EmptoSight
EmptoSight is a synthetic survey simulation platform that lets marketing, product, and research teams test pricing, promotions, channel strategies, and creative variants on AI-powered consumer panels built from real shopping data. The platform reduces traditional 3–6 week research cycles to minutes, enabling rapid iteration across the marketing funnel before committing media or production budgets.
- Data & Analytics
- Artificial Intelligence
- Software Only
- Marketing Technology
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional consumer research methods are slow and expensive, with typical turnaround times of 3–6 weeks, small sample sizes of 200–500 respondents, and high iteration costs per wave. This makes it difficult for companies to test multiple marketing strategies, pricing points, or creative variations before committing significant media or production budgets.
Solution
EmptoSight provides a synthetic survey simulation platform that enables companies to test marketing strategies on AI-powered consumer panels built from real shopping data. The platform allows users to simulate thousands of marketing decisions in seconds, running large synthetic panels with speed and consistency that traditional methods cannot match. By replacing conventional testing with a self-serve, low-cost alternative, EmptoSight enables rapid iteration across the marketing funnel—from pricing and promotions to channel strategy and product launches. Users can identify weak concepts, claims, or price points before spending real budget, reducing risk and improving decision-making efficiency.
Target Audience
Primary customers are marketing, product, and research teams at consumer brands and agencies who need fast, cost-effective consumer insights to validate strategies before committing budget.
Features
- Synthetic panels generated from real shopping data for realistic consumer behavior modeling
- Large panel sizes supporting thousands of simulated respondents per scenario
- Rapid scenario testing in minutes, compared to 3–6 weeks for traditional methods
- Low iteration cost per scenario, enabling frequent testing across multiple variables
- Self-serve workflow with no heavy logistics or coordination required
- Use cases spanning pricing elasticity, promotion structures, channel mix, product adoption curves, and A/B creative testing