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
