Quality control in Market Research: An insider’s guide with Field Director, Rosaura Strazzeri

Quality is the bedrock of meaningful insights, but what does it actually take to achieve this in market research? FFIND’s Field Director, Rosaura Strazzeri, pulls back the curtain to reveal the real work behind the scenes. With 12 years in the industry, she knows quality control isn’t just about data points; it’s about making every survey tell an accurate, valuable story that fuels better decisions.

Why quality control makes the difference

Ever skipped a quality check? Imagine running a marathon only to take a wrong turn at the last mile—without rigorous quality checks, your data can veer just as easily off course.
In the world of market research, quality isn’t just about technical accuracy; “Quality, for us, means capturing responses that are meaningful and genuine,” shares Rosaura.
“When quality is overlooked, you end up with data that’s unreliable or overly biased, which can mean the difference between a sound decision and a costly mistake,” she says.

But what does this commitment to quality actually look like?

“It begins long before the interview starts. Picture an interviewer, motivated and eager, but still new to the depths of statistics and market research. This is where our quality process starts. By immersing them in hands-on, foundational training, we ensure they’re not just prepared but confident, creating a real connection with respondents.

The journey continues through project-specific coaching, where role-playing sessions bring interview scenarios to life, shaping conversations that feel genuine and grounded. Our team keeps a watchful eye on each stage, and if we see patterns like too many “I don’t know” responses or choices of “other” that don’t align, we refine the approach on the spot.

Can you give us an example?
“In a recent benchmark study on energy utility providers, our team spotted a recurring choice of ‘other’ where standard answers already covered the response. By redesigning the question slightly and guiding respondents more clearly, we obtained much cleaner, more relevant data aligned with the client’s needs.”

The Takeaway: Quality control isn’t only about what data you collect but how you collect it. Each response must reflect an authentic viewpoint.

B2B vs. B2C: Quality Control in Different Markets

Effective quality control adapts to the type of respondent, and challenges between the two.

How quality control differs from b2b and b2c?
The way we approach quality control depends greatly on who’s answering the questions. In B2B, where respondents are busy decision-makers, keeping them engaged is key. “Every minute counts,” Rosaura notes. “In B2C, the challenge is helping respondents feel valued and motivated to share thoughtful responses. It’s all about building trust and reassurance—showing them that their opinions truly drive change, and that this study is about understanding, not selling.”

The quality check process itself, however, remains consistent across both types: checking technical precision (like methodology, assisted vs. spontaneous responses, and scale accuracy), using probing techniques to delve into hesitations or “don’t know” responses, and maintaining a professional, clear-headed approach in unexpected situations.

Practical tips to ensure quality in your research

Can you share the top three tips for a better quality?:

1. Clear and structured questionnaires: Design questions that are clear and structured, but allow for spontaneous responses to gain more accurate insights. In our experience, structure makes a world of difference.
2. Accurate targeting: Precise definitions of sample and criteria avoid collecting irrelevant data and ensure that responses align with your goals. We always say: know your respondent well before you start, and you’ll gather better data.
3. Flexibility in questionnaire management: When discussing flexibility in questionnaire management, we suggest rephrasing questions in a targeted way. During the design phase, it’s crucial to include clear and consistent explanations to ensure that the questionnaire is understood uniformly by all respondents, preventing variations depending on the interviewer. The client should define the flexibility, ensuring there is clear control and consistency in the approach.

What innovations are you introducing to further improve quality control?

“We use automated analysis tools to spot suspicious behavior patterns, like responses given too quickly or straight-lining (selecting the same response repeatedly),” she explains. “Recently, we’ve been exploring AI’s potential to correct open-ended answers in real time, suggesting phrasing improvements without altering meaning. But human oversight remains irreplaceable. Only live monitoring can catch the nuances and tones that bring data to life.”

Beyond Data: quality as an empathetic practice

Rosaura believes that quality control extends beyond processes and metrics. It’s about empathy and connection. “Our interviewers are not just ‘data machines’—they’re attuned listeners, and that’s where the magic happens,” she shares. “They know how to make a questionnaire feel like an authentic conversation, even in challenging scenarios. At FFIND, quality is as much about respect for the respondent as it is about the precision of the data.”

With Rosaura and her team’s approach to quality control, data collection becomes a thoughtful and meticulous process. It’s not just about numbers—it’s about crafting a genuine dialogue that ensures every answer reflects the respondent’s true experience. Quality control should ensure that the final product aligns with what the client expected, maintaining consistency and accuracy throughout.

Connect with us today to discover how our empathetic approach can help you capture more authentic insights and make confident, data-driven decisions that truly reflect your respondents’ voices. Let’s start a conversation about your research needs.