Market research with artificial intelligence: the definitive guide for companies that want to decide faster

In summary, market research with Artificial Intelligence uses Machine Learning algorithms and language models to collect, process, and generate insights in hours, not months. Companies such as Bradesco, Nestlé, and Banco do Brasil already use this approach in Brazil, with reductions of 97% in research time and 93% in cost per respondent. This guide explains what changed, how it works, and how to start.

Market research was built for a world that no longer exists

In 1970, a four-month market-research cycle was completely reasonable. The market moved slowly. Consumer behaviors changed over decades, not quarters. A study conducted in March was still relevant in October.

That world is over. Consumer trend cycles have shortened from years to months. Digital platforms create and destroy categories in weeks. The Brazilian consumer of 2026 made a purchase decision yesterday based on content discovered today, and may change their mind tomorrow.

Conventional market research, in large part, still operates in the 1970s paradigm: panel recruitment, fieldwork, manual analysis, PDF report. The process works; it just no longer keeps up with the pace of business.

This is the gap Artificial Intelligence came to solve. Not as a replacement for research, but as a radical accelerator of the cycle between question and answer.

What changed in market research with the arrival of AI?

The change is not only speed. It is a paradigm shift. To understand what AI brought, it helps to see the evolution of the four major market-research models that coexist today:

Source: a16z, evolution of paradigms for becoming customer centric.

Galaxies operates in the last two models: AI-native research for fast validations and simulation with generative agents for complex strategic decision scenarios. In practice, this means that the time between question and answer fell from months to hours, without sacrificing insight depth.

How does market research with AI work?

The process has fewer stages than traditional research, and each stage is faster. The simplified flow:

1. Collect real data. Questionnaires, interviews, CRM, or previous client research feed the model.

2. Model with Machine Learning. Data are organized into clusters that represent real market segments, with pre-model statistical validation.

3. Generate synthetically with LLM. Language models expand the respondent base and create personas capable of answering questions in natural language.

4. Validate post-model. Automated tests verify quality, consistency, absence of hallucination, and alignment with the original data.

5. Produce actionable insight. The user talks to personas, tests hypotheses, compares scenarios, and receives answers in hours, not in 80-page reports delivered weeks later.

The four types of research transformed by AI

1. Synthetic quantitative research

Equivalent to traditional quantitative research with a respondent panel. With Synthetic Personas, the sample can be expanded from 30 real respondents to 600 or more representative personas, maintaining the statistical distribution of the original group. The result is a robust quantitative base in hours, not the three to six weeks traditional fieldwork would take.

2. Synthetic qualitative research

Equivalent to in-depth interviews. The user talks directly to personas in natural language, asks open-ended questions, explores motivations, and receives contextualized answers aligned with each segment profile. No recruitment, no moderator, no transcription.

3. Stimulus analysis, or synthetic focus group

Equivalent to focus groups for testing creatives, concepts, and packaging. The material is submitted to personas, which evaluate perception, clarity, attractiveness, and purchase intent. The client receives the analysis in hours, not after two weeks of moderation, transcription, and analysis.

4. Predictive simulation

Exclusive to the AI approach. It allows hypothetical scenarios that traditional research cannot address: “If I change price by 15%, how does each segment react?” or “If a competitor launches a similar product, what is the migration probability of each cluster?” This type of insight is only possible with generative agents calibrated with real data.

The benchmarks that make a practical difference

Abstract metrics do not convince finance directors. That is why the numbers below come from real Galaxies client cases, not market estimates.

Which companies use market research with AI in Brazil?

Adoption of AI-powered market research in Brazil is still in the early-majority phase. Companies that have already adopted it have a real competitive advantage over those still operating exclusively with traditional methods. Among Galaxies platform clients:

• Bradesco Seguros: new-product validation with 600 synthetic respondents in 48 hours, 93% savings, and a 10.5x faster launch.

• Banco do Brasil: market research with synthetic data for strategic decisions, with full compliance with financial-sector regulatory requirements.

• Nestlé: launch validation and positioning for CPG portfolio products.

• O Boticário: concept, packaging, and communication tests with Synthetic Personas segmented by beauty-consumer profile.

• TikTok: creative segmentation and validation for user-acquisition campaigns, with 52% CAC reduction and 70% acceleration in creative improvements.

Is market research with AI reliable?

This is the question every manager evaluating adoption inevitably asks. And it deserves an honest answer: it depends on the methodology.

Generic AI applied to research — models that invent personas from public internet data, without a verifiable empirical base — produces results that look plausible but are not reliable. This is a real market risk.

The Galaxies approach is structurally different because it starts from real data, statistically validates input quality, tests results with an independent framework, DeepEval, and offers complete methodological transparency. The 91% accuracy versus real human respondents is not a marketing promise; it is the result of a control group comparing persona answers with real people’s answers to the same questionnaire.

Reliability exists when the methodology is rigorous. What managers need to evaluate when choosing an AI research solution is not whether AI in general is reliable, but whether that specific methodology has verifiable quality controls.

How to start: the step-by-step path to implementing market research with AI

In a direct five-step answer: (1) map the strategic decisions that need data; (2) identify research or data already available in the company; (3) define the business questions that need answers; (4) create Synthetic Personas representative of the relevant audience; (5) use insights for decisions in hours, not months.

Step 1, map the decisions that need data

Start with decisions waiting for approval and currently made more by intuition than data: product positioning, price decision, channel choice, or campaign brief. Each decision has a cost of being wrong, and Synthetic Personas reduce that risk in hours.

Step 2, identify available data

Galaxies works with data most companies already have: NPS surveys, CRM data, satisfaction surveys, and transcripts from previous interviews. The more real data the company provides, the more precise and personalized the generated personas become.

Step 3, define the business questions

Research without a clear question generates a report, not a decision. Before anything else, define what you need to know to make the next decision. The clarity of the question determines the relevance of the insight.

Step 4, create the personas and start researching

With available data, the platform creates the personas in up to 48 hours. From there, the team starts asking questions, testing hypotheses, and comparing scenarios in real time.

Step 5, use the insight to decide

The goal is not a report. It is a decision. Synthetic Personas were designed to support decision-making, not to add another layer of analysis that stays in a drawer.

Frequently asked questions

What is market research with artificial intelligence?

It is the application of Machine Learning and language models to collect, process, and generate market insights in hours, not months. It includes Synthetic Personas, predictive analysis, and scenario simulation, with 91% accuracy compared with real human respondents.

What is the difference between AI research and traditional research?

Traditional research takes weeks or months and has a high cost per respondent. With AI, results arrive in hours, with cost up to 93% lower, unlimited scale, and 24/7 availability. Quality is certified by double statistical validation.

Is market research with AI reliable?

When based on validated real data, yes. Galaxies uses double statistical validation and presents 91% accuracy compared with real human respondents, verified by independent control-group tests.

Which companies use market research with AI in Brazil?

Bradesco Seguros, Banco do Brasil, Nestlé, O Boticário, and TikTok are confirmed clients of the Galaxies platform. Each uses the solution for sector-specific decisions.

How do I start doing market research with AI?

Identify the decisions that need data and the data available in the company. Galaxies offers a free demo to show the process in operation, with client data or sample sector data.

The gap between question and answer is closing

For decades, the interval between “we need to know what consumers think” and “here is the answer” was measured in months. This interval was accepted as the operating cost of the business, something structural and inevitable.

Not anymore. With market research with AI, the interval is measured in hours. This changes not only the research process, but the speed at which companies can iterate, adjust, and make better decisions than competitors.

The companies that discovered this first already have an advantage. Those that discover it later will run to recover ground. The time to start is now.

Discover the Galaxies platform, market research with AI in 48 hours!

See clients already using it: Nestlé, Bradesco, TikTok, Banco do Brasil