5 strategies to achieve feasibility and high-quality respondents

Delivering insights you are confident in is becoming more critical while finding high quality respondents is becoming increasingly challenging. This challenge is further complicated because we don’t have a consistent definition and standard for high quality data. With every researcher looking for high quality respondents, knowing how to define high quality data and achieve full feasibility without sacrificing data quality is vital to delivering the insights you need.

Rep Data will use case studies to illustrate the five strategies they use to deliver high quality data, on time and on budget, in the ever changing research world.

Key takeaways:

1. Understand the spectrum of high quality data and how to define what you need.
2. What to do pre-field, in-field and post-field to improve data quality and avoid surprises.
3. What is sample aggregation and how it is used to improve data quality.