Lifesight

Lifesight

Lifesight is a marketing decision intelligence platform that unifies causal measurement (MMM, incrementality testing, calibrated attribution) with AI agents to produce actionable, auditable budget and experiment recommendations for marketing and finance teams.

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Lifesight

Lifesight combines Marketing Mix Modeling, geo-based incrementality testing, and incrementality-adjusted attribution into a single causal measurement engine to determine the true incremental value of marketing channels. The platform layers Marketing Intelligence Agents (MIA) on top of that causal foundation to design experiments, detect anomalies, translate measurement into CFO-ready language, and recommend budget reallocation or tests within guardrails you define. Lifesight is built for CMOs, performance teams, finance leaders, and agencies who need decisions they can defend — not just dashboards.

The platform also includes one-click optimization (Budget Optimizer) that reallocates spend based on incremental ROAS and can push changes to platforms like Google, Meta, Amazon, and TikTok, plus scenario planning and forecasting tools so teams can model outcomes before committing budget.

Lifesight is a marketing decision intelligence platform that unifies causal measurement (MMM, incrementality testing, calibrated attribution) with AI agents to produce actionable, auditable budget and experiment recommendations for marketing and finance teams.

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Key Features

Unified Causal Measurement Engine

Combines causal MMM, incrementality testing, and calibrated attribution into a single engine so methods validate one another and produce a single causal truth about what drives revenue.

Marketing Intelligence Agents (MIA)

AI agents built on the causal engine that reason across measurement layers to recommend actions, design experiments, detect anomalies, generate CFO-ready reports, and monitor creative performance within user-defined guardrails.

Budget Optimizer

Automatic budget reallocation driven by incremental ROAS (iROAS) rather than platform-reported metrics, with the ability to push changes directly to ad platforms.

Scenario Planner & Forecasting

Model budget scenarios (best case, base case, worst case) with confidence intervals to forecast profit and growth before committing spend.

Experiment Designer

Automated design of incrementality tests (e.g., geo-lift tests) that validate model recommendations prior to full-scale reallocations.

Anomaly Hunter

Continuous monitoring that detects data or performance anomalies across channels and campaigns.

CFO Bridge & Board-ready Reporting

Auto-generated, auditable P&L language reporting showing incremental revenue, payback periods, and profit contribution for finance sign-off.

Integrations & Data Ingestion

Native connectors to major ad platforms, commerce and data sources with a native data warehouse and support for 50+ integrations to unify signals for measurement.

Creative Intelligence

Monitoring and analysis for creative performance so teams can identify what creative assets drive incremental outcomes.

Pricing

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Use Cases

Improve Profitability

Identify and invest in channels and tactics that generate true incremental profit and reduce spend on non-incremental activity.

Forecast Growth

Model the impact of budget shifts across channels with confidence intervals to plan for periods like Q4 with data-driven scenarios.

Maximize Media Efficiency

Optimize spend using incremental ROAS to ensure budgets are allocated where they deliver the most incremental return.

Acquire New Customers

Measure and validate the incremental acquisition impact of channels and campaigns to scale customer acquisition more efficiently.

Align Marketing & Finance

Provide auditable, CFO-language reporting on incremental revenue and profit contribution so marketing and finance share a single causal truth.

Validate Channel Shifts with Experiments

Design and run geo-lift tests or other incrementality experiments to confirm model-driven recommendations before committing full budgets.

Integrations

Google

Connects advertising data for unified measurement and can receive budget optimizer activations.

Meta

Ingests Meta performance data, supports causal measurement, and accepts optimizer-driven budget changes.

Amazon

Supports Amazon ad data ingestion and measurement to attribute incremental retail outcomes.

TikTok

Connects TikTok ad data for inclusion in unified causal models and optimizer actions.

Shopify

Commerce connector to map ad-driven activity to sales and revenue in the measurement engine.

The Trade Desk

CTV and programmatic connector to include connected TV and programmatic spend in causal measurement.

Native Data Warehouse

Built-in data warehouse for unified ingestion, storage, and modeling of cross-channel signals.

Benefits

Provides causal, not correlational, measurement so teams know what actually drove outcomes.
Turns measurement into executable recommendations via AI agents, reducing manual analysis work.
Enables one-click optimization and direct activation on major ad platforms for faster budget execution.
Improves cross-team alignment by producing auditable, CFO-ready reports and a single source of truth.
Speeds time-to-insight — many customers receive causal insights within days of connecting data.
Supports privacy-first architecture (no user-level tracking) and enterprise security/compliance.

Limitations

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Frequently Asked Questions

What makes Lifesight different from traditional MMM or attribution tools?
Lifesight unifies causal MMM, incrementality testing, and calibrated attribution in one engine where the methodologies validate each other. Additionally, Marketing Intelligence Agents (MIA) turn those insights into executable recommendations and experiments rather than just dashboards.
Do we need a data scientist to use Lifesight?
No. Lifesight is designed for marketing teams; MIA handles analysis in plain language and the platform is no-code. Optional marketing science services are available for deeper support.
How long does it take to get started?
Most customers are live with causal insights within days of connecting their data, rather than the weeks or months traditional MMM often requires.
What does causal measurement mean?
Causal measurement proves what actually drove a business outcome using experiments and statistical methods to separate true impact from coincidence — it shows experimental evidence rather than platform-reported correlation.
Is our data secure?
Yes. Lifesight states compliance with HIPAA, GDPR, SOC 2 Type II, and ISO 27001. Data is encrypted in transit and at rest and the architecture is privacy-first with aggregated signals rather than user-level tracking.

Getting Started

  1. 1 Step 1: Book a demo or contact Lifesight to discuss your goals and required integrations.
  2. 2 Step 2: Connect your data sources and ad platforms (Lifesight supports 50+ integrations and a native data warehouse).
  3. 3 Step 3: Configure business rules/guardrails, review initial causal insights from MIA, and enable optimization or run recommended experiments.

Support

Demo

Book a demo through the Lifesight website to see the platform and discuss onboarding.

Documentation

Product docs and methodology guides available on Lifesight's website for self-serve learning and support.

Product Updates

Read about feature launches and what's new via the Product Updates section on the site.

Training / Academy

Lifesight Academy offers training and certification to become a marketing measurement expert.

API

Available: No

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