Research Data You Can Defend
Layered fraud prevention and participant verification that help keep bots, duplicates, and inattentive respondents out of your study — so your findings hold up to scrutiny.
Online research has a fraud problem. Bots, professional respondents, and duplicate sign-ups can quietly erode a dataset. We combine identity verification, screening rigor, and hands-on human review to protect the integrity of what you collect.
Trusted by leading brands and research teams
A layered defense for your data
No single check catches everything. We stack multiple safeguards — automated and human — so problems are caught at different stages, before they reach your dataset.
Identity verification
Participants are verified at sign-up and re-checked over time, so the person in your study is who they say they are.
Fraud & bot detection
Automated checks flag bots, duplicate accounts, and suspicious patterns before participants ever reach your study.
Screening & consistency checks
Detailed screeners and cross-question consistency checks help confirm participants genuinely qualify — not just that they clicked the right answers.
Attention & engagement checks
Attention and open-end quality checks help identify disengaged or low-effort respondents so they don't skew your results.
Dedicated human review
Our project managers review recruits personally — a layer of judgment that automated systems alone can't replace.
Certified to ISO 20252 & 27001
Independent certification for market-research quality (ISO 20252) and information security (ISO 27001) underpins how we run projects and handle data.
Participant experience
From recruitment to follow-up, we prioritize respectful, seamless, and rewarding participant experiences. Engaged participants give richer, more honest input — which strengthens the foundation of every study.
Industry alignment & leadership
We actively contribute to industry standards, supporting initiatives like the Data Quality Excellence Pledge, GDQ, and the Insights Association's Participant Bill of Rights — collaborating to build a stronger, more ethical research ecosystem.
Frequently asked questions
How do you prevent fraudulent or bot respondents?
Do you verify that participants actually qualify?
How do you handle data security and privacy?
What happens if a respondent looks low-quality during fieldwork?
Build your study on data you can trust.
Tell us about your project and we'll walk you through how our quality safeguards apply to your audience, methodology, and timeline.