Just 18 months ago, the market research industry viewed synthetic data with healthy skepticism, and for good reason. The industry has always sought to balance speed and technology with human-centered insights, and synthetic data felt too risky — too far removed from the real human voices that make research valuable.
Now, almost two years later, we’re starting to get validation that these techniques have legs, and syndicated research is where it’s finding the fastest traction.
Syndicated research companies already collect ongoing conversations across categories and topics, making them perfectly positioned to use this technology.
Morning Consult, for example, conducts monthly interviews in multiple countries, then trains AI on those conversations. Subscribers can query the AI during meetings instead of commissioning new research every time a question arises.
This approach is gaining momentum. The Qualtrics–Pure Spectrum partnership is exploring similar territory, combining user experience data with profile information to create synthetic research applications.
The economics make sense with multiple companies sharing the cost while getting instant access to insights. No more waiting, no separate studies for every question; just real-time answers from ongoing conversations.
Syndicated synthetic data is reshaping insights work in specific ways — how we access category intelligence, when we can get answers, and what questions become worth asking. Getting familiar with these new approaches now puts you in a stronger position as they develop.
The Benefits of Synthetic Syndicated Data
Synthetic syndicated data collapses traditional research timelines because there’s no need to field new studies for each question. Instead of spending weeks on multiple research waves, teams can query existing AI-trained data instantly.
This empowers teams to reach refined concepts faster while maintaining quality controls where they matter most. Traditional rigorous validation still happens for final decisions, but the early screening process becomes much more efficient and insightful.
Efficiency gains enable more research because the traditional cost-per-question model disappears. Instead of paying for individual studies, subscription access means lower costs and faster turnaround make it affordable to research smaller questions.
From a use case perspective, early-stage testing represents the strongest application for syndicated synthetic data. The ability to get instant feedback makes it ideal for initial concept screening and rapid iteration before investing in more rigorous validation studies.
Product concept testing is a perfect example. Researchers can test multiple variations and get real-time feedback during strategic meetings.
Advertising creative follows the same pattern. Teams can quickly evaluate different brand positions and directions before committing to expensive production and media buys.
So to recap, synthetic syndicated data enables:
- Instant access to AI-trained data (no new fielding required)
- Faster early screening with validation saved for final decisions
- Lower costs through subscription vs. per-question pricing
- More research on smaller questions made affordable
- Strongest fit in early-stage testing and rapid iteration
- Real-time concept and creative feedback during strategic discussions
The Tracking Study Opportunity
Syndicated synthetic data is expanding beyond traditional syndicated research boundaries.
“I really see a shift coming where there’s going to be less ad hoc survey research and more synthetic data,” explains Frank Kelly, Market Research Practice Lead at Virtual Incentives.
The biggest opportunity in this shift? The area where continuous research has struggled the most: tracking studies.
The Problems Plaguing Traditional Tracking
Tracking studies are facing serious quality challenges that affect their reliability. Survey exclusions that once protected data integrity have become impossible to maintain.
The industry used to enforce 3-12 month exclusions between similar surveys, but those protections have disappeared as different panels network together.
Without these safeguards, the same respondents end up taking too many surveys. For example, they might be asked about Coca-Cola awareness in January, then get the exact same questions in February. Naturally, they’ll recall Coca-Cola more readily the second time, not because of any marketing impact or authentic brand awareness, but simply because the questions are fresh in their memory.
This skews the tracking data, which makes tracking studies increasingly unreliable for strategic planning. Beyond the reliability problems, these studies rarely generate fresh insights; they just cycle through the same conclusions repeatedly.
How Syndicated Synthetic Data Offers a Solution
Syndicated synthetic data offers a solution. Instead of commissioning expensive individual tracking studies, brands subscribe to category-specific AI intelligence trained on ongoing conversational data.
The quality contamination disappears entirely. Since the AI draws insights from fresh conversations collected continuously, there’s no risk of respondent fatigue or ghost awareness affecting the data. Participants engage in natural discussions about category usage rather than repetitive brand awareness surveys.
The innovation problem gets solved too. Unlike tracking studies that only measure predetermined metrics, conversational data reveals unexpected insights. AI can identify innovation opportunities that traditional surveys would never capture.
“You’re much more likely to find innovative ideas or new ideas that the researcher who wrote the survey might not even be aware of or thought of,” Frank explains.
Most importantly, the insights become immediately actionable. Instead of waiting for monthly reports, teams get real-time intelligence for quick decision-making when it matters most.
In summary, syndicated synthetic:
- Eliminates quality contamination through fresh conversational data
- Prevents respondent fatigue and ghost awareness
- Reveals unexpected insights and innovation opportunities
- Provides immediately actionable intelligence
- Enables real-time decision-making
- Delivers authentic category discussions vs. repetitive surveys
The Future of Market Research
The sentiment around synthetic data has moved from skepticism to validation, with syndicated research leading the way.
By pairing ongoing conversational data with AI analysis, teams can access real-time insights, uncover new opportunities, and reimagine long-standing studies like trackers. The result is faster, fresher intelligence that extends well beyond the boundaries of traditional syndicated research.
And we’re still early. If these benefits are possible now, before most teams have fully mastered the approach, the potential as the technology and expertise grow is enormous. Validation is building confidence across the industry, and adoption will only accelerate from here.
The takeaway is simple: this is no longer a “wait and see” situation. Synthetic data is reshaping how research gets done, and those who engage with it now will set the pace. Rather than replacing human insight, it strengthens it — making skills like strategic thinking, consumer understanding, and synthesis more valuable than ever.