AI's transformative role in amplifying human insights

New Delhi: The recent webinar hosted by the Market Research Society of India (MRSI) titled "Amplifying Human Insights with AI," brought together industry leaders to explore the transformative impact of artificial intelligence (AI) on market research. 

The panel featured Shaveta Bhardwaj, Co-founder and CEO of SprintStudio.ai; Preriit Souda, Director, Data Science, PSA Consultants; and Vinay Virwani, Head - Consumer Insights, Dabur. Together, they shared their insights and experiences on integrating AI into market research.

Bhardwaj spoke during the initial part of the session, raising a compelling question: "What’s your AI code?" She urged attendees to reflect on their organisations' approaches to AI deployment. She noted that while "97% of business leaders are talking about the urgency to deploy AI in the next six months," a staggering "86% (Cisco AI Readiness Index study) say they’re not fully prepared." Addressing the barriers to adoption, she stated, "Culture eats strategy for breakfast," emphasising the importance of organisational culture in successfully implementing AI.

Highlighting India's position in the AI landscape, she pointed out, "Indian GenAI startups have had record growth 3.6 times over a short period," positioning India sixth globally (Nasscom India’s Generative AI Startup Landscape 2024). However, she noted, "India's AI country readiness is low, and so is the investment," indicating significant hurdles that need to be overcome. She elaborated on the explosive growth in the AI sector, stating, "The largest growth is really coming from building AI assistants specifically for a particular industry, followed by productivity tools." She emphasised the importance of being proactive in developing AI strategies that are not just about adopting technology but about fostering a culture that embraces change.

As she would call it, "LLMs agents today," are where users type queries into AI tools and receive direct answers— termed "zero shot mode," Bhardwaj elaborated, "In the future, agentic workflows will enable AI to think, iterate, research, and revise its responses." This capability will transform user interaction, providing a more dynamic and responsive experience. "This is happening now," she asserted, signalling the rapid advancement in AI technology.

As the discussion progressed, Vinay Virwani shared his perspective on the FMCG sector. He illustrated AI's growing role by noting the public's misconceptions about AI’s capabilities, drawing a parallel to personal experiences with music curation: "I still get questions when I'm playing some music in my car. Did you curate the playlist? I have to tell people that it’s not that I have curated a playlist." This highlights the need for FMCG firms to leverage AI effectively in their insights functions, as understanding consumer preferences is more critical than ever.

Virwani outlined five key areas where AI has been effectively utilised in FMCG:

• Insights Function: AI assists in data collection and processing, analysing consumer sentiment through social listening.
• Market Mix Modelling: By deriving cause-and-effect relationships, AI helps predict marketing outcomes based on investment levels.
• Programmatic Targeting: AI identifies potential consumers based on their preferences and behaviours, enabling targeted marketing strategies.
• Predictive Analytics: AI simulates various market scenarios to optimise pricing and promotional strategies.
• Price and Promotion Models: AI analyses historical data to determine optimal pricing strategies and promotional effectiveness.

Virwani noted the evolution of sentiment analysis, stating, "Not just bucketing different sentiments, but analysing them—whether it's positive, anxious, or something else—has also evolved significantly." Understanding consumer sentiment through AI can lead to more tailored marketing approaches, ensuring that brands resonate with their target audiences.

Souda then provided practical applications of data science and AI, emphasising their role in long-term strategic planning. He shared examples of projects undertaken by his team, starting with a small to mid-sized Indian manufacturer of construction materials seeking to expand internationally. "We analysed shipping data to understand global cargo movements and linked that with economic dynamics and government data to inform targeted strategies," he explained. 

He highlighted the importance of integrating diverse data sources to create comprehensive insights, noting, "By combining economic trends with actual shipping patterns, we were able to predict market shifts effectively."

He also discussed an algorithmic simulator designed to understand the evolution of a premium product category over the next 15-20 years, combining macroeconomic factors with 30 years of digital search data. "Our work is not just about immediate insights but about building a roadmap for the future," he emphasised, pointing out the necessity of long-term vision in strategic planning.

For Mars Wrigley, Souda and his team explored the fast delivery ecosystem across multiple countries. "We reverse-engineered how algorithms influence consumer behaviour by analysing e-commerce reviews and linking them with consumer feedback to develop strategies," he noted. This reflected the value of understanding consumer behaviour through AI, stating, "This analysis not only informs product development but also enhances customer experience by aligning with consumer needs."

The need is to enable AI in a way that it can augment human intelligence. "It's not going to be just AI; it’s going to be AI plus human," Bhardwaj said, highlighting the strengths of AI—speed, scale, pattern recognition, and cost efficiency—compared to the human strengths of emotional intelligence, contextualisation, and ethical judgment. She remarked, "What can AI bring to the table? Speed. It's a scale. It's pattern recognition. It's predictive data."

Bhardwaj further elaborated on their developments at SprintStudio, saying, "We built Conversation Studio AI, which transforms qualitative conversations into transcription and summarisation, making processes significantly faster." This innovation addresses the pain points in traditional qualitative research methods, allowing for immediate insights.

For Souda, recalling the importance of collaboration between AI and human researchers was much needed. "We need to ensure that AI tools are built with researchers in mind," he noted, emphasising that tools should align with the workflows and needs of users. "The right technology can enhance our capabilities, making us more efficient and insightful." He also highlighted, "A key aspect is ensuring that the insights generated from AI are actionable and can inform decision-making across all levels of an organisation."

Bhardwaj stressed the importance of creating a researcher-driven AI platform rather than merely applying existing technologies without consideration of industry needs. "We had to build something that was really a process that we can follow to give it to the last mile," she explained. Quality and rigour were key focuses in their development, ensuring that the tools aligned with the actual workflows of researchers.

The panellists emphasised the critical need for organisations to evaluate their AI readiness and adapt their cultures to embrace this technological landscape. They set the stage for deeper consumer understanding and innovative strategies that can drive business success in the years to come.

Bhardwaj’s opinion formed a crucial part of the audience’s takeaway, as she reiterated the importance of understanding the problem at hand: "What is the problem that you're solving? It really begins with that. So go identify your AI code to transform in the future."