Data quality
Data quality isn't a setting.
It's a system.
GroupSolver routinely removes fraud and low-quality data at double the industry rate — through a four-layer process that starts before a single respondent enters your study and ends with a human analyst reviewing the dataset.
No deck, no pitch — just the platform answering your questions.
2×
the industry fraud removal rate
4 layers
of protection on every study
Every study
ends with a human analyst review
Monthly
public transparency reports published
How we protect your data
Four layers. Every study. No exceptions.
Most platforms run one or two quality checks at the end of fielding. GroupSolver runs four — starting upstream with panel partners and finishing with a human analyst who reviews everything before you see the data.
Start with reliable partners
Before a respondent sees your survey, our panel partners run rigorous checks when recruiting B2B and B2C audiences. When bad respondents do get through, we share that data back with our partners — so the panel gets cleaner over time.
Watch in-survey behaviour
GroupSolver surveys include multiple QC checks throughout — not just at the end. Distracted, low-quality, or fraudulent respondents are caught and removed before they can submit their answers. They never reach your dataset.
AI and QC scripts in real time
As responses arrive, AI eliminates gibberish, profanity, and zero-value answers immediately. After fielding closes, additional quality scripts run to catch anything the real-time AI missed — so the cleaning is thorough, not just fast.
Finish with human review
Before you see the data, GroupSolver's team of analysts reviews it for coherence, relevance, and context — things AI can miss. Any remaining low-quality responses are removed in this final pass. No study leaves our hands without it.
Transparency reports
We publish the numbers. Every month.
Every month, GroupSolver publishes a public data quality report showing removal rates, per-study breakdowns, and the methodology behind each decision. Not a marketing claim — a record.
Recent removal rates have run between 21% and 53% depending on study type and panel source — always with context explaining the variation.
Read the latest report ↗February 2026
6 studies
41%
avg removal rate
January 2026
7 studies
43%
avg removal rate
December 2025
7 studies
46%
avg removal rate
October 2025
7 studies
21%
avg removal rate
September 2025
8 studies
34%
avg removal rate
What this means in practice
Clean data at the source. Full control in your hands.
GroupSolver's four-layer process handles the data quality work that most platforms leave to researchers. But you also stay in control — every decision is visible, reviewable, and yours to override.
Fraud caught before it affects your data
Bots, duplicates, and synthetic responses are flagged by AI and removed before they reach your dataset — not discovered afterwards during analysis.
Real-time gibberish and profanity filtering
Open-ended responses are screened as they arrive. Low-effort keyboard mashing and copy-paste noise are removed immediately — so your qual data reflects what respondents actually thought.
Panel feedback loop
When bad respondents slip through, GroupSolver shares that data back with panel partners. Over time, the panels you recruit from get cleaner — because we're actively improving them.
Every decision is transparent
Removals are logged with reasons. You can review exactly who was excluded and why — whether that's for a client debrief, an internal audit, or your own peace of mind.
Quality runs while fielding runs
You don't wait until close to find out you have a fraud problem. In-survey QC catches bad respondents mid-field so your quota fills with good data — not data that needs replacing.
Published methodology
Monthly public reports document what was removed, why removal rates varied, and what drove the numbers — so our quality commitment is evidence, not just a claim.
Take control yourself
GroupSolver cleans the data. Respondent Manager gives you the controls.
GroupSolver's four-layer process handles data quality automatically. But if you want to dig deeper — review individual respondents, apply your own quality thresholds, or build a case for a panel chargeback — Respondent Manager gives you a complete workbench inside the platform.
Filter by attention checks, completion time, open-end quality, bot signals, and more. Exclude in bulk. Every decision adjusts your quota automatically and is logged for review.
Explore Respondent ManagerReady to see Agatha?
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