Why good enough isn’t good enough: Sample quality changes your research outcomes

In a time where data is abundant and time is finite, it can be easy to opt for data that is “good enough.” 84.51° embarked on a journey to understand if research could truly be “good enough.” A sneak peek: only 20% of people in more traditional recruiting methods should actually qualify for a study. Embracing the mantra of “good enough” can have far-reaching consequences that jeopardize important decision-making. We’ll explore what the research showed us, why you should care and why it matters.

Join us as we debunk the myth of “good enough” data quality. We’ll explore evidence that shows talking to the wrong shoppers leads to different business decisions and that finding sampling methods to ensure you are talking to real shoppers making real purchases will lead to higher-quality research and business decisions you can feel confident in. After all, the customer is always right – but only if you’re asking the right customer.

Key takeaways:

1. If you’re settling for “good enough” data, you’re likely not talking to who you think you are.
2. Self-claimed data leads to major misclassification of shopper segments and higher rates of survey fraud.
3. General-population samples and behaviorally targeted samples deliver results that lead to different business decisions.

Consumers Presentation by Supplier Research Report