Lifesight vs Haus

Move Beyond Lift Tests to Unified Growth Measurement

Modern marketing teams are shifting from fragmented lift tests to continuous, AI-driven decisioning. Lifesight unifies MMM, attribution, incrementality, and optimization into one system.

How Lifesight compares with Haus

Below is a comparison of core features and marketing intelligence depth.

Capability

Geo-Incrementality Testing

Causal MMM

Causal Attribution

Unified Methodology (all three calibrated)

Forecasting & Scenario Planning

1-Click Platform Optimization

Agents That Execute

Continuous Measurement

Time to First Insight

Privacy & Compliance

Integrations

Haus

tick - Lifesight
tick - Lifesight

⚠️ Yes, Daily for Calibrated Channels

tick - Lifesight
cross - Lifesight
cross - Lifesight

⚠️ Basic AI features

cross - Lifesight Experiment-cycle only

6–8 weeks

tick - Lifesight SOC 2 Type 2, Privacy-first

tick - Lifesight

Lifesight

tick - Lifesight Yes (Unified with MMM + Attribution)

tick - Lifesight
tick - Lifesight
tick - Lifesight
tick - Lifesight
tick - Lifesight
tick - Lifesight
tick - Lifesight

6–8 weeks

tick - Lifesight GDPR, HIPAA, SOC 2, ISO

tick - Lifesight

Features

Lifesight

Haus

Geo-Incrementality Testing

tick - Lifesight
tick - Lifesight

Causal MMM

tick - Lifesight
tick - Lifesight

Causal Attribution

tick - Lifesight
tick - Lifesight

Unified Methodology (all three calibrated)

tick - Lifesight
cross - Lifesight

Forecasting & Scenario Planning

cross - Lifesight
tick - Lifesight

1-Click Platform Optimization

cross - Lifesight
tick - Lifesight

Agents That Execute

tick - Lifesight
cross - Lifesight

Continuous Measurement

tick - Lifesight
tick - Lifesight

Time to First Insight

cross - Lifesight
tick - Lifesight

Privacy & Compliance

⚠️ Partial / emerging capability

tick - Lifesight

Integrations

tick - Lifesight
tick - Lifesight

What Changes When You Run Measurement Continuously

Haus Causal Attribution gives daily answers for already-tested channels without re-running a test. True for new experiments, not every answer.

Causal MMM, incrementality testing, and causal attribution designed to calibrate each other, not pieced together after the fact. One number your marketing team and CFO can both stand behind.

Lifesight’s AI Agents don’t hand you a finding and wait. They surface a budget reallocation, run a spend scenario, and push the change directly to your ad platforms. One click from insight to action.

A Haus geo-lift test often takes 6–8 weeks to get answers. Lifesight’s causal model runs continuously, so when a channel shifts mid-quarter, you don’t wait for your next test window to know.

Paid, organic, upper funnel, lower funnel, offline, retail sales, direct mail sends all calibrated together. Not a dashboard that aggregates platform-reported numbers. A causal model that tells you what’s actually driving revenue.

Why teams choose Lifesight

When Haus Is the Right Choice

Haus is purpose-built for geo-lift experimentation and does it exceptionally well. If your primary goal is running rigorous, channel-by-channel incrementality tests, and your team has the runway to wait 6–10 weeks per answer, Haus is a strong tool for that job.

When Teams Move to Lifesight

The question isn’t whether geo-lift testing is valuable. It is. The question is whether experiments alone are enough to run your marketing.

Teams typically make the move when:

  • Experiments can’t keep pace with decisions. At 6–8 weeks per test plus post-treatment window, you can validate a handful of channels per quarter. When you’re managing 8–12 active channels, that math breaks down fast.
  • Untested channels stay unaccountable. Haus’s causal attribution calibrates using incrementality multipliers, but only for channels where you’ve run experiments. Every channel without a completed test is still flying on platform-reported numbers.
  • You need measurement to act, not just inform. Lifesight’s AI Agents take you from causal insight to one-click budget reallocation, directly to your ad platforms. The loop closes without leaving the platform.

Frequently asked questions

It depends on your needs. If you’re looking for incrementality testing alone, both platforms can help. If you need a broader measurement platform that combines MMM, Incrementality Testing, and Causal Attribution to support marketing optimization and forecasting, Lifesight is a strong alternative.

Lifesight is built for portfolio-level budget decisions. It combines causal MMM, incrementality testing, and causal attribution into one continuously running model, so you can reallocate across your entire mix with confidence, not just validate individual channels after 6–8 week test cycles. When you’re managing 8–12 active channels and need faster decision cycles, a unified always-on model outperforms an experiment-by-experiment approach.

Haus’s causal attribution calibrates platform-reported data using incrementality multipliers, but only for channels where you’ve completed experiments. Channels without test coverage remain uncalibrated. Lifesight’s causal attribution is unified with MMM from the ground up, giving you a calibrated view across every channel in your mix, including channels where geo experiments aren’t feasible. The result is one number across your full portfolio, not a patchwork of tested and untested channels.

No. Marketing teams run Lifesight without a data science team or engineering dependencies. Most customers are running unified measurement within 45–90 days of onboarding.

Why Wait Weeks for Insights You Can Get Faster?

Replace longer lift tests cycles with always-on marketing measurement.