As product teams scale, speed becomes the top priority. New features, updates, and market launches happen at a rapid pace—leaving little time for traditional user research. To keep up, teams often turn to quick research methods, assuming that fast insights are better than no insights at all.

But moving fast doesn’t mean cutting corners on research. Bad insights can be worse than no insights at all—leading to wasted development cycles, flawed assumptions, and frustrated users.

In this post, we’ll break down three major research mistakes that fast-moving product teams make, and more importantly, how to fix them—so you can scale quickly without sacrificing research quality.

Mistake #1: Prioritizing Speed Over Data Quality

Many growing product teams fall into the trap of thinking that quick feedback is better than deep insights. They rush through research by:

• Relying on quick-turnaround surveys instead of real user testing
• Gathering feedback from unverified participants versus engaged, relevant users
• Accepting low-effort responses just to check a box before launch

While this approach delivers fast answers, it often leads to flawed data, misleading insights, and ultimately, product decisions that miss the mark.

The reality? Researchers disqualified 46% of respondents in a 10-minute questionnaire due to serious quality concerns, such as inconsistent answers, nonsense responses, or multiple errors. That means nearly half of the data collected from online panels is unusable before even being analyzed.

The Fix: Build a Research Process That Balances Speed and Accuracy

Instead of chasing immediate but unreliable feedback, product teams should:

• Maintain a pre-vetted research community of their own engaged users who can provide authentic, in-depth insights—fast
• Use iterative research cycles to collect quick but meaningful data at each stage of development
• Avoid research shortcuts that compromise validity—such as unvetted survey respondents or overly simplified testing methods

When research is built into the product development process, speed and quality don’t have to be at odds.

Mistake #2: Over-Relying on Paid Research Panels for Quick Insights

Many teams under pressure turn to paid research panels to gather feedback rapidly, believing they offer an easy way to test ideas.

While these panels provide immediate access to participants, they also introduce significant risks:

• Low-quality responses from “professional testers” who speed through surveys for incentives
• Lack of actual product experience—participants may have no familiarity with your industry or use case
• One-time feedback that doesn’t track user behavior or feature adoption over time

In the end, you’re left with superficial insights that may not reflect how core users would engage with the product.

And it gets worse: according to studies by Grey Matter Research and Harmon Research, 90% of researchers fail to implement proper quality control measures in online panels. Many studies lack the most basic safeguards, such as:

• 50% fail to remove straightliners—participants who just select the same response for every question.
• 75% omit red herring questions that catch respondents who aren’t paying attention.
• 95% don’t include fake brands in awareness studies, allowing panelists to falsely claim familiarity with non-existent products.

A Real-World Example of What Can Go Wrong

A SaaS company preparing for a major onboarding redesign needed quick validation that their new flow was easier to use. They ran a usability test with a paid research panel, and feedback was overwhelmingly positive—participants completed tasks easily and rated the experience highly.

But when the update rolled out, support tickets surged, and activation rates dropped. The panelists weren’t actually real users, they were professional testers.  While they followed the steps perfectly, they didn’t represent how new customers actually learned the product.

And this isn't just an isolated case—inflated research data is a known issue. In one study, 58% of invalid respondents claimed awareness of a brand, compared to just 15% of valid respondents—a 287% inflation gap.

That means teams relying on panel data might be making major product decisions based on completely skewed results.

The Fix: Build a Scalable Research Community for Reliable, Fast Feedback

Instead of starting from scratch with every study, product teams should:

• Develop a research group of actual customers who use the product and are invested in its success
• Segment participants by use case, experience level, and product familiarity for more targeted insights
• Tap into this engaged network whenever quick research is needed, rather than relying on survey respondents with no real connection to the product

A well-maintained research community ensures that teams always have access to high-quality insights—without the trade-offs of paid panels.

Want to see how you can quickly build and manage a scalable research community? Book a demo of Centercode and see how leading teams streamline research, reduce reliance on third-party panels, and collect actionable insights at speed.

Mistake #3: Treating Research as a One-Time Step Instead of a Continuous Loop

Many product teams view user research as a box to check before launch—rather than an ongoing source of insight that can drive continuous improvements.

When research is treated as a one-and-done process, teams miss out on:

• Longitudinal insights - understanding how user behavior evolves over time
• Feature iteration feedback - tracking whether past improvements actually solved the right problems
• Ongoing engagement with key users - ensuring the product remains aligned with customer needs

Without continuous research, product teams risk making the same mistakes over and over—fixing the wrong problems, chasing the wrong features, and frustrating users who don’t feel heard.

The Fix: Establish Research as a Core Part of Product Development

Fast-moving teams should integrate continuous research cycles into their workflow by:

• Using a research community for ongoing feedback so teams always have a pulse on what actual users need
• Incorporating rapid iteration testing to gather insights at multiple stages instead of waiting for a single “final” study
• Tracking key research findings over time so improvements are based on real user behavior, not just pre-launch assumptions

The most successful product teams don’t just test before launch—they collect and apply insights throughout the product lifecycle.

Scaling Fast Without Sacrificing Quality

Speed is critical for growing product teams, but rushing research, relying on bad data, and treating feedback as a one-time event leads to costly mistakes.

By avoiding these common pitfalls and shifting to a research model built on continuous, high-quality insights, product teams can:

• Move quickly without making avoidable mistakes
• Get reliable feedback from engaged users—not rushed, unqualified participants
• Scale research as fast as the product itself

Want to see how leading teams build scalable, high-quality research programs? Download our free ebook with the button below to learn how to replace bad data with insights that drive real product success.