Northbeam is a marketing intelligence and attribution platform designed for performance-driven brands spending heavily across paid social, search, and influencer channels. It provides cross-channel attribution and media mix modelling that helps marketing teams make budget decisions based on actual revenue impact rather than platform-reported metrics.
Product Overview
Northbeam's ML-powered attribution model ingests data from ad platforms, website analytics, and e-commerce systems to produce a unified view of how each channel, campaign, and creative drives revenue. Its predictive spend optimisation recommends budget reallocation across channels to maximise ROAS. The Creative Insights module analyses ad creative performance at the asset level — identifying which images, videos, and copy generate the most revenue per dollar spent.
Key Features
- ML Attribution Model: Machine learning attribution that weighs each touchpoint by its actual contribution to conversion — not arbitrary rule-based models.
- Creative Intelligence: Revenue attribution at the ad creative level — identify which specific images, videos, and copy drive the most efficient revenue.
- Predictive Spend Optimisation: AI recommendations for budget reallocation across channels to maximise projected ROAS given current performance data.
- Blended Metrics Dashboard: Unified ROAS, CPA, and revenue metrics across all channels in a single dashboard — no manual aggregation.
- Cohort & LTV Analysis: Track customer cohorts by acquisition channel and understand LTV impact of each spend decision.
Best For
Performance marketing teams at DTC and e-commerce brands spending $1M+ on paid social and search who need creative-level attribution and budget optimisation recommendations.
Pricing
Custom pricing based on ad spend. Contact sales. Targets mid-to-large DTC brands.
Key Integrations
Shopify, WooCommerce, Meta Ads, Google Ads, TikTok Ads, Snapchat Ads, Pinterest, Klaviyo, Triple Whale
Pros
- Creative-level attribution is a genuine differentiator for performance teams
- ML attribution is more accurate than rule-based models
- Predictive spend optimisation adds actionable budget guidance
- Strong for social-heavy brands
Cons
- Expensive — better suited to larger DTC brands
- Less suited for B2B or subscription businesses
- Setup complexity with multiple ad accounts
RevOps Jobs-to-Be-Done
- Post-iOS Privacy Attribution for E-Commerce — Use Northbeam's ML attribution to accurately measure digital ad performance after iOS 14+ signal loss degraded platform-reported ROAS. KPI: Recover 30–50% of previously invisible conversion attribution and reallocate budget to true top performers
- Multi-Touch Attribution Across Ad Channels — Model the contribution of each ad touchpoint across Facebook, Google, TikTok, and influencer using a unified ML attribution model. KPI: Make media budget decisions based on incrementality data rather than platform self-reported ROAS
- New Customer Revenue Attribution — Separate new customer acquisition from repeat purchase revenue attribution to understand true CAC by channel. KPI: Optimize CAC by identifying which channels drive net-new customers vs retargeting existing buyers
How It Fits Your Stack
Primary system of record: Shopify and other e-commerce platforms
Key integrations: Shopify, WooCommerce, Facebook Ads, Google Ads, TikTok Ads, Pinterest, Klaviyo, Triple Whale
Data flows: First-party pixel captures all ad clicks and site events; revenue data from e-commerce platform feeds ML attribution model; daily budget recommendations delivered to media buyers
Security & Compliance
- SSO / SAML: Google SSO
- RBAC / permissions: Yes
- Audit logs: Yes
- Certifications: SOC 2 Type II
- Data residency: US
Implementation & Ownership
- Time to first value: 1–2 weeks for initial data; ML models mature in 30 days
- Implementation complexity: Low — pixel setup and platform connections; ML models self-train
- Typical owners: CMO, Growth Director, Media Buyer
Targets mid-to-large DTC brands with $1M+ annual ad spend; pricing scales with spend
Proof & Buyer Signals
Ratings: G2: 4.5/5 (60+ reviews)
What buyers praise:
- Best ML attribution for DTC brands
- Post-iOS tracking recovery is real
- Channel-level budget recommendations
Common complaints:
- Premium pricing vs lighter tools
- ML model needs 30-day ramp period
- Less suited for B2B/SaaS
Often Compared With
- Triple Whale — Both target Shopify DTC brands; Triple Whale has stronger analytics dashboard and creative reporting; Northbeam leads on ML attribution model accuracy
- Rockerbox — Rockerbox targets enterprise marketing teams; Northbeam is more DTC/e-commerce focused with deeper ML attribution models
- Windsor.ai — Windsor.ai aggregates ad platform data for reporting; Northbeam applies ML attribution modeling on top of first-party pixel data
