Cassandra vs LiftLab: agile MMM and testing, or an AI marketing brain that does the work
LiftLab publishes a loop between agile marketing mix modeling and incrementality testing, aimed at growth leaders, boards and CFOs. Cassandra, an AI marketing brain for growth teams, measures with a Bayesian marketing mix model checked by live geo experiments, then does the work.
Both run a model and experiments that check it, in a repeating cycle. They differ in inference framework, what follows the measurement, audience and how each is bought.
What Cassandra is
- An AI marketing brain for growth teams that 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, budget moves, ads, creative and reports.
- Approvals: the team decides what waits for approval, and every move is checked against its forecast.
How this comparison was made
Everything about LiftLab 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If anything is out of date, write to hello@cassandra.app and we will correct it.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 LiftLab is the better choice
- Your audience is a board: LiftLab's framing names a board and a CFO explicitly.
- The loop matters more than the framework: a team that will not inspect priors can choose on other grounds.
- A published methodology: LiftLab publishes one.
- A faster modeling cycle: "Agile" is LiftLab's word, aimed at teams planning faster than quarterly.
What each one says it is
- LiftLab's homepage heading: "Agile Marketing Mix Modeling for Growth Leaders" (captured 14 September 2026).
- Its description says it closes the loop between agile MMM and incrementality testing, for a board and a CFO.
- Cassandra describes itself as an AI marketing brain for growth teams.
- Both describe a loop: model, test, recalibrate, repeat.
Where the published claims differ
- Across the pages we reached, LiftLab publishes claims on MMM, incrementality, geo and holdout tests, and calibration.
- Inference: Cassandra measures with a Bayesian marketing mix model.
- Audience: LiftLab names growth leaders, boards and CFOs; Cassandra names growth teams and agencies.
- After the measurement: Cassandra plans, moves budgets, manages ads, makes creative and writes reports.
Why the inference framework matters inside a loop
- In a loop, the model must take in each test result and carry it across the mix.
- A Bayesian model takes a result in as a prior or a fit term, and shows how far each range narrowed.
- Other frameworks can use test results too, for example as calibration constraints.
- Ask LiftLab how its model is built; we cannot establish it from outside.
What each publishes about pricing
- LiftLab says it does not publish a flat pricing card, so pricing is quoted on request.
- Cassandra: start for free with your website and data. Paid plans scale with yearly ad spend.
Questions to ask both vendors
- When a test result lands, what changes in the model, and can I see it?
- What does "agile" mean in practice? How often the model is refitted.
- Show me the assumptions on a live model, and change one.
- Which model version produced last quarter's plan, and can you rerun it?
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 to build a comparison group.
- Time: tests need a few weeks, free of other changes in the test regions.
Cassandra is an AI marketing brain for growth teams. It measures with a Bayesian marketing mix model checked by live geo experiments, and does the work. Start for free with your website and data, or book a demo.
What moving between platforms involves
- The experiment record moves with you: each test stays valid evidence in any model.
- So does the cleaned history. The new work is priors: agreeing them, and recording who set each.
- Run both for a cycle and compare how each takes in the same recent test.
How to choose
- LiftLab: a board-facing narrative, a faster modeling cycle, or a published methodology your reviewers know.
- Cassandra: a Bayesian model checked by geo experiments, and the work done for the team.
- Undecided: run both on the same history for one cycle.
Questions
What is the difference between Cassandra and LiftLab for marketing mix modeling?
Both link a marketing mix model with incrementality tests in a loop. LiftLab names boards and CFOs and publishes an open methodology. Cassandra, an AI marketing brain, uses a Bayesian model checked by geo experiments and does the work: plans, budgets, ads, creative and reports.
Does LiftLab publish pricing?
LiftLab says it does not publish a flat pricing card, so pricing is quoted on request.
What does LiftLab focus on?
Marketing mix modeling and experiments, framed for finance and leadership decisions, as LiftLab's own pages describe.
What does agile marketing mix modeling mean?
A marketing mix model refitted more often than the traditional quarterly or annual study, so that new data and test results reach the plan sooner.
What are alternatives to LiftLab?
Vendors publishing both geo experiment and holdout claims include Measured, Haus and Recast. Cassandra, an AI marketing brain, is another option. Our list of incrementality tools sets out who each suits.