Market Research in the Age of AI: How to Guarantee Reliable Responses

As artificial intelligence increasingly shapes our activities, the question of response quality in online studies becomes more pressing. How can we ensure that the responses collected are of high quality? How can we verify that they do not come from a bot or AI? How can we be certain that the panel you rely on is trustworthy?

Even without considering AI, the stakes of a market study are so significant that it is crucial to guarantee that respondents have been serious and attentive when providing their feedback on your study.

Before Launching Your Study, Build Your Questionnaire Carefully

To reach the right target audience for your study, screening questions are essential. These questions help filter out respondents who do not match the desired profile.

Crafting effective screening questions
Screening questions should be designed carefully to prevent respondents from easily identifying the "correct" answer.

• Avoid simple yes/no questions – Instead, “bury the lead” by using a multiple-choice format.
• Ensure subtlety – Questions should effectively distinguish between qualified and unqualified participants.

Encouraging Meaningful Responses
Panellists enjoy sharing their opinions—so let them! Engaging respondents leads to higher-quality responses:

• Include at least one open-ended question – This allows respondents to express themselves while serving as a quality check.
• Identify poor-quality responses – Inattentiveness, lack of concentration, or AI-generated content often results in responses that lack nuance and originality.

Filtering Out Bots and Inattentive Respondents
A key step in maintaining data integrity is the use of trap questions—simple checks to ensure respondents are paying attention.

• Basic knowledge questions (e.g., How much is 2 + 5? or What color is the sky when the weather is nice?)
• Consistency checks (e.g., verifying that a respondent's stated age aligns with their children's ages)

These questions are quick and easy to answer but highly effective in identifying disengaged or fraudulent respondents.

Choosing the Right Fieldwork Partner
Selecting the right panel is just as important as designing a high-quality questionnaire. Different panels use different recruitment methodologies, which impact data reliability.

Proprietary Panels

A proprietary panel is owned and managed by a panel provider, ensuring detailed knowledge of panellists' profiles. This allows precise targeting for each study (e.g., dog owners, parents, etc.).

However, not all panel companies operate the same way. Differences arise in recruitment methods and the level of respondent consent:

• Opt-in panels – Respondents register with just an email address.
• Double opt-in panels – Registration is confirmed via email, ensuring a valid address.
• Triple opt-in panels – Involves double opt-in verification plus an additional step (e.g., SMS confirmation).

A triple opt-in panel typically results in a more engaged and reliable respondent base.

River Sampling

River sampling involves inviting internet users to participate in a survey while they browse online. This is done via banners, ads, promotions and pop-ups on various websites.

• Best for testing a product with an existing audience or consumers interested in similar products.
• Challenges:
  Respondents may be less engaged, leading to “happy clicking” (answering too quickly) or dropouts.
  Higher screen-out rates, since respondents are not pre-targeted before starting the survey.

Strengthening Data Quality: Essential Checks
At the end of data collection, data cleaning is a crucial step to ensure accurate and reliable insights.

Monitor Response Time (LOI = Length of Interview)

• Check response times per page – If a respondent completes the survey too quickly, their data may not be valid.
• Track media viewing times – Ensure respondents watched videos or viewed images properly.

Review Open-Ended Responses

• Responses should be relevant and insightful – Avoid short or vague answers (e.g., "It’s good" or "Nothing to report").
• Detect AI-generated responses – These often appear overly long, repetitive, and closely resemble the original question.

Check IP Geolocation

• Remove responses from users outside the target country to maintain data integrity.

Verify Response Consistency

• Ensure household members and children's ages align logically.
• Identify contradictory responses that suggest inattentiveness.

Detect Straight-Lining

• Straight-liners select the same response across all rows in a matrix question (e.g., choosing the same column every time). This often indicates low engagement.

Validate Trap Question Performance

• As mentioned earlier, trap questions remain an effective way to catch inattentive respondents or bots.

Conclusion

By implementing these best practices, you can ensure high-quality survey responses that lead to more reliable and actionable insights.

• Selecting the right panel
• Designing effective questions
• Rigorously validating responses

All of these steps contribute to better research outcomes—ensuring that your market study is built on a foundation of reliable data. ?