Emporia for Enterprises
Confident Decisions at Enterprise Scale
Empower strategy, product, and go-to-market teams with same-day signals from LinkedIn-verified decision-makers. Emporia pairs rigorous B2B verification and fraud defense with study tooling and interactive reporting—so you can validate bets, reduce risk, and move faster.
Same-Day Data
Launch a pulse survey, interview sprint, or concept test in minutes; see responses the same day your project goes live—so stakeholders aren’t waiting on insight.
Verified Decision-Makers
Every participant is LinkedIn-verified and fraud-screened, ensuring you hear from real buyers, users, and influencers in your ICP—not panel noise.
DIY or Managed (Embedded)
Run studies self-serve, or have our managed service team embedded alongside your PMM, CX, or Insights org to handle screeners, quotas, scheduling, and QA.
Enterprise-Grade Controls
Audit trails, consistent screeners, PII-safe workflows, and transparent quality signals—built for governance, repeatability, and cross-functional visibility.
Emporia gives us another perspective. Our product team does a really great job working with our existing customers: understanding and solving for their needs. Emporia allows me to find new audiences and conduct that initial research that helps set the stage for potential new customers, products and markets.
We are often trying to recruit hard to reach audiences and so it's imperative for us to have high quality data and verified respondents. Emporia go above and beyond to help us and our agency partners not only reach the right audiences but enhance our customer understanding which is a great experience.
Client Success Stories
Unlocking New Perspectives from Sales and Revenue Leaders
3 min read
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Unlocking Verified Perspectives from Operations and Technology Leaders
5 minute read
Unlock the Power of AI-Driven B2B Market Research with Synthetics
Discover how synthetic agentic audiences deliver faster insights, enhanced scalability, and improved ROI for your brand clients—without compromising data quality.
