Sample Size vs. Sample Excellence: what really drives reliable insights
It’s tempting to think that the larger the sample size, the better. Surely a bigger sample means more accurate data? But that’s not always the case.
It’s important to consider sample size vs sample excellence. Instead of focusing on sample size alone, it’s better to prioritise a smaller, well-vetted, and representative sample that delivers actionable insights.
A small, well-vetted, engaged sample often delivers far more accurate and actionable insights than a large, less targeted one.
Why bigger isn’t always better
It’s tempting to think that a larger panel size improves confidence in results. While larger samples can reduce statistical error, representative or trustworthy data isn’t guaranteed.
The bigger the sample, the more likely it is you’ll have low-quality participants. Whether it’s bots or disinterested people, this can skew your results and make your research useless, no matter how large your sample size is.
Another issue with large samples is survey fatigue. Large panels tend to rely on participants who complete a lot of surveys. As a result, the incentive is to rush through the survey so they can get to the next one.
Even if only 10% of respondents rush or provide poor-quality answers, the results can become unreliable.
Instead of giving you increased certainty, more data points can give the illusion of accuracy if your sample isn’t robust.
A larger sample size can mask underlying biases and integrity issues that are less likely to be present on a smaller but more targeted sample.
A bigger sample can work if managed well, but if it’s not, it can lead to misleading insights, wasting both time and money.
The case for sample excellence
Instead of focusing on sample size, it’s better to prioritise sample excellence, but what do we mean by sample excellence?
It means panel integrity, quality assurance, and engagement. Instead of disinterested participants looking to jump to the next question, you have engaged ones motivated to provide genuine feedback on your products.
When thinking about sample excellence, there are three things you should consider:
- Panel quality assurance: Ensuring your sample is diverse and representative is essential for delivering high-quality insights
- Ongoing monitoring: Detecting disengagement, fatigue, or repeated survey attempts prevents samples from returning poor results
- Fraud prevention: Blocking bots, duplicate accounts, and incentive-driven manipulation ensures malicious actors can’t skew the results
By prioritising these factors, you’re more likely to get reliable, actionable insights, even with smaller or mid-sized samples.
Quality always trumps quantity. This has never been truer when you need to make a critical business decision based on data.
How can VySafe ensure sample excellence?
At Vypr, we’re committed to providing high-quality samples that you can trust, no matter the size. That’s why we developed VySafe.
Our VySafe framework is designed to protect the integrity of market research at every stage, ensuring sample excellence across your panels.
Every panellist goes through a 120-steer quarantine process to ensure we have only the highest quality contributors providing feedback.
Once we accept panellists, we constantly track their activity. Our VySafe score applies more than 28 checks a week, looking at behaviour, device activity and consistency to ensure responses continue to meet our high standards.
We ground our surveys in behavioural science, with a focus on capturing instinctive thoughts and responses. By keeping our surveys short and engaging, informed by System 1 thinking, we mitigate bias and fatigue, ensuring responses are genuine and insightful.
With VySafe, you don’t just collect data, you get responses from real, engaged, and representative participants, turning your panel into a source of trustworthy insights.
Get quality over quantity with VySafe
Reliable insights don’t come from the biggest sample they come from the best ones. Without strong safeguards, even the most well-intentioned survey can run aground.
Vypr’s VySafe framework is purpose-built to help uphold panel integrity and research quality from start to finish. Unlike traditional data quality tools that only identify bad data after it appears, VySafe minimises the risk of it entering your sample in the first place.
Discover how VySafe can transform your research by prioritising sample excellence over size. Schedule a demo today.