For research & insights teams

Pre-qualified respondents. No screener disqualification.

Run surveys, focus groups, and longitudinal studies against a consented base where demographic and intent attributes are already known — and purchases are receipt-verified, not self-reported. Field a study in minutes — and stop paying for respondents who don’t qualify.

Surveys, studies and research sessions includedSponsored offers open after the betaPer-response & per-seat pricingNo annual contracts
The shift

Stop paying for screener disqualification.

Traditional panels charge you for the time and rewards spent on respondents who didn’t qualify. Fairly doesn’t ship a respondent to your study until they already match.

Traditional research panel
Find them, then qualify them.
25–50% screener disqualification on most studies — paid for, then discarded.
Self-reported demographics per study — re-asked, never verified across waves.
Recruit a new batch per wave — cohorts drift, comparisons get noisy.
Days to field — recruiting, qualifying, and starting takes most of a week.
Trust-based verification — purchase history is whatever the respondent claims.
Fairly
Already qualified. Already verified.
0% screener disqualification — every respondent matches before the invite goes out.
Profile data already known — same attributes carry across every study you run.
Locked cohorts across waves — track the same people from month to month.
Field in minutes — launch immediately against any saved segment.
Real purchase data — buying behavior comes from real purchase data from members’ receipts, not self-report.
Three research formats

One pre-qualified audience. Three ways to ask.

Surveys
Included

Send a survey to any saved segment. Eight question types including matrix, ranking, and NPS. Census-weighted or segment-matched quotas across gender, age, income, and state. Priced per response.

8 question types, conditional logic, branching
Quotas across gender, age, income, state
Census weighting (US Census recommended)
Response count as it fills; results from 20 responses
Skincare brand preference
Illustrative
Live · responses
412 / 500
Quota fill
Women 25–34
102 / 125
Women 35–44
125 / 125
Men 25–34
89 / 125
Men 35–44
97 / 125
Avg. completion
7m 42s
Disqualified
0%
Est. complete
~6 hrs
Longitudinal studies
Included

Lock a cohort, send them the same base survey across 2–12 waves. The same people respond every wave, so opinion shifts come from the people — not from a different sample.

Built-in cross-wave trend comparison renders the result directly in the study view. No exporting to a stats package to see if a number actually moved.

Cadences: weekly, bi-weekly, monthly, bi-monthly, quarterly
Locked cohort persists across waves
Participants paid at least $2.50 every wave, to keep the cohort together
Cross-wave trend comparison built in
Q2 cohort · cross-wave comparison
Illustrative
500 women 28–38, skincare buyers · 3 of 5 waves complete
“Open to switching skincare brands”
W1 · Mar
12%
W2 · Apr
18%↑6
W3 · May
24%↑6
“Loyal to current brand”
W1 · Mar
64%
W2 · Apr
58%↓6
W3 · May
51%↓7
Trend: increasing openness to switching · directional shift visible across waves
Focus groups & interviews
Included

Recruit a saved segment into a paid 1:1 interview or a focus group of 4–8 seats. Video, audio, or text format. Pay per confirmed seat — seats nobody confirms are refunded.

Every participant matched your segment’s profile attributes before they were invited. Reliability scoring on past sessions surfaces participants who’ve shown up and engaged.

1:1 interviews or focus groups (4–8 seats)
Video, audio, or text format
Charged per confirmed seat · unconfirmed seats refunded
Participant reliability scoring from past sessions
Skincare brand switching · Mar 22
Illustrative
60-min video focus group · 6 seats
6 of 6 attended · 100% show rate
P1
Woman, 32 · New York
Skincare buyer (real purchase data) · monthly cadence
98%
P2
Woman, 28 · Austin
Skincare buyer (real purchase data) · subscription member
100%
P3
Woman, 35 · Boston
Skincare buyer (real purchase data) · brand-switcher
94%
P4
Woman, 30 · Los Angeles
Skincare buyer (real purchase data) · premium spend
96%
Avg. reliability
96%
Length
58 min
Stop screening. Start asking.
Apply for access if your team is ready to run, or request a demo to explore the platform with seeded research data first.