Data Reliability

The pillars of data quality

At Vypr, we use a robust methodology to ensure data accuracy. Consistent data reliability means you can base important decisions on valid data throughout the entire lifecycle of your product development process.

1. Engaged community

Since we have our own proprietary panel, we’re able to control the sample and track the integrity of consumer insights. Our consumer-facing app is designed to increase engagement and retention amongst our panel. 

We maintain high engagement by enforcing data integrity rules and removing users who don’t follow them. By adhering to strict data quality metrics, we ensure you get accurate response data from reliable sources.

2. Reliable responses

Vypr implements several data reliability assessment strategies to remove poor-quality data. We recruit community members from vetted sources with verified consumer profiles and implement our own comprehensive consumer profiling and validation process. 

We also track open responses, flag and resolve invalid data, and run monthly integrity steer checks that help us identify and remove unreliable participants. This data quality methodology is key in maintaining data integrity and helps ensure our panel’s data remains robust and reliable. 

3. Representativeness

Data representativeness ensures you can explore results at a granular level. This makes targeting usually hard-to-reach audiences easy and helps ensure the diversity and reliability of your data.

We manage the recruitment of our community to ensure the sample is representative of the population in key geo-demographic criteria, including age, gender and region. We consider these criteria along with buying behaviour and consumer attitudes.

Our diverse quantitative and qualitative data means you can use our platform to target demographic profiles with both combinations and weighting. This versatile testing is key in maintaining data reliability across markets.

4. Up-to-date research protocols and methodology

Utilising everything from qualitative and quantitative testing to comparative or monadic testing, you can be sure we provide high-quality data that is reliable.

We apply behavioural science to our quantitative and qualitative research methodology. We help you ask clear questions that encourage panellists to respond quickly with instinctive system 1 responses. 

Behavioural science data helps you better understand consumer actions. It improves predictive intelligence by ensuring valid and reliable data that is truly reflective of typical buying behaviour. 

5. The right team

Our expert Community team has over 150 years combined experience managing global consumer panels. As business leaders, we use our expertise to understand our customers’ needs and deliver strong results. 

By relying on the best practices in reliable data delivery, we ensure our data collection methods provide reliable, trustworthy and accurate information. 

With such high data reliability, you can feel confident using our predictive customer intelligence and data analytics to make informed product decisions. 

Streamline your new product development process with Vypr.