The Rise of Synthetic Research
From niche to multibillion-dollar growth: how simulating human behavior with AI is redefining market research
The Rise of Synthetic Research
What if you could test a new campaign, validate a product idea, or explore customer behavior without ever conducting a traditional survey?
That’s the promise of synthetic research — a fast-growing methodology that uses synthetic data and AI agents to simulate human behavior with remarkable realism.
Once a niche experiment in data science labs, synthetic research is now becoming one of the most transformative tools in technology. Fueled by the demand for innovation, tighter privacy regulations (like GDPR and LGPD), and the rapid evolution of generative AI, it’s reshaping how companies design products, test ideas, and understand people.
What Exactly Is Synthetic Research?
At its core, synthetic research uses AI-generated data and virtual agents to recreate human-like behaviors, preferences, and decision patterns.
Instead of collecting feedback from real participants, businesses can simulate thousands of responses in minutes — gaining insights faster, safer, and at a fraction of the cost.
Synthetic vs. Real Data
While traditional research depends on data gathered directly from people, synthetic data are artificially generated. They mimic real-world patterns but contain no personal information, which preserves privacy and ensures compliance with global data regulations.
Why It Matters
Synthetic research removes many of the bottlenecks of conventional research. It speeds up innovation cycles, cuts operational costs, and allows organizations to experiment freely — all without risking exposure of sensitive data.
It’s not a replacement for human input, but a powerful complement that helps companies learn, iterate, and validate faster.
A Market Poised for Exponential Growth
The synthetic research market is expanding rapidly. The broader synthetic data generation segment — which powers synthetic research — is expected to grow from around $390 million in 2025 to more than $4.6 billion by 2032, with annual growth rates above 30%.
Behind this acceleration are a few key forces:
- Global data-privacy regulations that limit the use of real personal data.
- The growing need for diverse datasets to train AI models.
- Advances in generative and conversational AI that make simulations more realistic.
- Lower costs and faster insights compared to traditional field research.
Together, these factors are turning synthetic research into a mainstream practice across industries.
Who’s Adopting Synthetic Research the Fastest?
Marketing and Market Research
Marketers are using synthetic research to simulate audience reactions before launching campaigns. They can test messaging, creative assets, and landing pages in controlled environments — refining strategies long before investing in large media budgets.
By 2028, experts predict that most marketing datasets will be built primarily from synthetic responses, thanks to the speed, scalability, and safety of this new model.
Product Development and UX Design
Product and design teams are leveraging synthetic agents to test user journeys and interface usability.
Imagine prototyping a new app interface and running a thousand synthetic interactions overnight — identifying friction points instantly and shortening months of iteration into days.
Regulated Sectors: Healthcare and Finance
For industries bound by strict data governance, synthetic research offers a breakthrough.
Hospitals and banks, for instance, can create synthetic datasets to model patient behaviors or financial transactions without ever exposing sensitive information. The result: compliance and innovation finally working together.
2025–2030 Outlook: What’s Next for Synthetic Research
AI-Driven Acceleration
With the rise of generative AI, research processes that once took weeks can now happen in hours. Synthetic respondents — AI agents that behave like real humans — can test ideas across diverse demographics, personas, and scenarios, driving personalization at scale.
Growing Strategic Influence
Teams that master synthetic research will increasingly shape strategic decisions, earning more visibility and investment within organizations. Research will no longer be a back-office function, but a driver of innovation and growth.
Redefining Roles and Skills
Traditional data collection will give way to modeling, simulation, and interpretation. Researchers will need to blend analytical thinking with AI fluency, collaborating more closely with data scientists and business strategists.
How to Bring Synthetic Research Into Practice
Step-by-Step Implementation
- Map your goals — identify what needs to be tested or validated.
- Choose the right platform — select a synthetic data or simulation tool aligned with your needs.
- Train your team — build familiarity with generative models and AI-based analytics.
- Generate and validate synthetic personas — ensure they reflect realistic patterns and diversity.
- Apply insights continuously — use findings to refine strategies, not just report them.
Common Pitfalls to Avoid
- Overlooking the quality and representativeness of generated data.
- Running synthetic studies disconnected from business objectives.
- Neglecting training and alignment across teams.
Myths and Realities
Myth: Synthetic research replaces traditional research.
Reality: It complements it — making human studies smarter, faster, and more targeted.
Myth: It’s only for large enterprises.
Reality: Scalable solutions now make it accessible for companies of any size or maturity level.
Measuring Success: Metrics and KPIs That Matter
How can organizations evaluate their synthetic research performance?
Here are key indicators that reflect maturity and ROI:
- Model accuracy — how closely synthetic results mirror real-world outcomes.
- Cost and time savings — measurable reductions versus traditional research cycles.
- Data diversity — broader, more inclusive datasets.
- Stakeholder satisfaction — how well teams trust and adopt insights from synthetic studies.
Traditional Research vs. Synthetic Research
| Aspect | Traditional Method | Synthetic Research |
| Collection Time | Weeks to months | Hours to days |
| Cost | High, sample-dependent | Lower, scalable |
| Privacy | Complex and risk-prone | Privacy-by-design, compliant |
| Data Quality | Variable, human bias | Controlled, requires periodic validation |
Why Synthetic Research Is Changing the Game
Synthetic research represents more than a technological advance — it’s a shift in mindset.
It enables experimentation without friction, creativity without constraint, and learning without limits.
Companies that embrace it are discovering faster ways to innovate, test, and adapt to change — turning uncertainty into opportunity. Whether you’re designing a new app, running a global campaign, or building a predictive model, synthetic research lets you move at the speed of your ideas.
Frequently Asked Questions
What drives the growth of the synthetic research market?
Rising privacy demands, AI evolution, and the pursuit of faster, more affordable insights.
Which industries are adopting it fastest?
Marketing, technology, healthcare, and finance lead the way due to their data intensity and regulatory complexity.
Does synthetic research ensure data privacy?
Yes — by using artificial data that replicate patterns without linking to real identities, it minimizes legal and ethical risks.
What challenges come with adoption?
Team adaptation, maintaining data quality, and integrating new methods with existing workflows.
How does it benefit marketing and product teams?
It enables agile testing, faster iteration, and more confident decision-making — all while reducing research costs.
Is it accessible to small and midsize companies?
Absolutely. With flexible, scalable tools, synthetic research is no longer limited to enterprise-level budgets.
MJV Can Help You Lead This Transformation
Synthetic research is no longer a futuristic concept — it’s a competitive advantage in motion.
At MJV, we help organizations harness the power of synthetic data and AI to accelerate insights, validate strategies, and reduce costs — responsibly and at scale.
Discover MJV AIRA, your intelligent insights platform designed to bring synthetic research to life.
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