Cassandra vs Measured: how the two marketing mix modeling platforms compare
Measured publishes claims across marketing mix modeling, incrementality, geo experiments, holdouts, multi-touch attribution and calibration, and positions itself for enterprise brands. Measured suits buyers who want one vendor for everything. Cassandra, the marketing mix modeling platform, pairs a Bayesian model with geo experiments and suits budget planning that experiments check.
The two overlap on marketing mix modeling and experiments, and differ on how much else each covers. Measured's published scope includes attribution, and ours does not. The two also differ in how they combine methods, in their inference framework and in whether a price is published. This page sets out what each says it is, what Measured publishes about its method and pricing, where the two differ, when Measured is the better choice, and the questions worth asking both. Everything about Measured comes from its own published pages.
What Cassandra is
Cassandra is a marketing mix modeling platform. Its production engine is a Bayesian model built on PyMC, so every channel effect comes back as a distribution with its uncertainty stated. Geo experiments are designed and run in the same system, using the same method family as GeoLift, and each result enters the model as a constraint rather than as a separate report.
Reads sit at campaign level, in the planning layer, and nothing changes in an ad account unless a person confirms the exact figure. The platform does not do multi-touch attribution.
It is not built on Google Meridian. Meridian is one of three model engines a project can choose, it is being retired, and it is not offered on new projects.
How this comparison was made
Everything below about Measured comes from what Measured publishes. We read their homepage, methodology, integrations, resources and about pages on 14 September 2026, and quoted what we found.
We have not tested their product. Where we say they do not publish something, we mean we could not find it on the pages we could reach.
If something here is out of date, tell us and we will correct it, and the correction will carry its own date.
When Measured is the better choice
You want one contract covering attribution, modeling and experiments. Measured publishes claims across all three. If the current problem is that several tools produce several numbers and nobody reconciles them, one vendor covering the whole stack addresses it directly.
You are the enterprise buyer they describe. Their own description is "the AI-powered marketing effectiveness platform trusted by enterprise brands", captured 14 September 2026.
You need multi-touch attribution alongside the model. Measured publishes an attribution claim, and Cassandra does not offer attribution.
What each one says it is
Measured describes itself as "the AI-powered marketing effectiveness platform trusted by enterprise brands", and frames its work as turning complex media portfolios into accountable growth programmes.
Cassandra, the marketing mix modeling platform, describes itself around one pairing: a Bayesian model of the whole mix, calibrated by geo experiments run in the same system.
The first is a broad measurement platform for large portfolios. The second is a model and experiment pair for budget planning.
Both sell to marketing and finance teams that need to justify spend, and both talk about incrementality. The difference is how much of the measurement stack each covers, and how the pieces relate to each other.
What Measured publishes about its method
Across the pages we reached, Measured publishes claims covering marketing mix modeling, incrementality, geo experiments, holdout testing, multi-touch attribution, causal inference, calibration and self-serve access. That is eight of the ten method claims we check for. Two vendors publish all ten.
It does not publish a Bayesian claim on any page we reached, and it does not publish an open methodology on those pages. Of the twenty-one vendors we checked, twelve publish an open methodology. Not publishing a claim is different from not doing something, and we cannot establish from outside how their model is built.
Their published scope covers eight of the ten methods we check for, which fits their enterprise positioning: a buyer consolidating several measurement tools can find most methods under one contract.
Where the two differ
Scope. Measured publishes claims covering attribution, modeling and experiments. We cover modeling and experiments and do not offer attribution.
Inference framework. Our production engine is Bayesian, so each channel's effect comes with its uncertainty stated. Measured does not publish a Bayesian claim on the pages we reached.
Experiments. Both publish geo experiment claims. Measured also publishes holdout testing. We design and run geo experiments in the same system as the model.
How methods are combined. Measured presents results from several methods in one platform. We feed experiment results into the model as constraints, so the model has to agree with the tests.
Positioning. Measured names enterprise brands. We position on budget planning that finance or a client will review.
Pricing. We publish a price. We found no pricing page and no price for Measured.
One platform for everything, or a model checked by experiments
A platform that reports attribution and models the mix produces two views of the same channel from one vendor. When they differ, the platform reconciles them and presents one result. That is useful when the alternative is an unresolved argument between several tools.
Some decisions benefit from seeing the disagreement itself. When a budget change has to be defended to finance, knowing why two methods disagree, and which one the experiment evidence supports, is part of the defence. A reconciled number has already made that choice.
Which approach suits a business depends on how its measurement is used and reviewed.
An example: a platform's attribution view credits paid social with a strong return, and a model shows a smaller one. A reconciled platform might present a blended figure. A model calibrated by a geo test on paid social shows which of the two the experiment supports, and by how much. The second is more work to read, and easier to defend when the budget is questioned.
What Measured publishes about pricing
We checked measured.com, /pricing, /plans and /pricing-plans on 14 September 2026. We found no pricing page and no price on the pages we could reach, and no mention of a trial or free tier.
Fifteen of the twenty-one vendors we checked publish a pricing page, and Measured is among those that do not. In practice this means cost can be compared only after a sales conversation. For an enterprise procurement process with a scoping phase, that changes little. For a team that needs a figure for this quarter's plan, it affects the timeline.
A published price is also useful as a reference even when a business goes on to negotiate, because it shows the scale of commitment before any call.
Questions to ask both vendors
Show me the assumptions on a live model, and change one. A model whose assumptions cannot be seen is hard to defend.
Export the output behind this chart. The numbers, in a file you keep.
Which model version produced last quarter's result, and can you rerun it? Without this, past results cannot be checked.
How are experiment results used? Shown alongside the model, or used to calibrate it.
What does the platform not answer? Every model has limits, and a vendor should be able to name them.
What happens if we leave? Which data, outputs and model settings you can take with you, and in what form.
Asking the same questions of both vendors, in the same order, makes the answers comparable. Vague answers to the first two are the clearest signal that a model will be hard to defend later.
What we do not do
Reads sit at campaign level. The platform does not read ad sets or audience groups, and it is not a day-to-day optimiser. For decisions such as which creative to pause today, an attribution tool or the ad platform is the right instrument.
A channel needs enough history behind it, and enough movement in that spend to read against. A channel launched last month at a flat budget returns a wide range, which is the accurate answer for that data.
Geo experiments need regional structure. A business operating in a single market, with no way to build a comparison group, cannot run one.
And the platform does not offer attribution. Teams that need path-level reporting keep their attribution tool alongside it, with each used for the decisions it suits.
Cassandra, the marketing mix modeling platform, is the narrower option: a Bayesian model and geo experiments calibrated against each other, with priors your team helps set and output you can export.
A price is published. On the pages we could reach, Measured does not publish one, which is a difference in disclosure and says nothing about what either costs.
What moving between platforms involves
A cleaned, reconciled history of spend and outcomes is what either platform needs, and assembling it is most of the work. It moves with you.
Experiment results move too, and they remain valid evidence in any model. Record each test's design and result in a form that does not depend on either platform.
What does not move is the reporting your team is used to. Plan for a period of running both, so that differences between the old and new results can be explained before budgets depend on them.
If attribution was part of what the old platform supplied, decide before the switch where attribution will live afterwards, so that no report disappears without a replacement.
How to choose
One main question, where the budget should go, reviewed by finance: Cassandra's model and experiment pair.
Several questions across attribution, modeling and experiments, and too many tools answering them: Measured's broader platform.
Unsure which applies: list the decisions measurement has to support over the next year. If most of them are budget splits across channels, the narrower pair fits. If they span daily optimisation, attribution and planning, the broader platform fits.
A price needed before any call: Cassandra publishes one. Measured's pages do not.
Questions
What is the difference between Cassandra and Measured for marketing mix modeling?
Measured publishes claims across modeling, incrementality, experiments and attribution, and positions for enterprise brands. Cassandra, a marketing mix modeling platform, pairs a Bayesian model with geo experiments that calibrate it, and does not offer attribution.
Does Measured publish pricing?
We checked their homepage, /pricing, /plans and /pricing-plans on 14 September 2026 and found no pricing page and no price. Fifteen of the twenty-one vendors we checked publish a pricing page.
Is Measured a Bayesian marketing mix model?
They do not publish a Bayesian claim on the pages we reached. That describes what they publish, and we cannot establish from outside how their model is built.
Which is better for enterprise brands?
Measured's own positioning names enterprise brands. For a large portfolio where several tools produce several numbers, one vendor covering the whole stack is a strong option.
What are alternatives to Measured?
Vendors that publish both geo experiment and holdout claims include Haus, Sellforte, SegmentStream, Recast and Cassandra, a marketing mix modeling platform. Our list of incrementality tools sets out who each suits.