and the AI model performs transcriptions and insight extractions uniformly more accurately, and speedily. This frees researchers to focus their talents on strategic and creative work rather than administrative burdens. Better still, AI-driven solutions learn and improve with each additional wave of training, so they can surface valuable insights even better and deliver business-critical intelligence.
Combining AI and LLMs for market research
Our solution deploys AI powered by large language models (LLMs) to conduct in-depth qualitative research by engaging users in online interviews. In a virtual session, this AI-driven chatbot simulates the natural flow and depth that such conversations would have if guided by a human: asking open-ended questions, elaborating on them, and adapting its responses based on user inputs. For example, in our case study, the chatbot studied users on practices related to digestive health without suggesting any particular end to a conclusion so as not to prejudge any biases during data collection. It was told about the reasons why people employ activated charcoal treatments, from whom it was suggested, and the emotional and belief-related experiences associated with such a treatment.
It fine-tunes the asking of questions: precise, relevant, rephrased for clarity, and which keeps the engagement going. Such adaptive questioning emulates the way experienced interviewers delve deeper into a response without human fatigue, bias, or inconsistency. The generative AI, therefore, conducted consistent, scalable, high-quality interviews whose rich data were analyzed.
Getting insight in seconds, not weeks
Traditionally, qualitative would be constrained by resource issues, usually capping interviews at about 20 participants. This number, marketers argue, is sufficient to identify broad patterns, although it may overlook important nuances. Our AI solution flips this paradigm on its head by allowing hundreds or thousands of interviews in the same amount of time. The true innovation really lies not just in scalability but in the depth of analysis and speed of insight. It performs the transcription of data, analysis of responses, and organization of insights into comprehensive, easy-to-digest formats, such as tables and reports after every interview. Instead of weeks of researchers’ work, our solution makes the entire process happen in mere seconds.
This capability gives organizations unparalleled access to rich consumer insights. Marketers love presenting data in some order because it simplifies decision-making and helps formulate an effective messaging strategy. The AI will pick up commonalities, divide users based on behaviors, and outline patterns that might be very hard for a human to see. Such insights might be the system picking up that a large proportion of users rely on certain remedies based on the advice of family members, which shows key emotional and cultural associations.
Expanding benefits across industries
This solution goes beyond the benefits of pharmaceuticals by serving any business with a high level of marketing involvement. For example, in the highly competitive world of probiotics, where products are almost similar in nature, it all comes down to product differentiation. Marketers are constantly on the lookout for new channels and messages to connect better with consumers or for pain points to further address. Utilizing generative AI qualitative research, businesses are allowed to develop nuanced consumer preferences, craft messaging strategies, and overcome competition.
See a few examples of industries that benefit from employing Gen AI for market research:
The solution is beneficial to businesses in the technology sector, in attaining the perspective of how consumers view new products and technologies where innovation is a serious competitive factor.
Understanding how consumers make buying decisions is of the essence in the retail and e-commerce space. Such an AI-enabled approach may provide an identification of key touchpoints within the customer journey, whether online or in-store.
Other big beneficiaries of this technology are industries that provide complex services, financial services, or telecommunications because it enables large-scale qualitative studies to be done at a fraction of the cost and time.
In each of these industries, the generative AI solution gives businesses the power to transcend generic market surveys and consider a far more in-depth and comprehensive view of one's customers.
The future of market research with AI
Our generative AI solution represents a sea change in the fast-moving market research landscape. It empowers companies to make data-driven decisions more efficiently and precisely by interviewing side-by-side with pattern extraction, delivering actionable insights at unprecedented speeds. This opens an entirely new frontier for compelling insight into consumer behavior and is redefining the way businesses relate to their audiences and position themselves for success.
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