Why Some Synthetics Fall Short—and How Bellomy’s Synthetic Respondents Succeed
EXECUTIVE SUMMARY: Synthetics are making headlines—but not all the news is good. Can you trust synthetic respondents? Synthetic respondents are a hot topic in the world of market research. The promise is huge: AI-powered digital panelists that help us reach new audiences, accelerate research, and unlock insights we might otherwise miss. But as with any emerging technology, there’s a spectrum of quality—and not all synthetics are created equal. Some researchers have run into disappointing results, leading to skepticism about their reliability and usefulness.
So why do some synthetics fall short? And more importantly, what does it take to create synthetic respondents you can actually trust? Let’s take a closer look.
Why Do Some Synthetics Miss the Mark?
Not all synthetics deliver the same quality of insights. Many quick-fix or ad-hoc approaches are fine for simple validation tasks—like checking if a survey question makes sense to Gen Alpha or catching cultural sensitivities—but they’re not robust enough for large-scale research.
The main problem? These synthetics are often created in a vacuum, without any real-world boundaries or grounding. It’s easy (and cheap) to conjure up a “respondent” who’s a 105-year-old basketball-playing grandmother from Memphis with blue hair and a passion for Nike—hardly a realistic or useful sample.
Another common pitfall: generating answers that sound plausible but don’t reflect actual population distributions, leading to misleading or skewed results.
When synthetics aren’t anchored to real data and lack rigorous validation, they risk becoming little more than digital caricatures—interesting, perhaps, but not actionable for decision-making.
What makes Bellomy’s synthetic respondents different?
At Bellomy, we’ve taken a fundamentally different approach to building synthetic respondents—one that prioritizes realism, representativeness, and reliability.
Multi-Stage, Data-Driven Construction
Our synthetic panel is built using a multi-stage process that combines demographic data, advanced AI segmentation, and detailed attribute generation. This ensures our virtual panelists mirror real U.S. population segments, not just generic archetypes.
Census-Aligned Coverage
We anchor our synthetic panel to U.S. census data, covering over 33,000 ZIP codes and a wide array of demographic and psychographic segments. This allows us to fill gaps in hard-to-reach or niche populations with confidence.
Psychographic & Behavioral Depth
Beyond demographics, we enrich each synthetic respondent with Big 5 personality traits, behavioral patterns, and layered psychographic data using the latest GenAI techniques. This results in more nuanced, realistic responses.
“Upskilled” Personas
Our synthetics aren’t just a list of stats—they have backstories, habits, and established preferences. We add depth across life dimensions (food, finances, traditions, leisure, and more) to create panelists with consistent, believable personalities and rich histories.
Bounded by Real-World Variables
All our synthetics are grounded in real-world constraints, ensuring their responses stay relevant and actionable.
Continuously Evolving
Our panel grows and adapts over time—expanding ZIP code coverage, creating specialized sub-panels, and refining profiles through ongoing research and validation.
Every synthetic we create is built and tested with the same care we apply to human-collected data — because the quality of insight is non-negotiable, no matter the source,
—Kim Killian | Director, Insights Technology AI
How do Bellomy's synthetics compare to others in the industry?
Not all synthetics deliver the same quality of insights. Many quick-fix or ad-hoc approaches are fine for simple validation tasks—like checking if a survey question makes sense to Gen Alpha or catching cultural sensitivities—but they’re not robust enough for large-scale research.
Approach |
Bellomy |
Industry Standard |
|
No training on past surveys |
✅ By not training our synthetics on previous surveys, we avoid perpetuating legacy bias. |
❌ Many market research vendors’ synthetics are still rooted in historical data. |
|
ZIP-level & census anchoring |
✅ Bellomy’s synthetic panel includes coverage of ~33k ZIP codes and a wide range of census variables. |
❌ Other synthetics are often limited to broad demographics. |
|
Psychographic + GenAI layering |
✅ Our synthetics are built around Big‑5 traits and behavior enriched using Generative AI. |
⚠️ Others add various traits to their synthetics, but they’re not often multi-layered. |
|
✅ Bellomy recommends a nuanced hybrid research model that includes both synthetics and human respondents to validate results. |
❌ Many use synthetics alone or ad-hoc mixes that are unreliable. |
|
|
Twin methodology |
✅ We build digital twins of high-value segments that can be leveraged for strategic use by a range of stakeholders. |
⚠️ Most firms offer twins, but they vary in fidelity |
|
External validation |
✅ We incorporate sales and market data for even more accurate and reliable data. |
⚠️ Validation practices vary, often missing rigorous external benchmarks. |
Questions Market Researchers are Asking about Synthetics
Everything Market Researchers Want to Know About Synthetic Respondents & How They Work
What is a synthetic respondent?
A synthetic respondent is a new data-modeled, AI-generated profile that simulates real-world consumer behavior for market research purposes.
What is a synthetic response?
A synthetic response is a machine-generated prediction of how a real respondent would answer a specific question, based on behavioral and demographic modeling.
What does "synthetic" mean in research?
“Synthetic” refers to artificially created data or personas that reflect human-like responses, allowing researchers to simulate behavior without relying solely on live participants.
Explore more questions that market researchers are asking about synthetics
Seeking greater efficiency for your robust research programs?
If you manage a sophisticated and robust survey research program, please complete the form below and we will provide you with examples and greater detail about how to leverage synthetic respondents.
We use synthetics where they add reach, speed, or depth—then combine them with human responses to create a more complete, balanced picture of the market.
—Kim Killian | Director, Insights Technology AI
Want More Synthetics Insights?
Don’t settle for subpar synthetics.
Not all synthetic respondents deliver reliable insights, it’s crucial to choose solutions grounded in real-world data and rigorous validation. Bellomy’s synthetics stand apart, offering quality and trust you can count on for impactful research.
Synthetic Respondents in Market Research: The Next Frontier in Insights
Used wisely, synthetics can reduce the demands placed on human participants by pre-filtering concepts and ideas and optimizing research to remove noise, clutter and excess.
—Matt Gullett | SVP, Insights Technology/on How Synthetics Can Reduce Human Burden
