Cassandra vs Lifesight: unified marketing measurement, or an AI marketing brain that does the work
Lifesight offers causal MMM, incrementality testing and causal attribution in one platform, and says every test calibrates its model. Cassandra, an AI marketing brain for growth teams, measures with a Bayesian marketing mix model checked by live geo experiments and does the work.
Both calibrate a marketing mix model with experiments and include attribution. Lifesight is built around unified measurement; Cassandra around the work: plans, budget moves, ads, creative and reports.
What Cassandra is
- An AI marketing brain for growth teams: it learns what drives growth and does the work.
- Measures with a Bayesian marketing mix model checked by live geo experiments.
- Does the work within the rules the team sets: plans, budgets, ads, creative, reports.
- Approvals: the team decides what waits; every change is recorded.
How this comparison was made
Everything about Lifesight comes from its own public pages, read on 12 October 2026. We have not tested their product. If anything is out of date, write to hello@cassandra.app and we will correct it.
When Lifesight is the better choice
- One platform: attribution, modeling and experiments, for performance and analytics teams now on different tools.
- Ad-set and ad-level readings: listed on Lifesight's Precision and Enterprise plans.
- Broad connectors: Lifesight advertises more than 200 integrations, including Amazon Ads, Criteo, Klaviyo, BigQuery and Snowflake.
- Budget optimization: its Precision and Enterprise plans list always-on AI budget optimization.
What each one says it is
- Lifesight describes itself as "Agentic Unified Marketing Measurement": causal MMM, incrementality testing and causal attribution in one platform.
- Cassandra: an AI marketing brain that learns what drives growth and does the work.
- Both calibrate a marketing mix model with experiments, aiming at a figure finance will accept.
What Lifesight publishes about its method
Lifesight's pages describe:
- Causal MMM blending marketing mix modeling with geo-test calibration.
- Lift results: significant ones "re-weight priors and tighten the curve’s bands for that channel/market".
- A Model Card: each change is versioned and visible there.
- Geo tests: synthetic control picks test and control regions; one-click MMM calibration with geo-test learnings.
- Plans: causal attribution and geo-lift testing on every plan; causal MMM with geo-test calibration from Precision up.
Unified measurement and a marketing brain
- What is combined: Lifesight combines MMM, testing and causal attribution; Cassandra, measurement and the work that follows.
- Granularity: Lifesight lists channel and campaign on Performance, ad set and ad on Precision and Enterprise.
- Acting: Lifesight says you can push to platforms in one click or let agents act within your guardrails.
How each treats attribution
- Two views: attribution divides tracked conversions among touchpoints; a marketing mix model decomposes the whole outcome, baseline included.
- Lifesight's FAQ: triangulating MMM, experiments and causal attribution helps eliminate bias from platform-reported metrics, it says.
- Cassandra checks attribution against measured lift.
- Example: attribution often credits brand search heavily; a model separating baseline demand may credit it less.
- A geo test pausing brand search in some regions shows which view the evidence supports.
What each says about pricing
- Lifesight: three plans, Performance, Precision and Enterprise, each with a Book a Demo button.
- One annual subscription for all modules, depending on your data and marketing maturity level, Lifesight says.
- An estimate from its experts, so pricing is quoted on request.
Cassandra: start for free with your website and data, or book a demo. Paid plans scale with yearly ad spend.
Limits worth knowing
- Spend history: a channel needs enough spend, and variation in it, for the model to read.
- Regions: geo experiments need regional structure and a comparison group.
- Time: tests need a few weeks; keep test regions free of other changes.
Cassandra, an AI marketing brain for growth teams, learns what drives your growth and does the work within the rules your team sets. Start for free with your website and data, or book a demo.
What moving between platforms involves
- History and experiments move with you: experiments changed spend on purpose, so they stay the most reliable evidence.
- To Cassandra: decide in advance what waits for approval and which figure governs the budget split.
- Run both in parallel: where they differ on a channel, the reason is usually the baseline.
How to choose
- Lifesight: one platform for causal MMM, testing and attribution, ad-set and ad readings on higher plans.
- Cassandra: a marketing brain that measures, then does the work within the rules your team sets.
- Undecided: ask both what they show when attribution and the model disagree on a channel.
Questions
What is the difference between Cassandra and Lifesight for marketing mix modeling?
Both calibrate a marketing mix model with geo experiments and include attribution. Lifesight describes unified measurement in one platform. Cassandra, an AI marketing brain, checks attribution against measured lift and does the work.
How is Lifesight priced?
Pricing is quoted on request. Lifesight's pricing page offers a single annual subscription that depends on your data and marketing maturity, with an estimate from its experts.
Do Lifesight's experiments feed its model?
Yes, according to Lifesight: significant lift results re-weight its MMM's priors, and each change is versioned and visible in a Model Card.
What is unified marketing measurement?
An approach that combines attribution, marketing mix modeling and incrementality testing in one system, so different teams work from one set of figures.
What are alternatives to Lifesight?
Our list of marketing mix modeling software sets out several platforms and who each suits, including Cassandra, an AI marketing brain that learns what drives growth and does the work for the team.