Lifesight vs Other Testing Vendors

Feature	Description	Lifesight	Other Experiment Vendors
Advanced Causal Estimation Methodology	Uses a multi-objective augmented Synthetic Control framework combined with Difference-in-Differences (DiD) to estimate counterfactual outcomes under real-world constraints.	✅	⚠️
Simulation-Driven Counterfactual Estimation	Runs large-scale simulations to estimate counterfactual lift and uncertainty, rather than relying on a single point estimate from one test/control comparison.	✅	❌
Multi-Metric Market Diagnostics	Evaluates experiments using multiple market-level diagnostics such as market share shifts, incremental spend, minimum detectable lift (MDL), synthetic control imbalance, estimated lift, and estimated bias.	✅	❌
High-Power, High-Velocity Test Design	Designed to maximize statistical power while enabling faster test cycles through optimal market selection, pooling, and synthetic control construction.	✅	⚠️
Single-Cell & Multi-Cell Experiments	Supports simple single-cell tests as well as complex multi-cell and multi-arm experiments across markets, tactics, or budget levels.	✅	⚠️
Multiple KPI Support	Natively supports multiple primary and secondary KPIs within a single experiment, enabling full-funnel and trade-off analysis.	✅	⚠️
Generalization via Attribution Calibration	Uses experimental results to calibrate attribution systems, allowing localized test results to be scaled across channels, tactics, and time.	✅	❌
Generalization via Model Calibration	Integrates experiment outcomes directly into Lifesight’s causal models, enabling generalization of lift estimates beyond tested markets.	✅	❌
Ingest External Platform Experiments	Supports ingestion and evaluation of experiments run on external ad platforms (e.g., Meta, Google, Amazon), treating them as inputs rather than isolated studies.	✅	⚠️
Incrementality Adjustment for Delayed Impact	Adjusts delayed impact by augmenting the adstock effects from the models	✅	❌
Monitors for Test Contamination	Monitors for spend across all the channels and flags test contamination and pacing risks	✅	❌
Spillover risk monitoring	For granular geo-tests, use proprietary mobilty data to adjust for potential spillover between test and control groups	✅	❌

Find more about Lifesight's Incrementality Testing approach here