COMPARISON
Traditional research panels (Dynata-style, Forsta-style, Qualtrics-panel-style: any pre-recruited respondent database you pay per completed response) are the established methodology for quantitative research, substantiated claims, and statistical-confidence reporting. Candor’s synthetic research is a different methodology layer: fast, evidence-grounded, qualitative-style interviews at hours-per-study rather than weeks-per-round. The honest comparison is how they fit together. Most teams can use both, in different parts of the same research cycle. Some teams won’t need full panel rounds at all, and that’s a legitimate choice depending on the kind of research the team does.
Traditional panel research is the gold standard for several research jobs. Anything that needs real human respondents at statistical N, with documented methodology and reportable confidence intervals, belongs on a panel.
Quantitative point estimates. When the answer needs to be “27% of customers prefer Option A, plus or minus 3 percentage points at 95% confidence,” that’s a panel job. Synthetic research can produce directional signal. It can’t produce statistically-bounded point estimates from real-respondent N.
Substantiated claims. Anything going on a label, in a regulatory submission, in a clinical document, or in a publicly-defensible market claim needs real-respondent data with documented methodology. Panels are designed for that documentation. Synthetic research is not.
Brand and satisfaction tracking. Real customer perception over time, sampled consistently across waves, with year-over-year benchmarks. Synthetic research can hypothesize about brand-perception drift. Only real-respondent tracking can measure it.
Established benchmarks. Industries with decades of category-norm benchmarks (CPG concept-testing thresholds, ad-testing performance bands, NPS distributions by sector) have those benchmarks because they were built on panel data. New methodologies inherit category trust slowly. Established panel methodology already has it.
Anonymized aggregation at scale. When you need 500 or 5,000 responses to a structured survey for segmentation, market sizing, or share-of-wallet analysis, panel infrastructure handles that scale. Synthetic research is a different tool.
Synthetic research solves a different set of problems, the ones where speed, breadth, and cost are the binding constraints. How it works walks through the pipeline end to end.
Early-stage discovery. Before you scope a panel round, you want to know what shape the problem is. Synthetic research lets you talk to a population of evidence-grounded personas about their pains and current behaviors in hours. The output sharpens what to ask your real respondents about, and which segments are worth recruiting. See problem discovery.
Concept screening before panel rounds. Most concepts that go through traditional concept testing don’t make it to launch. Running every concept through a $23K-plus panel round is bad economics. Synthetic concept testing runs in roughly 1 to 2 hours of elapsed time per concept (most of it background pipeline work), so a project’s full concept pool fits comfortably in a single focused work week. Panel budget then concentrates on the survivors. See concept testing.
Hypothesis sharpening. Stress-test the hypotheses inside a roadmap, plan, or strategy against an evidence-grounded synthetic population. Get per-assumption verdicts before deciding which to substantiate with panel research. See assumption validation.
Value-prop and message testing at speed. Five angles, eight personas, 40 reactions, in hours rather than four weeks. See value-prop testing.
Research in populations that are slow or impossible to recruit. Healthcare patients with narrow eligibility, regulated members, niche professional audiences, early-product segments. Synthetic research grounded in published evidence bypasses the recruitment friction.
Qualitative depth at speed. A traditional panel survey gives you 200 short responses to fixed-question structure. A Candor study gives you 8 to 16 long, conversational interviews with persistent personas that remember everything you’ve asked them. Different signal shape, different decision support.
Most consumer-insights and B2B research operations face a structural math problem.
Concept volume is project-driven and stacks fast across every shape of team. A startup iterating on features, value propositions, and positioning typically tests 10 to 50 concepts per project. A consultancy running a strategy engagement is in the same range. A large company launching new products in-market is testing concepts across upfront screening, iteration, and finalist rounds at similar volume per launch. Most teams run multiple such projects a year, reaching hundreds of concepts tested in some form. Traditional panel concept testing for a full validation round runs roughly $15K to $50K (industry median around $23K) and takes 4 to 8 weeks per round including recruitment and analysis. Panel budget can’t cover the full project volume, so most concepts get cut on internal judgment with no respondent signal.
This is the structural waste. Concepts get killed without ever being tested. Some of the killed ones might have been winners. You’ll never know.
The math shifts when synthetic research handles the screening layer. Each synthetic concept test runs in roughly 1 to 2 hours of elapsed time (most of it background pipeline work, with the researcher’s active attention closer to 30 to 60 minutes), so a full concept pool is a single focused work week at most. The finalists advance to panel testing with respondent-grounded evidence already in hand. The cut concepts get killed with respondent-style reasoning, not internal judgment. Panel rounds get concentrated on the survivors with the highest signal-to-noise ratio.
B2B research has its own version of this problem. C-suite and senior-decision-maker research commands incentive premiums of $200 to $800 per completed response on top of base panel rates, and rounds take weeks because the audience is hard to recruit. Most B2B insights work runs at small N because the panel cost ceilings out. Synthetic research grounded in published B2B research can produce directional signal on dozens of hypotheses in hours, then concentrate the expensive real-respondent budget on the highest-value questions.
The frame isn’t “synthetic replaces panels.” It’s panels work better when synthetic research has filtered the question space first.
The teams getting the most value from synthetic research don’t replace panel work. They use synthetic research before and between panel rounds. The pattern that’s emerging:
Steps 1 through 3 used to be either skipped (internal-judgment culling) or done as expensive small-N qualitative work. Step 4 was where the research budget had to live. Now steps 1 through 3 are fast and cheap, and step 4 gets concentrated on the questions that have already survived a synthetic screen.
This is the hybrid research stack. The teams ahead of the curve are running it now.
Some research jobs belong on a panel. Some belong on synthetic. Most research operations need both.
For most teams, both answers are “yes.” The question is sequence: synthetic for the early and middle of the research cycle, panel for the validation and substantiation.
| Dimension | Traditional research panels | Candor |
|---|---|---|
| Respondent type | Real humans (recruited panel) | Evidence-grounded synthetic personas |
| Timeline per study | 4 to 8 weeks (with recruitment + analysis) | Hours |
| Cost per study | $15K to $50K per panel concept round ($23K median) | Flat per study, no per-respondent scaling |
| Sample size typical | 200 to 1,000+ responses (B2C), 50 to 150 (B2B) | 8 to 16+ personas per study |
| Recruitment | Required, weeks of screening | Not needed |
| Quantitative point estimates | Yes, with statistical confidence | No (directional signal only) |
| Substantiated claims | Yes (designed for it) | No (not appropriate) |
| Brand and satisfaction tracking | Yes (consistent wave-over-wave methodology) | No (synthetic is moment-in-time) |
| Concept screening (early-stage) | Yes (slow + expensive) | Yes (strong fit) |
| Discovery interviews | Yes (slow + expensive) | Yes (strong fit) |
| Value-prop and message testing | Yes (slow) | Yes (strong fit) |
| Price testing | Yes (slow + panel-contaminated over time) | Yes (strong fit, no panel contamination) |
| Assumption validation | Possible but rare due to cost | Yes (strong fit) |
| Hard-to-recruit audiences | Major constraint | Minor constraint |
| Established category benchmarks | Yes (decades of comparability) | Building |
This table is a starting frame, not a final scorecard. Panel research is right for some questions. Synthetic is right for others. The teams that pick the right tool per question, rather than treating it as a category-vs-category choice, get the most out of both.
This comparison is one of several. For other angles, see Candor vs UserTesting, Candor vs Synthetic Users, or the full comparison hub. For the category overview, see what is synthetic user research. For how the hybrid model works in concept testing specifically, see concept testing with synthetic users.
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