Sellforte Alternative

Looking for a Sellforte alternative? Consider what scale of operation you actually need it for

Sellforte is built for enterprise and mid-market ecommerce, DTC and retail brands, often operating across multiple markets, with campaign and ad-set-level optimisation calibrated by experiments. Brands looking for a Sellforte alternative are often single-market, growth-stage DTC brands who want the same automated, AI-driven MMM approach without that added scale and configuration.

HIGH CONFIGURATION OVERHEAD Requires constant multi-market tracking, deep campaign-level parameters, and ongoing developer resource to maintain. Multi-Market SetupAd-Set Calibration

➔AUTOMATED

AUTONOMOUS BAYESIAN MMM Pangolin automates the data science pipelines, outputting continuous, profit-optimized recommendations without complex structures. Continuous Refresh

See how Pangolin compares using your own data

The Drivers

Why businesses look for a Sellforte alternative

Teams typically start looking for a Sellforte alternative for one of a few reasons:

01 Enterprise-grade complexity isn't needed Sellforte's campaign and ad-set-level modelling, multi-market support and experiment calibration are built for large, often multi-market operations; a single-market DTC brand may not need that depth.

02 Optimisation target is ROAS-based Sellforte optimises for marginal incremental ROAS (miROAS), a revenue-based metric; brands wanting a contribution-profit objective need a different platform or a secondary configuration.

03 Pricing scales with media spend As spend and complexity grow, so does the cost, which can outpace the budget of an earlier-stage brand looking for straightforward growth insights.

04 Target segment is above 'SMB MMM' Sellforte targets enterprise and mid-market retailers operating across multiple markets, so a single-market, growth-stage DTC brand sits below the segment the platform is built and priced for.

Landscape Overview

Different types of Sellforte alternative

TYPE 1 Attribution-first platforms Platforms like Triple Whale and Northbeam, centred on multi-touch attribution, with MMM as a secondary layer in Northbeam's case.

TYPE 2 Enterprise measurement Platforms like Rockerbox, combining MTA, MMM and incrementality testing for complex, often omnichannel media mixes.

TYPE 3 Incrementality-first Platforms like Measured, proving incremental lift through controlled, geo-based experiments.

TYPE 4 Self-serve MMM toolkits Platforms like Cassandra and Forvio, giving teams a no-code or configurable toolkit to build and run their own models.

TYPE 5 Decision-first MMM Pangolin's category: Bayesian Marketing Mix Modelling optimised for contribution profit, generating specific AI-recommended budget decisions directly.

Pangolin Position

Where Pangolin fits

Pangolin is an automated marketing measurement platform built around Bayesian Marketing Mix Modelling. It models channel contribution, saturation and contribution profit continuously from your existing marketing and business data, then generates a specific AI-recommended budget reallocation that a human approves before it goes live. It's built for growth-stage DTC and ecommerce brands operating primarily in one market, without the campaign/ad-set-level configuration or multi-market complexity that enterprise-grade platforms are designed around.

Direct Comparison

How Pangolin compares to Sellforte

Capability	Pangolin	Sellforte
Marketing Mix Modelling	Core, Bayesian	Core, Bayesian, calibrated with geo and conversion lift tests
Granularity	Channel-level contribution and saturation	Campaign and ad-set level (miROAS)
Multi-market modelling	Not a current focus	Core strength
Optimisation target	Contribution profit	Marginal incremental ROAS (miROAS)
Autonomous execution	Yes, human-approved	Yes, via Media Buyer Agent with configurable guardrails
Target segment	Growth-stage, single-market DTC	Enterprise and mid-market, multi-market ecommerce, DTC and retail

The Core Difference

Pangolin vs Sellforte

Sellforte's depth is real: campaign and ad-set-level miROAS, calibration against geo and conversion lift experiments, and multi-market modelling for brands operating at genuine scale, backed by enterprise customers like Lidl, C&A and Tchibo. Pangolin takes a narrower, more accessible route built specifically for growth-stage, single-market DTC brands — channel-level Bayesian MMM optimised for contribution profit rather than incremental ROAS, without the configuration overhead that campaign-level, multi-market modelling requires.

When Pangolin is the right choice ✓You're a growth-stage DTC or ecommerce brand operating primarily in one market ✓Contribution profit, not incremental ROAS, is the number that should drive your budget ✓You want a focused platform without campaign/ad-set-level configuration overhead ✓Your media mix is primarily digital, without a significant offline component

When another solution may be better ○If you operate across multiple markets or a genuinely omnichannel mix including offline media ○If campaign and ad-set-level bid optimisation is a requirement ○If you want your MMM calibrated directly against geo and conversion lift experiments ○If you're operating at enterprise scale already, requiring robust global custom tools

Platform Interface

From data to a better budget decision

Data➔ Measurement➔ Insights➔ Recommendations➔ Better budget decisions

Live Bayesian MMM Output A live view of channel contribution, saturation and contribution profit, with AI-generated budget recommendations ready for approval.

Meta AdsActive saturation limitsStable

Google SearchOver-claiming creditReduce

TikTok VideoHigh marginal profit curveScale

Live Action Recommendations · No dedicated analyst required · Optimised for contribution profit · One click to approve

Common Inquiries

Frequently Asked Questions

Why would a brand look for a Sellforte alternative?

Common reasons include not needing Sellforte's multi-market or campaign/ad-set-level complexity, wanting a contribution-profit optimisation target rather than incremental ROAS, and pricing that scales with media spend at a rate that suits larger operations more than growth-stage ones.

Is Pangolin a direct replacement for Sellforte?

For growth-stage, single-market DTC brands, largely yes. For enterprise or multi-market retailers needing campaign-level bid optimisation and experiment-calibrated modelling, Sellforte's depth isn't fully replicated by Pangolin.

What type of alternative should I choose?

It depends on scale and optimisation target. Single-market, growth-stage brands wanting profit-focused automation tend to fit Pangolin; multi-market or enterprise brands needing campaign-level granularity may still need Sellforte.

Does Pangolin offer the same campaign-level granularity as Sellforte?

Pangolin's current focus is channel-level contribution and saturation modelling, not campaign or ad-set-level bid recommendations.

How does pricing compare?

Sellforte's pricing scales with media spend under management across tiered plans. Pangolin is positioned for growth-stage budgets specifically without complex contract scaling.

A Sellforte alternative built for growth-stage, single-market DTC brands

See what a focused, profit-first Bayesian MMM approach shows for your own channel mix.

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