Without high quality data, we've got nothing.
It’s why we’re obsessed with
getting it right.
What do we mean when we say quality?
High-quality insights only come from high-quality data. We like to think of “quality” in three distinct ways, each requiring its own set of solutions, that together make up a “quality framework.”
1: Identity
Are participants really who they say they are?Before we're letting anyone into our panel or your survey, we're verifying their identity by cross-referencing their credentials and self-reported data against a combination of private and public third-party resources. This not only helps us verify medical providers, but also protects against any level of bots and artificial intelligence.
- Panelists locked to NPI records (prevents duplicates)
- Two-factor authentication for identity-linked data
- Real-time credential verification
2: Targeting
Are the right people getting into your survey?To truly understand who we're inviting to your survey, self-reported data just isn’t enough. We leverage real-world data to understand participants' medical specializations and key professional attributes. We target using the following real-world data:
- NPI taxonomy/specialty (always)
- Real-world scripting data (as needed)
- Practice and hospital affiliation (as needed)
3: Truth
Are survey responses accurate, thoughtful, and real?We go beyond the industry-standard attention checks, and monitor for several in-survey behavioral patterns that indicate inattentive, malicious or non-human behavior. Where possible, we check self-reported data against an independent, credible source. If anything looks suspicious, we'll be the first ones to know.
- Standard attention checks: straight-lining, red herrings, etc. (programming required)
- Advanced behavioral analysis: mouse movements, rounding, etc. (programming required)
- Checking survey responses against third-party data sources