Data quality
Four layers of quality control, on every study you run
GroupSolver removes fraud and low-quality data at double the industry rate. The process starts before a respondent enters your study and ends with a human analyst reviewing the dataset.
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.
Step 01
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.
Step 02
Watch in-survey behaviour
GroupSolver surveys run continuous QC checks throughout fielding, catching distracted, low-quality, or fraudulent respondents before they can submit their answers. They never reach your dataset.
Step 03
AI and QC scripts in real time
As responses arrive, AI eliminates gibberish and profanity immediately, along with any zero-value answers. After fielding closes, additional quality scripts catch anything the real-time AI missed, so nothing slips through between passes.
Step 04
Finish with human review
Before you see the data, GroupSolver's analysts review it for coherence and context that 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 monthly
Every month, GroupSolver publishes a public data quality report: removal rates, per-study breakdowns, methodology, and the reasoning behind each decision. It's a record, published regularly for anyone to check.
View all reportsAugust 2026
8 studies
56%
avg removal rate
July 2026
2 studies
61%
avg removal rate
June 2026
2 studies
66%
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. You still stay in control: every decision is visible and reviewable, and you can override any of them.
Fraud caught before it affects your data
Bots and duplicate or synthetic responses are flagged by AI and removed before they reach your dataset. Analysis starts on data that's already clean.
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, for a client debrief or an internal audit.
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 from the start.
Published methodology
Monthly public reports break down what was removed and why removal rates varied, along with the full methodology behind each number. Our quality commitment is public record. Anyone can check it.
Take control yourself
GroupSolver cleans the data. Respondent Manager gives you the controls.
GroupSolver's four-layer process handles data quality automatically. If you want to dig deeper, Respondent Manager gives you a complete workbench inside the platform: review individual respondents, apply your own quality thresholds, and build a case for a panel chargeback.
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.
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