Attribution ties ad spend to real revenue with user-level, multi-touch attribution, Media Mix Modeling, and incrementality testing for B2B, ecommerce, and…
Category
Marketing
Pricing
Paid SaaS with a 14-day free trial on the Pro ($399/mo, up to 10,000 tracked visitors) and Shopify ($199/mo) plans; a Custom/enterprise plan is priced individually and adds multi-project support, data-warehouse tooling, and account-based attribution., from $399/mo
Verified
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Last updated
August 6, 2026
SaaSPaidAPIShopify Integration
Attribution is a marketing analytics platform built to solve cross-channel double-counting, where multiple ad platforms each claim credit for the same conversion and inflate reported revenue beyond actual results. It ties real ad spend to individual customer journeys with user-level cost tracking, and supports five configurable attribution models (first touch, last touch, linear, time decay, and position-based) so teams can compare ROAS by model. Beyond attribution, the platform offers Media Mix Modeling for budget optimization and revenue forecasting, plus incrementality testing via geo holdout and synthetic control methods. Users can drill into the underlying transactions behind any number for full auditability, and export raw data to warehouses like Snowflake, BigQuery, and Redshift. Attribution also ships a native Model Context Protocol (MCP) server that lets Claude and other AI assistants query attribution data through natural language. It targets B2B SaaS companies, B2C/ecommerce brands (with dedicated Shopify support), marketplaces, marketing agencies (via a partner program), and enterprise teams that need CFO-defensible reporting.
Key Features
Multi-touch attribution modeling — Five configurable models (first touch, last touch, linear, time decay, position-based) with ROAS comparison across each.
User-level cost tracking — Ties actual ad spend to individual customer journeys for de-duplicated, auditable revenue reporting.
Media Mix Modeling — Budget optimization and revenue forecasting across marketing channels.
Incrementality testing — Geo holdout and synthetic control methods to measure true causal lift from ad spend.
Data warehouse export — Raw data export to Snowflake, BigQuery, Redshift, and other warehouses for custom analysis.
MCP server for AI assistants — A native Model Context Protocol server lets Claude and other AI assistants query attribution data through natural language.
Pros & Cons
Pros
Combines multi-touch attribution, Media Mix Modeling, and incrementality testing in one platform instead of three separate tools
User-level cost tracking and full transaction-level auditability let teams verify exactly how a reported number was calculated
Broad integration coverage across ad platforms, CRMs, ecommerce, and data warehouses (Snowflake, BigQuery, Redshift)
Dedicated Shopify and B2B (CRM lifecycle/deal-stage) plans tailor the product to two very different buyer types
Cons
Entry-level Pro plan starts at $399/mo, a significant commitment compared to lighter-weight analytics tools
Overage fees apply once a plan's monthly tracked-visitor limit is exceeded
Public pricing page does not disclose exact enterprise/Custom plan pricing, so budgeting requires a sales conversation