At C+R Research, we understand that great research and deep perspective begin with reliable, accurate data, and we carried over this philosophy with the creation of A+U NOW®. Specifically, A+U NOW® implements a two-tier process that ensures the highest quality data in every A+U NOW® project.
In the first tier, our technology partner, PureSpectrum, uses its proprietary PureScore processes to evaluate respondents before they are included in any survey. By utilizing PureScore, survey respondents’ background data is validated as accurate and true.
- PureSpectrum’s PureScore analyzes the profile and past behaviors of each transaction to score and block fraudulent activity before a person fills out a survey.
- Each respondent’s transaction is assigned a rating of 1-10.
- To gain access to the survey, the respondent’s transaction must score 5 or greater.
As the respondent is allowed access to an A+U NOW® survey, quality assessment continues into the second tier:
Using C+R’s Sentinel Data Quality system, our survey can identify, react, and remove “satisficers” ─ those trying to “satisfy” the survey to qualify and get their incentive ─ non-engaged respondents, and over qualifiers from a study.
- Led by our Ph.D. statisticians, in-field data analysis utilizes an algorithm that scans across embedded consistency checks and assigns a Sentinel Data Quality score to each respondent based on the algorithmic results.
- Respondents with a score outside the acceptable range are removed from the dataset in real-time, allowing A+U NOW® to complete the quota with only valid, engaged respondents.
- The consistency checks include evaluating against a minimum acceptable interview length, flagging straight-liners on key attribute batteries, identifying contradictory responses within individual surveys, and flagging “red herrings” in the dataset.
In today’s sampling marketplace, it is important to exercise caution and expend every effort to ensure data quality. A+U NOW® uses a two-tier approach of stringent data checks to provide peace of mind that every project results in high quality, reliable data.