The market research industry is entering a new phase. What once felt like emerging disruption is now the reality of modern research: more sophisticated fraud, rising pressure on feasibility, changing respondent behavior, and artificial intelligence embedded across the research process.
EMI’s 2026 Sample Landscape Report examines the forces reshaping online sample and the decisions researchers need to make to protect data quality, improve confidence, and generate more reliable insights.
The Top 6 Trends Shaping Quality in Market Research in 2026
Market research trends in 2026 are not just about new tools. They are about accountability, transparency, and better trade-offs. As AI changes how people interact with surveys and fraud tactics become more technically savvy, researchers need to look beyond surface-level metrics and ask harder questions about where their data comes from, how it is validated, and what risks remain hidden.
Based on EMI’s ongoing research-on-research program, the 2026 Sample Landscape Report explores the sample ecosystem through observed respondent behavior, panel comparisons, quality metrics, fraud detection, and consumer adoption of generative AI.
Trend 1: Data Quality Is Now a Business-Critical Issue
Low-quality sample can shift the actual outcome of a study, not just add noise to a dataset. EMI’s research found that unfiltered data can meaningfully distort core measures, including brand awareness, brand rating, and concept purchase intent. In some cases, poor-quality and fraudulent respondents changed brand awareness by as much as 18 percentage points, while purchase intent inflation ranged from 4 to 9 points at the panel level. For brands making high-stakes decisions, those differences can be the deciding factor in whether a product is launched, repositioned, or abandoned.
How EMI Can Help
EMI helps research teams build stronger sample strategies through rigorous supplier evaluation, quality checks, fraud mitigation, and transparent sample consulting. Instead of treating sample as a commodity, we work with clients to identify the right blend of sources for each project and apply quality controls designed around the business decision at stake.
Trend 2: Fraud Is Becoming More Sophisticated, Technical, and Organized
Survey fraud is no longer limited to speeders or inattentive respondents. The report profiles a new generation of fraudsters who use AI-generated responses, VPNs, proxies, manipulated devices, emulators, and bot networks to bypass traditional safeguards, often gaining access in the first place by exploiting unsecured survey pathways. EMI identifies several of these personas, including respondents who shift identities across surveys, mask their digital footprint, misrepresent their location, manipulate device configurations, orchestrate automated participation, or trigger “ghost completes” without a real person behind them. Together, they add up to a more complicated threat environment, one where no single fraud check catches everything.
How EMI Can Help
EMI takes a layered approach to quality, combining Pre-Study traffic evaluation, In-Study behavioral checks, fraud detection tools, Post-Study validation, and ongoing supplier monitoring. This helps clients reduce exposure to manipulated data while maintaining realistic expectations around feasibility and sample availability.
Trend 3: AI Is Reshaping Research Workflows and Respondent Behavior
Artificial intelligence is now present across the market research workflow, from survey programming and coding to reporting, creative testing, AI moderators, conversational surveys, and research assistants. But AI is also changing respondent behavior. Consumers are more familiar with generative AI platforms, more likely to use them in everyday tasks, and potentially more likely to bring them into survey participation. This opens the door to faster workflows but also raises new questions about integrity, attention, and data validity. EMI’s report shows that ChatGPT leads consumer familiarity and recent usage, while tools like Gemini, Copilot, Claude, Grok, and Perplexity show varying levels of awareness and adoption.
How EMI Can Help
EMI helps clients understand how AI is affecting the sample ecosystem, from respondent engagement to fraud risk and survey design. By tracking AI awareness, usage, and behavior over time, EMI gives researchers a clearer view of how technology is influencing the data they collect.
Trend 4: High-Frequency Survey Takers Are Changing the Sample Landscape
High-frequency survey takers are respondents who attempt 100 or more surveys in a 24-hour period. EMI’s tracking shows this group has grown over time and now makes up a meaningful share of respondent traffic. Their behavior can affect results: high-frequency survey takers may report lower brand awareness while rating brands and concepts more favorably, creating patterns that can distort insights if they go unidentified. Knowing who completes a survey is only half the picture. Researchers also need to understand how those same respondents behave across the wider sample ecosystem.
How EMI Can Help
EMI monitors respondent activity and applies quality standards that help identify high-risk participation patterns. By evaluating survey activity, behavioral indicators, and downstream data consistency, EMI helps clients reduce the influence of overactive or unreliable respondents.
Trend 5: Feasibility Pressure Is Becoming Harder to Ignore
Feasibility is one of the least-talked-about market research trends shaping 2026, but it may be one of the most important. Respondents are harder to engage, budgets are tighter, survey expectations are higher, and sample providers are under pressure to deliver more for less. At the same time, people have more competing demands on their attention. A long, poorly designed survey with a low incentive competes against every other survey out there, and against everything else a respondent could be spending their time on. As feasibility gets harder to come by, research teams will need to rethink how they design surveys, structure incentives, set expectations, and balance sample quality with fielding realities.
How EMI Can Help
EMI brings more than 25 years of sample industry expertise to help clients plan realistic, effective research. From audience feasibility and source selection to fielding strategy and quality management, EMI helps research teams make smarter trade-offs before a study launches.
Trend 6: Certification Alone Will Not Solve Sample Quality
ISO 20252 certification can provide a valuable framework for quality management in market research, but EMI’s findings suggest that certification alone doesn’t guarantee better sample quality. The report found variation between ISO-certified panels and non-certified panels, and even meaningful differences between certified panels themselves. This proves that frameworks help but execution decides the outcome. Quality comes down to what organizations actually do: how they monitor sample, validate respondents, evaluate partners, and act on quality signals.
How EMI Can Help
EMI evaluates partners and sample sources based on performance, quality behavior, and project outcomes, not labels alone. By combining standards with active monitoring, EMI helps clients move from quality claims to quality evidence.
Download the 2026 Sample Landscape Report
Get EMI’s full analysis of the market research trends shaping the sample industry, including:
- Evolving role of AI in research
- Impact of poor-quality data on insights
- Sophisticated fraud personas
- High-frequency survey taker behavior
- Feasibility and respondent engagement challenges
- Consumer adoption of generative AI
- Limitations of certification as a quality signal
Ready to make better sample decisions?
Reliable insights start with better sample strategy. EMI helps research teams understand the trade-offs behind sample quality, feasibility, cost, and speed, so they can make decisions with confidence.
Frequently Asked Questions
Key trends include the growing role of artificial intelligence, rising concern around data quality, more sophisticated survey fraud, tighter feasibility, greater scrutiny of sample sources, and shifting respondent behavior. EMI’s Sample Landscape Report shows these are no longer emerging issues. They’re now structural realities shaping how online research is conducted and evaluated.
Data quality is important because poor-quality responses can change the outcome of a study. If fraudulent, inattentive, or overactive respondents are included in the final dataset, key metrics such as brand awareness, brand rating, and purchase intent may be distorted. EMI’s research found that unfiltered data can bias brand awareness by as much as 18 percentage points, which can lead to incorrect business decisions.
AI is changing market research in several ways. Research teams are using AI for survey programming, coding, reporting, creative testing, online qualitative moderation, conversational surveys, and analysis support. At the same time, consumers are increasingly familiar with generative AI tools, which may influence how they answer surveys or interact with research experiences. This creates both opportunities for efficiency and new risks for data integrity.