Comparison · Enterprise MMM

Same Bayesian MMM the Fortune 500 uses. $299 a month.

Enterprise Bayesian MMM vendors charge upwards of $1,500/month, with multi-week onboarding and a required account manager. MixLift charges $299 and takes five minutes.

See pricing

$299/mo

vs $1,500+ enterprise

< 5 min

vs 4-week onboarding

Month-to-month

No annual contract

How MixLift compares

Three tiers of Marketing Mix Modeling software.

The market has fragmented. The methodology is identical across all three. The price and the overhead are not.

Enterprise
Open-source DIY
MixLift
Methodology
Bayesian MMM
Bayesian MMM
Bayesian MMM
Price
$1,500+/month
Free + engineering cost
$299/month
Time to first result
4 weeks onboarding
~1 month engineering
5 minutes
Team required
Account manager
Data scientist
None
Contract
Annual
N/A
Month-to-month

The methodology

The math is identical. The price and the overhead are not.

The market for marketing mix modeling software has fragmented into three tiers that should not all carry the same label. There are enterprise platforms running rigorous Bayesian inference and charging upwards of $1,500 per month — for a dashboard plus a required account manager and a multi-week onboarding. There are open-source frameworksRobyn, Meridian — that give you the raw methodology and require a data scientist and a month of engineering to operationalize.

And then there is MixLift: the same Bayesian engine, the same credible intervals on channel-level ROAS, the same budget optimizer — delivered through a Claude conversation, at $299/month, with no onboarding call and no lock-in. Full PyMC-Marketing, 4-chain MCMC. 90% credible intervals on every estimate. Scenario modeling without refitting.

How it works

From CSV to channel-level ROAS in under five minutes.

01 · Connect

Upload weekly spend and revenue.

A single CSV with weekly rows per channel. No API integrations. No platform credentials. No data warehouse required.

02 · Model

Bayesian MMM runs in your Claude session.

Full PyMC-Marketing pipeline — 4-chain MCMC, adstock, saturation, seasonality controls. Posterior distributions on every estimate, not point estimates.

03 · Optimize

Ask the model what to change.

Budget recommendations, saturation curves, scenario modeling. All through conversation. Refits are not required for what-if questions.

Run it on your data. Month-to-month.

Start on the free tier — two channels, two analyses per month, the full Bayesian engine. See whether the math matches what your platform dashboards tell you. If it does not, you will know within the hour.

See pricing