Simplifying AI for Product Experience: A Framework for Faster, Better Insights

Navigating AI’s complexity in FMCG insights and R&D can feel overwhelming. You're constantly bombarded by suppliers promising the "next big thing," facing fragmented data sources and siloed teams, and often struggling to authentically understand what truly shapes consumer decisions in-the-moment. The real challenge is uncovering insights that foster empathy and drive impactful decisions.

To simplify this landscape and make it easier to understand where best to implement this exciting technology to maximise value, we've developed a clear, actionable framework around three essential pillars: Create, Connect, and Synthesise.

Create: Harnessing AI to innovate and translating insights into tangible outputs

Connect: Using AI to deeply engage consumers at scale, enabling more authentic and meaningful interactions.

Synthesise: Converting extensive, complex unstructured datasets into clear and actionable insights, enabling faster decision-making at scale.

AI to Connect: Enhanced Data Collection

MMR’s Conversational AI tools, particularly research chatbots, have significantly elevated how researchers engage with participants, unlocking richer insights at scale. We’ve developed these tools to capture consumer stories, feelings, and expectations:

• Survey Bot: Enhances traditional quantitative surveys by deepening responses to open-ended questions.
• Sensory Bot(coming soon!): Incorporates MMR’s specialized sensory science expertise to systematically dissect and analyze detailed product experiences.
• Q.Bot: An end-to-end chatbot engagement to amplify qualitative depth with scale.

We’ve been blown away by the versatility and impact of Q.Bot. Clients are reaping the benefits across all sorts of research scenarios, using the tool to access challenging locations and better engage with younger demographics like Gen Z and Gen Alpha.

Q.Bot's fundamentally open engagement approach helps identify what truly matters to consumers, uncovering hidden white space and innovation opportunities. Check out some of the recent use cases for Q.Bot...

Voice in chatbots

We have already demonstrated the transformative potential of voice technology in consumer and sensory research, and voice responses are now available across all our chatbot solutions. This enables hands-free, authentic, and immediate consumer feedback, allowing participants to naturally express nuances of their product experience, enhancing empathy, accessibility, and revealing deeper insights into consumer preferences, motivations, and frustrations.

Product efficacy over time, anytime!

We've developed methods integrated seamlessly with our chatbot platforms to measure perceived product efficacy over time. Chatbots allow consumers to conveniently capture in-the-moment reactions at specified intervals, offering valuable insights such as:

• Food: Perceived levels of satiety
• Functional beverages: Changes in energy or relaxation
• Skincare: Hydration and moisture retention
• Hygiene & Personal Care: Freshness or cleanliness perception
• Household & Cleaning: Odour control and freshness
• Healthcare: Symptom or pain relief

Leveraging chatbots for this longitudinal feedback helps us answer key questions:

• How does consumer perception of product effectiveness evolve over time?
• How do usage patterns impact perceived performance?
• Are product marketing claims aligned with consumer experiences?
• How does perceived efficacy compare with competitors across usage periods?

This conversational AI-enabled approach makes capturing and analyzing dynamic in-use product experiences effortless and scalable, while ensuring deeper, continuous insights into real-world consumer perceptions.

BeSci techniques with chatbots: Future thinking & Scenario planning

We also integrate behavioural insights techniques such as Future Thinking Priming (FTP) into our chatbots. FTP significantly increases consumer engagement, prompts richer qualitative responses, and encourages participants to think more vividly and specifically about their future interactions with new product ideas. This technique has demonstrated notable success, particularly in engaging younger demographics and improving the depth of responses among traditionally harder-to-reach cohorts, like male participants or Gen Z.

We are currently piloting techniques to pressure test whether scenario-based' future thinking priming is a viable technique for testing new product prototypes. Do reach out if you’d like to know more.

Looking ahead, AI will soon evolve from capturing voice responses to facilitating intelligent conversations through lifelike avatars. Initial experiments demonstrate that avatars significantly increase participant engagement, thus yielding richer, more actionable data.

Although device compatibility and consistency remain challenges, voice-enabled interactive avatars offer enormous potential for immersive, real-time exploration of consumer-product interactions.

Further into the future, continuous data streams from always-on devices such as wearable pendants or smart glasses will enable researchers to tap into constant, contextually rich streams of consumer data.

Devices designed for real-world environments, like those addressing social connectivity (e.g., "Friend"), could revolutionize real-time consumer understanding and unlock unprecedented levels of insight through continuous monitoring and interaction.

Seek ways strengthen your consumer understanding using AI on your next project. Get in touch for inspiration on how to achieve this.