Artificial Intelligence (AI) has become prevalent in business applications and social media, but you might still be wondering about its role in market research. AI market research tools exemplify how AI and machine-learning algorithms are transforming industries through intelligent and efficient processes..
New Advances in Market Research AI
AI for market research is continually evolving, making it an exciting time for researchers aiming to achieve more with less effort.
Generative AI
Generative AI (Gen AI) models can create text, images, code, and other media in seconds. A notable example is ChatGPT, which can generate text, provide research on specific topics, and even tell jokes. For market researchers, Gen AI helps quickly research topics, provide a survey foundation, or determine the best survey layout—all from a few prompted words, showcasing its efficiency.
Synthesizing AI
Synthesizing AI (Synth AI) takes large datasets or extensive information and summarizes them for faster and cleaner analysis. Research teams can use Synth AI for insight summaries, quick data analysis, knowledge management, and report creation. Both Gen AI and Synth AI are modernizing market research by making it less tedious and more efficient, allowing researchers to focus on strategic storytelling from insights to make data-driven decisions.
Six Widely Used Cases of AI and Machine Learning in Qualitative Market Research
Here are six practical use cases of AI for market research:
1. Survey Ideation
AI tools can help generate ideas and questions for surveys, ensuring high data quality and actionable insights. This is particularly useful for advanced methods or product innovation studies when exploring new target audiences.
2. Survey Programming
AI can automate the logic programming of survey questionnaires. Platforms offer drag-and-drop pre-programmed survey questions and advanced research methods, speeding up the process from concept to fieldwork and decision-making. AI also predicts the length of interviews (LOI), enhancing participant experience.
3. Data Collection and Analysis
AI tools streamline data collection and analysis, allowing researchers to focus on insights and stories from the data. Many AI tools automate the analysis of various research methodologies, enabling users to spend more time on findings rather than on analysis. AI can also generate predictive analytics to forecast market trends.
4. Data Reporting
AI can populate real-time data, enabling early insights analysis before fieldwork completion. AI-generated chart titles and descriptions further reduce the time from survey launch to stakeholder delivery.
5. Qualitative Analysis
For qualitative research like focus groups or online interviews, AI can quickly perform emotion or sentiment analysis and extract key insights using natural language processing (NLP).
6. Customer Support
AI serves as a co-pilot, supporting researchers throughout the research process from planning to final reporting. AI allows researchers to be more hands-on while providing assistance, freeing up time for additional projects or supporting other business needs
Conclusion
Choosing the right methods and tools in market research is crucial for obtaining important and valid insights. AI and machine learning are revolutionizing market research by making processes more efficient and insightful. By integrating AI tools, researchers can focus on strategic storytelling and make decisions that drive success. While AI can assist with many steps in market research projects, it cannot completely replace quantitative and qualitative research where human intuition and analysis are essential. The role of AI and machine learning in market research should be about enhancing human processes rather than entirely replacing them
