EMI - Research Solutions

Sometimes the first sign your sample strategy is failing isn’t obvious. It’s the brand tracker showing a spike that makes no sense. The major PR crisis that somehow never appears in your data. The panel provider asking to loosen quotas “just this once.” When your data and reality stop lining up, it’s usually not random. In our latest blog, we break down some of the biggest warning signs that your research strategy may need an upgrade, including how unstable sample sources, weak respondent verification, and “set it and forget it” panel management can quietly introduce bias into your studies. One of the biggest misconceptions in research today: There’s no such thing as a “perfect panel.” The companies getting the best insights aren’t relying on static sample sources. They’re continuously monitoring, adjusting, and strategically blending sources to maintain data quality over time. Read more here: https://hubs.li/Q04j4qFn0 #MarketResearch #ConsumerInsights #DataQuality #MRX #Innovation #SurveyResearch

If an AI company sells its technology to the government, should it still have a say in how that technology is used? That debate became very real earlier this year when Anthropic reportedly attempted to restrict how the Department of Defense could use its AI systems, particularly around military and surveillance applications. We wanted to know what consumers think. Do Americans support AI companies placing limits on government or military use of their technology? The results were more nuanced than you might expect. Support for restrictions was surprisingly consistent across political parties, varied significantly by income and age, and shifted dramatically depending on panel source. One panel showed support at 52%. Another came in at just 36%. The findings raise important questions not only about AI ethics, but also about how researchers should think about source bias in public opinion research. Read the full breakdown here: https://hubs.li/Q04j4--Z0 #AI #ArtificialIntelligence #MarketResearch #ConsumerInsights #AIethics #DataQuality

❌ False positives cost you sample efficiency. ❌ False negatives cost you data integrity. Both happen more often than most researchers realize because no single fraud detection platform catches everything. ����𝗵𝗲 𝗿𝗲𝗮𝗹 𝗶𝗺𝗽𝗮𝗰𝘁: •False positives reject valid respondents, shrinking your sample and increasing costs to hit targets •False negatives let fraudulent responses through, compromising the insights you deliver to clients •The balance between precision and protection varies dramatically across platforms—some err on the side of caution, others prioritize throughput •Our testing showed that platforms often agreed on obvious fraud and clear legitimacy, but diverged sharply on the borderline cases that actually matter Our independent evaluation tested five systems across consumer, B2B, and healthcare audiences to identify which approaches balance both concerns. The findings challenge common assumptions about "good enough" data quality: https://hubs.li/Q040zg7c0

Every year, we publish The Sample Landscape Report so you can see what's actually happening in online research—not what vendors are telling you. The 2026 edition covers fraud sophistication, high-frequency survey takers, the ISO certification reality, synthetic respondents, and where consumers stand on generative AI. It's 81 pages of research-on-research. No fluff. No sales pitch. Download your free copy. https://hubs.li/Q04gKgT80

Should AI companies work with the government? For defense? For national security? You’d expect strong opinions...instead the results are somewhat evenly distributed. Check out our new blog for the details: https://hubs.li/Q04fG9Y70 #publicopinion #mrx #AI

Summer movie season is just around the corner! There are lots of movies consumers are excited to see. In our recent round of research-on-research, we asked consumers which ones they were most excited to see. And Tom Holland's fourth go around as Spiderman took the crown! #mrx #consumeropinion #movies

Your data looks fine. Your quotas are being met. So why does something feel off? Most research teams don't realize their sample strategy is introducing bias until it's already done damage. A brand tracker that doesn't reflect a PR crisis, a spike with no market explanation. After 15 years of research-on-research, we can tell you the problem usually isn't a bad vendor. It's a flawed assumption about where bias actually comes from. We broke it all down. https://hubs.li/Q04fm-Jk0

👩⚕️ Nursing professionals make critical decisions about patient care, product recommendations, and healthcare technology, influencing medical practices and outcomes. EMI's healthcare network includes nurses across all specialties and practice settings. We connect you with frontline professionals who shape patient care delivery daily. #EMI #HealthcareResearch #MarketResearch #DataCollection #QualityAssurance

Can you support deportation…but oppose how it’s enforced? Based on data from our recent round of research-on-research, a lot of people do. Get all the details: https://hubs.ly/Q04frVkc0 #publicopinion #marketresearch

Speeders and inattentive respondents used to be the fraud problem. They're not anymore. Today's fraudsters build fake identities, rotate IP addresses, run bot networks, and manipulate device hardware — all to look like your ideal respondent. The 2026 Sample Landscape Report names them, profiles them, and shows exactly what they're doing to your data. Read the full report:https://hubs.li/Q04gK3Cx0