INCRMNTAL
An ad incrementality measurement platform with no tracking or holdout tests
INCRMNTAL is an Israeli measurement platform that continuously estimates advertising incrementality using causal models on existing campaign data, avoiding user-level tracking and dedicated holdout tests for mobile and web advertisers.
Key Features
- Continuous ad incrementality assessment
- Causal-model-based algorithms
- No user-level tracking required
- No dedicated holdout tests needed
- Supports web and mobile applications
Pros
- Protects user privacy without violations
- Saves testing time and opportunity cost
- Provides real-time, objective marketing performance
Cons
- Requires a certain scale of ad data
- A relatively steep learning curve
Use Cases
- Cross-channel ad budget optimization
- Assessing the true benefit of marketing campaigns
- Performance attribution under privacy restrictions
Editor's Note
By using causal models to break through privacy limits, INCRMNTAL is a powerful tool for marketing teams that value both true performance and privacy.
FAQ
How does INCRMNTAL measure incrementality without holdout tests?
It uses advanced causal-inference models to analyze existing marketing and business data to continuously estimate the true incremental effect of ads.
Does this platform need to track individual users' data?
No. INCRMNTAL uses a method that doesn't rely on user-level tracking, perfectly fitting current privacy trends.
What size of advertiser is it suitable for?
It suits web and mobile app advertisers with larger budgets who run cross-channel marketing and value true ad effectiveness.
Related AI Tools
Motobook
Taiwan's used scooter market at a glance—see the resale value of gas and electric bikes under the sun.
Carbook
Turn “What’s this car really worth?” into a clear, searchable number for Taiwan’s used‑car market.
實價雷達 HouseTW
A free Taiwanese real estate platform overlaying 3.49 million official transaction records with soil liquefaction, fault lines, and flood risk maps.
Perplexity
AI‑powered search with built‑in source citations