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Northbeam vs Triple Whale

Northbeam is warehouse-native attribution built for analysts; Triple Whale is an all-in-one operator dashboard with attribution as one module among several.

Side by side

Northbeam Triple Whale
Vendor Northbeam Triple Whale
Pricing model Quote only Subscription
Free tier No No
Deployment Cloud Cloud
Open source No No
Best for DTC and e-commerce brands wanting warehouse-native multi-touch attribution tied to Shopify order data. Shopify-based DTC brands wanting one dashboard for profitability, attribution and ad performance.
Pricing

Custom quotes based on monthly ad spend or order volume; pricing is not published.

Pricing has not been verified yet — see the vendor's site.

Tiered monthly plans scaled to order volume, with a free trial; higher tiers add attribution and MMM modules.

Pricing has not been verified yet — see the vendor's site.

Features
  • Warehouse-native multi-touch attribution
  • Creative-level and campaign-level performance reporting
  • New-versus-returning customer breakdowns
  • Post-purchase survey attribution
  • Cross-channel spend and ROAS dashboards
  • Shopify-native order and revenue matching
  • Blended ROAS and contribution-margin dashboards
  • Shopify order and cost-of-goods integration
  • Post-purchase survey and pixel-based attribution
  • Creative-level ad performance reporting
  • AI assistant for querying store and ad data
  • Media mix modeling module on higher tiers

Verdict

Northbeam and Triple Whale are the two names that come up most often when a Shopify DTC brand is shopping for attribution, and both explicitly list each other as the direct competitor. Both pull order, ad-spend, and website data into channel-level performance reporting and both report new-versus-returning customer splits. The difference is what each one is built to be beyond attribution. Northbeam is warehouse-native and positions itself as less reliant on its own tracking pixel than some rivals — its focus stays on attribution modeling, creative-level reporting, and post-purchase survey data, aimed at teams that want a precise, warehouse-grounded measurement layer. Triple Whale is broader by design: a single operator dashboard combining blended ROAS, contribution-margin and profitability reporting, creative-level ad performance, an AI assistant for querying store and ad data, and — on higher tiers — its own media mix modeling module, with attribution as one part of a larger daily-operations tool rather than the whole product.

Choose Northbeam if

  • Attribution accuracy and warehouse-native measurement are the primary requirement, more than an all-in-one dashboard.
  • You want to minimize reliance on a proprietary tracking pixel as browser and platform privacy restrictions tighten.
  • Creative-level and post-purchase-survey attribution detail matters more to your team than profitability reporting in the same tool.

Choose Triple Whale if

  • You want one dashboard covering profitability, attribution, and ad performance rather than assembling several tools.
  • An AI assistant for ad-hoc questions across store and ad data is a genuine workflow fit, not a nice-to-have.
  • You're likely to want a bundled media mix modeling module as you scale, rather than adding a separate MMM vendor later.

What they share

Both are built around Shopify as the core data source, both integrate the same major ad platforms (Google, Meta, TikTok), and both are used almost exclusively by DTC and e-commerce brands rather than B2B or offline businesses. Both blend pixel-based and non-pixel signals to varying degrees, reflecting the same industry pressure: pure client-side pixel tracking has gotten less reliable for everyone in this category.

The honest caveat

"Blended ROAS" and attribution figures from Northbeam and Triple Whale are calculated with each vendor's own model and will not match each other, or match either platform's own ad-reported numbers, exactly — that is expected, not a bug in either tool. Pick the one whose methodology you trust enough to make budget decisions on, and hold it constant over time rather than switching between the two and comparing absolute numbers.

Last reviewed September 22, 2026

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