Dairy Leader: Disrupting Market Research with AI Synthetic Users, Achieving 100x Speed

Overview

For a global dairy giant, understanding granular consumer preferences in the fast-paced bakery and food service sectors is critical. Traditional market research methods, while thorough, were becoming a bottleneck due to their inherent slowness and high cost. To maintain agility and deeper consumer empathy, they collaborated with Tezign to pioneer an AI-native research approach using "Synthetic Users," aiming to break through the "Slow, Expensive, Narrow" limitations of conventional studies.

Challenge

The consumer research department faced a systemic "Iron Triangle" of constraints: Speed, Cost, and Quality/Depth. Traditional offline questionnaires and consulting projects typically took weeks or even months to complete. The financial cost was prohibitive, often ranging from 100,000 to over 500,000 RMB per single study, limiting the frequency of research.

Furthermore, the sample size in traditional focus groups is often limited, leading to unstable feedback quality and potential bias. For specific projects like "Western Pastry Consumer Purchase Behavior," getting deep, authentic insights from a specific demographic (e.g., middle-income females aged 25-45 in Tier 1-2 cities) was logistically difficult. The brand needed a way to predict consumer reactions to new products, advertisements, or packaging rapidly without sacrificing the depth of qualitative insight.

Solution

The company adopted Tezign’s atypica.AI solution, fundamentally transforming research from "Sampling" to "Simulation." This AI-native research agent employs a 4-step workflow to conduct large-scale, high-fidelity consumer simulations:

1. AI Debrief (Requirement Deconstruction): The system automatically deconstructs broad, vague research objectives into specific, executable research plans. It precisely targets demographics (e.g., defining the exact profile of the target consumer) and outlines the research methodology.

2. AI Persona (Synthetic Users): Instead of recruiting real humans, the system generates high-fidelity "AI Personas" (e.g., "Urban Exquisite Lifestyler," "Quality Family Guardian"). These are not simple chatbots; they are digital entities initialized with specific demographic data, psychographic traits, preferences, and biases, simulating real human decision-making logic.

3. AI Interview (Intelligent Probing): The system conducts concurrent, high-speed interviews. An AI Interviewer engages with AI Personas (or real humans) in deep dialogue. Unlike static surveys, the AI Interviewer can dynamically probe for deeper reasons ("Why do you prefer this texture over that one?"), ensuring qualitative depth at a quantitative scale.

4. AI Analysis (Automated Synthesis): The system automatically synthesizes massive amounts of interview data. It identifies trends, extracts key viewpoints, and generates comprehensive reports like the "Western Pastry Consumer Insight Report" with minimal human intervention, turning raw text into structured strategic insights.

Result

The shift to AI-native research delivered transformative efficiency gains. The company achieved a 100x increase in research speed, compressing what used to be months of work into days or even hours. The cost of research was reduced by approximately 60%, allowing the brand to conduct research more frequently and on more topics.

The system successfully covered over 1,500 survey samples and conducted 100+ in-depth interviews, identifying 4 major consumer personas that are now driving product strategy. This case proves that AI can not only execute tasks but can simulate the subjective world of consumers, democratizing high-quality market insights and making them accessible in real-time.