From weeks to hours, from static data to dynamic simulations, AI is reshaping the underlying logic of user research with disruptive efficiency. This article focuses on cutting-edge AI research practices at home and abroad, and provides an in-depth analysis of how generative agents build virtual users and simulate decision-making links, so that “insight” can move from lagging to real-time, providing a new paradigm for product, marketing, and strategic decision-making.
Now, the product optimization or new product launch of major brands has poked your heart? Those moments that make you exclaim “understand me” are likely to be behind themResults from in-depth AI analysis and insights.
At the moment when AI technology is developing rapidly, the wave of AI has also hit the field of consumer researchCapital and companies are accelerating their influx into this track, and those teams with a keen sense of smell have taken the lead in gaining the favor of capital with the most cutting-edge technology and drank the “first bite of soup”.
- Outset：Successfully developed an AI host, conducted in-depth interviews with research participants through video, and the market research project that traditionally took weeks to complete in a few days, just completed a $17 million Series A financing;
- ListenLabs：Secured $27 million in financing with AI-powered voice interview technology, which can process thousands of customer voice interviews simultaneously and output in-depth insights within hours;
- Whobot：Domestic AI phone digital employee companies can provide intelligent call services such as intention mining, product sales, and service communication based on enterprise needs, and have recently completed tens of millions of yuan in Series A financing.
The a16z team, a top venture capital firm in Silicon Valley, also recently released a research report titled “FasterSmarterCheaper: AIIsReinventingMarketResearch”, revealing that AI is reconstructing the market research industry ecology with disruptive forces, which is predictableIn the future, AI research companies will gradually replace expensive manual investigation and analysis processes.
AI-Powered Consumer Research: Efficiency Enhancement and Model Restructuring
Why is AI-driven consumer research favored by capital and enterprises? At its core,AI has fundamentally subverted the operational logic of traditional research– AI can quickly generate research reports tailored to business scenarios and provide initial insights that can significantly improve efficiency while significantly reducing costs.
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Unlike traditional research that has long faced the pain points of slow progress, sample bias and lagging insights, global companies spend as much as $140 billion on market research every year,By providing timely and accurate customer insights, AI helps enterprises effectively capture user needs, make product iterations highly consistent with user demands, and at the same time explore more product innovation opportunities, break the homogenization with differentiation, and ultimately drive brand growth.
AI-driven consumer research is reshaping the value of the industry through three major breakthroughs:
1. Time Compression:Traditional research takes weeks of analysis reports, but AI can complete it in hours;
2. Cost Reduction:Relying on large models and software to replace manpower, small and medium-sized enterprises can also afford enterprise-level research;
3. Scene penetration:From product, research, marketing to sales, customer service, customer service and other teams, it can be used by multiple departments of the enterprise.
Generative Agents: A further breakthrough in AI consumer research
Although AI has revolutionized consumer research, the a16z team pointed out that conventional AI research will still be limited by the variability and difficulty of obtaining human samples.The emergence of generative agents is breaking this limitation——The Outset and ListenLabs companies mentioned at the beginning of the article have begun to develop virtual user groups based on AI large language models to achieve in-depth demand insights by simulating users’ real consumption behavior.
The concept of “Agent” comes from the paper “Generative Agent: Interactive Simulation of Human Behavior”, which is centered on the construction of virtual characters with memory, reflection and planning capabilities through large language models.
The following example can help you understand the concept of “Agent” more intuitively:
A French beauty brand built 10,000 agents based on Gen Z and millennial consumer modeling before the launch of new products: each agent was implanted with multi-dimensional data such as customer reviews, CRM history, social media topic sharing, and past purchase behavior, and these virtual entities could shop independently, express product opinions, and interact with other agents in simulated scenarios. Through their 24-hour “life”, they can react to market changes, form new preferences, and even be influenced by other agents. This continuous simulation allows businesses to track the long-term evolution of their consumption trends, rather than just capturing the state of consumption at a static point in time.
The continuous evolution of agents relies on rich qualitative data(such as user interviews or behavioral trajectories), this information builds the agent’s “memory framework”, allowing it to iteratively upgrade with experience accumulation and contextual feedback – by injecting behavioral history, environmental clues, and decision-making logic, the agent can generate more delicate and realistic interactive responses, realizing the leap from data simulation to behavior simulation.
A new stage of consumer research: the synergistic drive of AI automation execution + expert decision-making intervention
The a16z team found that current leading AI research companies are adopting a new hybrid research model:AI automated execution + expert decision-making intervention。 In other words, the core research process is automated by AI, but key decisions are made by a team of enterprise experts.This model not only retains the efficiency and cost advantages of AI but also ensures the quality and accuracy of insights——As AI technology continues to iterate, AI will gradually take over more repetitive tasks, while enterprises and experts can focus on higher-value strategy formulation and business decision-making.
Since then, enterprises no longer need to rely on high-priced one-time research reports for regular purchases, but have obtained a lower-cost, continuous dynamic insight engine – AI can not only respond to new research questions and track changes in market trends in real time, but also trigger early warnings at key nodes such as changes in consumer behavior and industry patterns.Achieve qualitative change from “insight lag” to “forward-looking forecast”.
At present, many teams have captured the transformative potential of AI technology in the field of consumer research, making AI-driven consumer research products explode:
- Aaru: Building a multi-agent AI system that accurately simulates human behavior based on proprietary and public data sources, can quickly generate behavior predictions for customer audiences, help optimize customer experience, explore growth opportunities, and shorten product time-to-market, and has received investment from Accenture.
- Simile: A startup focusing on AI generative agent simulation, exploring user scenarios, predicting challenges, and optimizing solutions through AI systems with real human behavior characteristics.
- atypica. AI: Pioneering multi-agent system that builds virtual consumer groups and simulates real user decision-making paths through AI, and can output in-depth research reports.
- Velozity: Build AI characters based on user characteristics for focus group discussions and usability testing, supporting the validation of ideas, testing Figma prototypes, running A/B tests, and obtaining real feedback throughout the product development process.
- Decode: A consumer research platform integrated by InsightsAI (emotional AI + behavioral AI + generative AI + predictive AI) to capture multi-dimensional insights based on user behavior and sentiment data;
- Convo: Helping product teams conduct user research at scale by fully automating the qualitative user research process through AI, saving months of data collection and analysis time.
- Waveform.ai: Optimize the research experience through interactive voice AI, which is suitable for customer interviews, employee surveys, market research and other scenarios, and output more intelligent analysis insights;
- AudioForms: An AI-based voice survey tool that integrates audio into questionnaire design, allowing users to complete questionnaires through voice and improve survey participation.
- ClayLabsInc: AI-powered relationship management platform that can connect 20+ CRM systems and 75+ data sources to automatically complete the cleaning, deduplication and update of contact data, and has reportedly completed Series C financing;
- Intercom: An AI platform focused on customer service with FinAlAgent that automates complex questions, provides high-quality solutions, and takes action to resolve customer issues.
- CEM: An AI-driven customer experience management platform with its Al assistant that can obtain instant answers through conversational interaction and quickly generate insight reports adapted to business scenarios for different positions.
We firmly believe that the rise of AI is not only an iterative upgrade at the level of technology and tools, but also a subversive reconstruction of the operating logic of the entire consumer research industry. Therefore, those companies that adhere to the traditional research model are facing an existential crisis of being eliminated by the market, and those that take the lead in embracing and building an AI-driven consumer research system will dominate the industry.
Resources:
1.《FasterSmarterCheaper：AIIsReinventingMarketResearch》
2. a16z’s latest insights: AI is disrupting the $140 billion market research industry
3. Sequoia United States $27 million, betting on this Agent vertical scenario
4. Following Sequoia’s large bet in the United States, this AI track ushered in another $17 million in large financing
5. [$3 billion valuation] GTMAI agent platform Clay completed Series C financing, led by CapitalG, with a valuation increase of 6 times in half a year
6.AI Telephone Digital Employee Company “Whobot” completed tens of millions of yuan in Series A financing, and Xiangyang Capital served as the exclusive financial advisor|Xiangyang Transaction
