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Alternatives

The best INCRMNTAL alternatives.

Looking past INCRMNTAL for incrementality measurement? If the question is how much to spend in total and where, with TV and other offline media in the picture, the strongest alternative is Odins: one managed Bayesian model per market, with test results taken into the model. Odins is ours, so we say it up front. Four more options follow, sorted by who they fit.

Reviewed October 2026 · sources cited on this page

The alternatives

Five alternatives, sorted by fit.

INCRMNTAL measures incrementality without user-level data by treating marketing changes as micro-experiments, with deep roots in apps and gaming. These five take a different route. The best-for lines say which one suits you.

  1. Odins

    Managed Bayesian platform That's us

    Best INCRMNTAL alternative for advertisers who need the total budget sized, offline media included.

    Odins is a managed marketing investment platform. INCRMNTAL reads the incremental effect of the changes you make. Odins answers the standing budget question: one Bayesian model per market, with TV, radio, OOH and print next to digital, pricing and promotions, and results from tests you have run taken into the model. Data flows in daily and scenarios and forecasts are yours any time. The model is retrained monthly and checked against stored forecasts, and a person reviews every recommendation. Disclosure: this is our platform.

    Bayesian MMM · Fully managed · Daily data, monthly retrain Odins vs INCRMNTAL
  2. Lifesight

    Unified measurement

    Best for global retail, DTC and travel brands that want unified measurement with agent execution.

    Causal MMM, geo-based incrementality testing and attribution in one product, with AI agents that can push changes to the ad platforms within guardrails. Lifesight does not state its inference method publicly. Pricing on request.

    MMM plus experiments · Agentic · Global Odins vs Lifesight
  3. Recast

    Advanced specialist

    Best for large, mostly US advertisers with analytics teams and daily data.

    A Bayesian MMM with time-varying parameters, weekly automated refreshes and out-of-sample backtesting. Built for Fortune 500 and large DTC budgets, with enterprise pricing that is not published.

    Bayesian MMM · Managed platform · Weekly refresh Odins vs Recast
  4. Funnel Measure

    Data platform

    Best for teams that want measurement on top of the data hub they already run.

    Stockholm's marketing data hub, with MMM, attribution and incrementality layered on its own data foundation and updated daily. The three methods cross-check each other instead of sitting in one model. Deepest across digital sources.

    Triangulated MMM · Product-led · Daily updates Odins vs Funnel
  5. Meta Robyn

    Open-source framework

    Best free way to get a first directional MMM inside a week.

    The package that made MMM feel free, and the most automated of the three. It is frequentist rather than Bayesian, returns a set of candidate models to choose between, and Meta has stopped active development. Fine for a first look. Think twice before betting the measurement stack on it.

    Frequentist framework · Self-hosted · Community-maintained Odins vs Robyn

INCRMNTAL facts come from incrmntal.com, read October 2026. Other provider facts come from each vendor's public documentation, read September 2026: lifesight.io, getrecast.com, funnel.io and facebookexperimental.github.io/Robyn. Odins is our platform.

At a glance

Which alternative for which need.

Start from the question: reading changes as they happen, or sizing the whole budget.

Best fit
Why
Total budget size and allocation, offline included
Best fitOdins
WhyOne Bayesian model per market with offline media and business drivers inside it, test results taken into the model
Geo testing with agent execution
Best fitLifesight
WhyCausal MMM, geo incrementality testing and attribution in one product, with agents that can act in the ad platforms
Large advertisers with daily data and analytics teams
Best fitRecast
WhyTime-varying Bayesian MMM with weekly refreshes and out-of-sample backtesting
Measurement on top of a data hub
Best fitFunnel Measure
WhyMMM, attribution and incrementality on the Funnel data foundation, updated daily
A free first directional MMM
Best fitMeta Robyn
WhyOpen source and highly automated, frequentist, and no longer actively developed by Meta

Sources as listed above. Where a vendor does not state something publicly, we left it out.

When to look elsewhere

Four reasons to look for an INCRMNTAL alternative.

INCRMNTAL makes incrementality practical for teams that change their marketing often. These are the situations where another route fits better.

  • The first question is total budget size, before any single change
  • TV, radio, OOH or print carry real budget and need to sit inside the model
  • You want forecasts at budget levels you have not tried yet, checked against actuals afterwards
  • You want a person to review each recommendation before it reaches you
Why Odins

One model for the budget, your tests included.

Odins is MMM, run for you: test results and platform data feed one model of the whole budget, with scenarios and forecasts open to your team any time.

  • One Bayesian model per market, with TV, radio, OOH and print next to digital, pricing and promotions
  • Priors set in 2 to 3 working sessions, from your spend history, digital saturation signals and structured interviews
  • Results from lift and geo tests you have run are taken into the model, and a structured test is proposed when a channel is uncertain
  • Data flows in daily and the model is retrained monthly, with forecasts stored before actuals arrive and checked at each retrain
  • Scenarios and forecasts you run yourself any time, in the platform or from Claude via the Odins MCP

Channel contribution, 80% ranges

from the posterior
Search 14 to 16% optimize
Social 9 to 13% optimize
Display 2 to 9% test first

A tight range is a decision. A wide range is a test plan, with cost boundaries.

FAQ

Frequently asked questions.

What is the best alternative to INCRMNTAL?

It depends on the question. For total budget size and allocation with offline media inside the model, Odins is the alternative we would point to, and yes, it is ours. For geo testing with agent execution, Lifesight. For large advertisers with daily data, Recast. For measurement on top of a data hub, Funnel Measure. For a free first directional MMM, Meta Robyn.

How is Odins different from INCRMNTAL?

INCRMNTAL measures the incremental effect of the changes you make, close to real time and without holdouts. Odins is a Bayesian marketing mix model for the standing budget question, with offline media and business drivers inside it, priors set with your team, data flowing in daily, a monthly retrain checked against stored forecasts and a person behind every recommendation. The full comparison, with sources, is on Odins vs INCRMNTAL.

Is incrementality measurement the same as marketing mix modeling?

They overlap. Incrementality measurement asks what a specific change or channel added. A marketing mix model estimates how every channel, offline media and business drivers included, contributes over time, with saturation curves that show where the next euro still pays. Odins uses both: test results go into the model, and the model sizes and splits the budget.

Is there a free alternative to INCRMNTAL?

Meta Robyn is free and the most automated of the open frameworks, though Meta has stopped active development. Google Meridian and PyMC-Marketing are free Bayesian options. Your own team builds and maintains the model, so the cost is staff and time.

What does an INCRMNTAL alternative cost?

INCRMNTAL does not publish prices; its subscription is not tied to ad spend. Lifesight and Recast do not publish pricing either, and Robyn is free to license and paid for in staff and time. Odins is a subscription priced for the budget it optimizes, for companies with a marketing budget from EUR 1M to several hundred million a year, with the team included and no data science hires needed.

Talk to our team

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