The effects of Artificial Intelligence (AI) on the Market Research industry
By now, you’re probably familiar with Artificial Intelligence (AI) technology, as it’s become increasingly prevalent in business applications and social media. However, you might still be curious about AI’s role in market research. AI market research tools exemplify how AI and machine-learning algorithms are transforming industries through intelligent and efficient processes. Below, we explore how AI tools are reshaping market research and their future potential.
Existing AI Applications in Market Research
In today’s digital market research landscape, many providers rely on AI for efficient data cleaning, predictive insights, text and data analysis, and more. AI is so seamlessly integrated into these platforms that you might not even realize you’re using it.
If you’ve ever utilized intuitive survey building features (like drag & drop modules), length of interview (LOI) prediction tools, automated data cleaning filters, automated analysis of advanced research methods, or real-time charting solutions, you’ve been benefiting from AI. Compared to the traditional manual and tedious market research processes, AI has brought us a long way. Yet, AI continues to advance in market research.
Recent Advances in Market Research AI
AI for market research will only keep evolving, making this an exciting time for researchers who want to achieve more with less.
One clear example is Generative AI (or Gen AI), which creates text, images, code, and other media in seconds. A popular GenAI tool is ChatGPT. ChatGPT can generate text, list bullet points, provide research on a topic, and even tell a joke! For market researchers, Generative AI helps quickly research a topic, lay the foundation for surveys, or determine the best survey layout – all from a few prompts.
Beyond generating information, AI can synthesize it. Synthesizing AI (or Synth AI) processes large data sets and summarizes them for faster, cleaner analysis. Research teams can use Synth AI for insights summaries, rapid data analysis, knowledge management, and report creation.
Both Gen AI and Synth AI modernize a traditionally labor-intensive industry, enabling researchers to focus on strategic insights for data-driven decisions.
Six Use Cases of AI in Market Research
Here are six practical applications of AI in market research to support your research team throughout the insights process:
- Survey Ideation: AI tools can generate ideas and questions for surveys, ensuring high data quality and actionable insights, especially useful for advanced methods or product innovation studies.
- Survey Programming: AI can automate the writing and programming of survey logic. Some platforms offer pre-programmed survey questions or advanced methods for drag & drop use, speeding up the transition from concept to fieldwork to decision-making.
- Data Collection and Analysis: AI tools streamline data collection and analysis, allowing researchers to focus on insights. mypinio uses AI to automate the analysis of descriptive and advanced research data, so users spend more time on findings rather than analysis. AI can also generate predictive analytics to forecast market trends.
- Data Reporting: AI tools can populate real-time data, enabling early insights analysis before fieldwork concludes. Set up charts to be populated automatically as respondents complete your survey. AI can even generate chart titles and descriptions, expediting the process from survey launch to stakeholder delivery.
- Qualitative Analysis: For qualitative research like focus groups or video interviews, AI can perform emotion or sentiment analysis on consumer responses, extracting key insights using natural language processing.
- Customer Support: AI can serve as a co-pilot, assisting throughout the research process from planning to reporting. It supports researchers who prefer hands-on involvement but need help along the way, freeing up time for additional projects or business needs.
Market Research Tasks Beyond AI’s Reach
Despite AI’s transformative impact, certain aspects of market research still require human intervention:
- Strategic Consulting: Human-to-human discussions are essential for personalizing consumer insights.
- Data Scientists: Skilled professionals are needed to set up AI integrations, troubleshoot issues, and improve features.
- Relationship Building: Successful market research relies on relationships with panel partners, software integrations, and other external elements.
- Full Project Execution: AI can assist with steps but cannot fully replace the execution of quantitative and qualitative research projects.
AI should enhance human processes, not entirely replace them.
The Overall Positive Impact of AI on Market Research
Consumer trends evolve rapidly, challenging businesses to keep up. Executives increasingly demand real-time, high-quality insights, putting pressure on market researchers. AI technology can take over tedious tasks like data cleaning, chart input, statistical analyses, and report creation. This allows researchers to focus on analyzing consumer behavior insights to support strategic initiatives.
AI’s impact on the market research industry includes automation, transformation, and the emergence of new roles.