Bayesian MMM Comparison

Pangolin vs Forvio

Forvio and Pangolin both aim to make Marketing Mix Modelling accessible without a data science team, but they package that accessibility differently. Forvio is a self-serve toolkit combining MMM, MTA and GeoLift testing for teams of any size to run themselves. Pangolin is a managed, automated system purpose-built for DTC brands, optimised for contribution profit.

FORVIO: CONFIGURABLE TOOLKIT Marketers own the setup, running, and interpretation of models. High control over inputs, but demands operational bandwidth and optimization logic design. User-Configured

➔vs

PANGOLIN: MANAGED OPTIMISER No model configuration required. Connected datasets are automatically structured, calculated, and modeled to deliver clear contribution-profit-optimised budget advice. Zero-Overhead MMM

See how Pangolin compares using your own data

At a Glance

Who's each platform for?

Pangolin BEST SUITED FOR Growth-stage DTC and ecommerce brands that want a managed Bayesian MMM system generating contribution-profit-optimised budget recommendations automatically.

Forvio BEST SUITED FOR Marketers, consultants and agencies of any company size who want a self-serve toolkit combining MMM, multi-touch attribution and GeoLift testing, and are comfortable setting up and interpreting the models themselves.

Head to Head

Direct Capability Mapping

Capability	Pangolin	Forvio
1. Measurement Foundations
Marketing Mix Modelling	Core, Bayesian, managed	Core, built on frameworks including Meta's Robyn and Google's Meridian
Multi-touch attribution	Not the primary method	Included alongside MMM
Incrementality testing	Built into the contribution model	GeoLift experiments available
Model ownership	Modelled and maintained by Pangolin	Self-serve setup by the user
2. Action & Optimisation
Budget optimisation	AI-generated recommendations, core feature	Scenario Planner for 7/30/90-day budget allocation
Autonomous execution	Yes, core to the product (human-approved)	Not a core feature - recommendations are actioned manually
Contribution profit focus	Core feature	Not a primary focus (ROAS/CPA-oriented)
3. Product Experience & Audience Fit
Target user	DTC and ecommerce marketing leaders	Marketers, consultants and agencies across sizes and sectors
Setup approach	Managed, automated	Self-serve, workspace-based configuration
Agency support	Not a current focus	Dedicated workspaces for agencies and freelancers
Vertical focus	DTC and ecommerce specifically	Broad, cross-sector

Foundational Beliefs

Two contrasting approaches to measurement

APPROACH A Forvio: Self-serve measurement toolkit Combine MMM, MTA and GeoLift testing in one configurable platform.Let users run scenario planning across different time horizons.Leave model setup, interpretation and execution to the team operating it.

APPROACH B Pangolin: Managed, decision-first MMM Model incremental contribution and contribution profit automatically from connected data.Generate a specific budget recommendation without requiring setup or configuration.Route the recommendation for human approval before execution.

The Pangolin Advantage

Where Pangolin is different

Managed, not self-configured Forvio provides the toolkit; Pangolin builds and maintains the model for you, with no setup step between connecting data and receiving a recommendation.

Optimised for profit specifically Pangolin targets contribution profit directly, while Forvio's optimisation centres on ROAS and CPA-style metrics across its scenario planning.

From recommendation to approved action Pangolin's recommendations move through human approval as a core workflow, rather than producing scenarios the team must still build into a media plan.

Purpose-built for DTC and ecommerce Forvio is designed to serve teams of any size and sector; Pangolin's product is built specifically around the data and channel mix of DTC and ecommerce brands.

Pangolin's Continuous Optimization

From data to a better budget decision

Data➔ Measurement➔ Insights➔ Recommendations➔ Better budget decisions

Live Bayesian MMM Output A live view of channel contribution profit and saturation, generated automatically with AI-written explanations.

Meta AdsModel refreshes continuously - scale marginScale

Google SearchMarginal return saturation detectedReduce

Action Recommendation · Target Focus: Contribution Profit · Workflow: One click to approve

Choose Pangolin if: ✓You want a managed system that generates the recommendation, not a toolkit you configure yourself ✓Contribution profit needs to drive the decision, not ROAS or CPA-based scenarios ✓You're a DTC or ecommerce brand and want a platform built specifically around that channel mix ✓You'd rather approve a specific recommendation than build scenarios into a media plan yourself

Consider Forvio if: ○You want MMM, MTA and GeoLift testing combined in one self-serve platform ○You're a consultant or agency managing measurement across multiple clients ○You want visibility into the underlying modelling framework ○Your team is comfortable setting up and interpreting the models directly

Pangolin vs Forvio FAQ

Pangolin vs Forvio Comparison FAQ

How does Pangolin compare with Forvio?

Forvio is a self-serve toolkit combining MMM, multi-touch attribution and GeoLift testing for teams to configure and run themselves. Pangolin is a managed platform that models your data and generates an AI-driven, contribution-profit-optimised budget recommendation automatically.

Does Pangolin include multi-touch attribution like Forvio?

No. Pangolin's core method is Bayesian MMM. Forvio combines MMM with MTA and GeoLift testing as complementary methods within one toolkit.

Which platform is better for DTC brands?

DTC and ecommerce brands wanting a managed, profit-optimised recommendation without setting up their own toolkit tend to fit Pangolin better. Brands, consultants or agencies wanting a configurable, multi-method toolkit across sectors may prefer Forvio.

Is Forvio's use of open frameworks like Robyn and Meridian an advantage?

It offers transparency into the underlying modelling approach for technically-minded users. Pangolin trades that visibility for a managed model and an automatically generated recommendation, suited to teams who'd rather not configure the modelling process themselves.

Does Pangolin support agencies managing multiple clients, like Forvio?

Not as a current focus. Forvio's workspace structure is built for agencies and freelancers; Pangolin is built for a single growth-stage DTC or ecommerce brand.

Skip the toolkit setup. Get straight to the budget decision.

See what an automated, profit-optimised recommendation looks like for your own brand.

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