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Odins vs Funnel
Funnel already sits in many Nordic stacks as the data hub, and Funnel Measure adds MMM, attribution and incrementality on top of it. The honest comparison: a data platform growing into measurement, against a measurement platform that brings its own data layer.
Reviewed September 2026 · sources cited on this page
Odins
Managed marketing investment platform
Funnel
Marketing data hub with Funnel Measure
At a glance
Side by side.
The short version of the whole page. Details and sources below.
Funnel facts: funnel.io/measure and related product pages, read September 2026. Funnel does not state its inference method publicly.
Credit first: Funnel earned its place in the stack.
Stockholm-built and everywhere in the Nordics for a reason. As a data foundation, Funnel is excellent, and Measure is a serious step up the stack.
- The best-known marketing data hub in the Nordics, with 500 plus connectors that just work
- Data collected, cleaned and normalized continuously, exportable to wherever you work
- Measure ships MMM, MTA and incrementality in one product on that foundation
- Real distribution: this is the stack we meet most often in first meetings
A data hub is not a decision layer.
Funnel's gravity is the pipeline: collect everything, keep it clean, layer measurement on top. Ours is the decision: one Bayesian model built for your market, verified monthly, with a recommendation attached. If you already run Funnel, the two coexist well.
- Three methods reconciled in a dashboard still leave you choosing what to trust; priors fold the evidence into one model with one answer
- Offline media and business drivers are modeled, where a hub can only store them
- Budget size and allocation arrive as a reviewed recommendation, not a self-serve chart
- Keep Funnel if you have it: we ingest structured data from the hub or connect to sources directly
Channel contribution, 80% ranges
from the posteriorA tight range is a decision. A wide range is a test plan, with cost boundaries.
The choice
Who should choose which.
This is the least either-or comparison on our site. Start from what your stack is missing.
Choose Funnel if
- You want one vendor for data infrastructure and directional measurement on top
- Your mix is digital-heavy and campaign-level daily numbers drive your decisions
- Your team prefers to self-serve analytics on a clean data foundation
Choose Odins if
- Real budget decisions ride on the output, so the model has to be verified
- Offline media and business drivers need to be in the model, not beside it
- You want the modeling owned by a team you can call, with a monthly recommendation
The honest overlap
Plenty of future Odins customers should keep Funnel as the data layer and let us do the modeling on top. That pairing works well, and we will tell you in the first call if it describes you.
Frequently asked questions.
We already use Funnel. Do we have to replace it?
No. We can ingest structured marketing data from Funnel or connect to the sources directly, whichever is cleaner for you. A well-run data hub usually shortens onboarding, and you keep the reporting your team already relies on.
What is the difference between triangulation and priors?
Triangulation runs MMM, attribution and experiments as parallel analyses and reconciles the outputs afterwards, which leaves someone deciding what to trust. In a Bayesian model the same evidence enters as priors, so the model returns one answer with that evidence already inside it. Calibrating MMM with experiments via priors is mainstream best practice; Google's Meridian documentation describes the same approach.
Funnel Measure updates daily. Why is Odins monthly?
Because budget decisions are monthly and quarterly. Daily updates suit pacing and operational questions, and Funnel is good at those. A model that moves annual money should be retrained on complete data, reviewed by a person, and verified against actuals. That is a monthly rhythm.
Is Funnel's MMM Bayesian?
Their public material describes triangulation and AI automation rather than the inference method, so we will not put a label on it. It is a fair question to ask any vendor, us included. Our answer: Bayesian end to end, with priors set together with you.
We have offline channels Funnel's connectors do not cover. What then?
Offline spend usually arrives as reports and invoices: TV spot logs, radio schedules, OOH bookings. Our team loads and reconciles those as part of the service, which is exactly the data a digital-first hub is thin on, and often the spend where the biggest allocation wins hide.
Marketing spend, modeled like an investment.
A 30-minute walkthrough of the model, the priors and the verification, on your channels.
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