INCRMNTAL
INCRMNTAL delivers continuous, cookie-free incrementality measurement that reveals the true causal impact of marketing spend, enabling marketers to optimize budgets based on real lift rather than misleading attribution proxies.
Last updated May 27, 2026 by ATDb automated enrichment · Connections updated Jun 1, 2026
- Industry
- Marketing Measurement & Attribution
- Business Model
- SaaS
- Target Market
- Mid-Market, Enterprise
- Employee Count
- 11-50
- API Available
- Yes
Emerging specialist in always-on incrementality measurement, positioned as a privacy-safe alternative to traditional MMP attribution and periodic MMM studies
INCRMNTAL is an Israeli-founded marketing measurement company specializing in incrementality-based attribution and causal inference for digital advertising. Unlike traditional last-touch or multi-touch attribution models, INCRMNTAL uses a continuous, always-on methodology to measure the true incremental lift of marketing campaigns — meaning it identifies what conversions or outcomes would not have happened without a specific ad spend. This approach is particularly valuable in a privacy-first world where user-level tracking is increasingly restricted. The platform is designed to work without cookies, device IDs, or personally identifiable information, making it resilient to signal loss from iOS privacy changes, GDPR, and the deprecation of third-party cookies. INCRMNTAL's technology uses statistical modeling and machine learning to create counterfactual baselines, enabling marketers to understand the genuine causal contribution of each marketing channel rather than relying on correlation-based proxies. INCRMNTAL serves mobile app publishers, performance marketers, and growth teams at brands and agencies who need to optimize budget allocation across channels. The company positions itself as a next-generation alternative to legacy MMP (Mobile Measurement Partner) attribution and media mix modeling (MMM), offering a more agile and granular solution that operates continuously rather than requiring periodic studies. It competes in the growing incrementality and causal measurement space alongside players like Measured, Northbeam, and Rockerbox.
Always-On Incrementality
Continuous incrementality measurement platform that runs without requiring holdout tests or campaign pauses, using causal inference to isolate true ad impact
Causal Attribution
Attribution methodology based on causal modeling rather than correlation, providing more accurate channel contribution analysis
Budget Optimization Insights
Actionable recommendations for reallocating marketing spend based on measured incremental returns per channel
Privacy-Safe Measurement
Measurement framework that operates without cookies, device IDs, or user-level data, compliant with modern privacy regulations
- 2021Founded