Lifesight vs Competitors

Feature / Aspect	Lifesight	Recast	Haus	Measured	Workmagic
Methodology	Unified Causal Stack: Causal MMM + Incrementality testing (Geo and Time) + Causal Attribution	Bayesian MMM; purely econometrics-focused	Experiment-first: Geo-lift testing + basic MMM	Hybrid: MMM + MTA (Multi-Touch Attribution)	Hybrid: Experiments + MTA
Granularity	Ultra-granular: campaign, ad set, and ad-level insights	High-level: channel and tactic level	Limited: channel / tactic level only	Varies: granular via MTA, prone to signal loss	Limited: short-term forecasts; no tactic-level depth
Actionability	1-click optimization with direct platform integrations for budget re-allocation	Manual recommendations; execution required	Low: explains what happened, not what to do next	Standard budget optimizer; limited causal activation	Rudimentary: no weekly pacing or custom scenario planning
Expertise Needed	Marketer-centric: no-code UI; End-to-End configurable modeling framework	Backlog Modeling. Platform is used only to embed models built outside.	Technical: heavy experimental-design focus	Moderate: analyst support often required	Standard: marketer-friendly but less robust
Speed to Value	Immediate: causal insights in days after integration	Slow–medium: rigorous setup and modeling time	Slow: experiment-dependent (weeks/months)	Standard onboarding timelines	Standard setup; limited long-term insight