Rockerbox is a marketing measurement and attribution platform purpose-built for direct-to-consumer and e-commerce brands. It centralises marketing data from every paid and organic channel, applies multiple attribution models, and provides a single source of truth for marketing performance — replacing the patchwork of ad platform reports that consistently inflate individual channel ROAS.
Product Overview
Rockerbox solves the fundamental problem of cross-channel measurement: every ad platform claims credit for the same conversion, making it impossible to know which channels actually drove the sale. Rockerbox de-duplicates conversions, applies neutral multi-touch attribution across all channels, and provides a true, unbiased view of marketing performance. Its Incrementality Testing module measures the true causal impact of specific channels — going beyond correlation to prove which spend actually drives incremental revenue.
Key Features
- Unified Marketing Data: Aggregate spend, impression, click, and conversion data from 100+ ad platforms and channels in one dashboard.
- De-duplicated Attribution: Remove the double-counting that inflates ROAS in ad platform reports — see true cross-channel credit allocation.
- Multi-Touch Models: Compare first-touch, last-touch, linear, time-decay, and data-driven models across all channels simultaneously.
- Incrementality Testing: Run geo holdout and A/B tests to measure the true causal lift of any channel or campaign.
- Media Mix Modelling: Statistical model that estimates the impact of each channel on revenue — without relying on cookies or user-level tracking.
Best For
DTC and e-commerce brands spending $500K+ annually on paid media who need an unbiased, cross-channel view of marketing performance beyond what individual ad platforms report.
Pricing
Custom pricing based on ad spend and data volume. Contact sales.
Key Integrations
Shopify, Google Ads, Meta Ads, TikTok Ads, Klaviyo, Google Analytics, Snowflake, BigQuery
Pros
- Purpose-built for DTC — Shopify-native and e-commerce focused
- De-duplication solves the double-counting problem definitively
- Incrementality testing provides causal proof of channel value
- Strong media mix modelling for cookieless attribution
Cons
- Less suited for B2B SaaS with long sales cycles
- Expensive for brands below $500K media spend threshold
- Incrementality tests require time and traffic volume to be statistically valid
RevOps Jobs-to-Be-Done
- Centralized Marketing Data and Attribution — Aggregate all marketing touchpoint data into a unified platform and apply multi-touch attribution models across the full funnel. KPI: Replace 5–8 siloed platform reports with one source of truth for marketing performance and attribution
- Privacy-Resilient Attribution Strategy — Use Rockerbox's first-party tracking and modeled attribution to maintain accurate measurement despite iOS and cookie deprecation. KPI: Maintain attribution coverage above 80% as third-party signal loss continues
- Customer Journey Analysis — Analyze the typical touchpoint paths customers take before converting to optimize channel sequencing and budget allocation. KPI: Identify 2–3 high-impact sequence changes that improve conversion rate without increasing spend
How It Fits Your Stack
Primary system of record: Salesforce, HubSpot, and e-commerce platforms
Key integrations: Salesforce, HubSpot, Shopify, Facebook Ads, Google Ads, Snowflake, BigQuery, Looker
Data flows: First-party pixel and platform API data flows into Rockerbox; attribution models applied; results exported to data warehouse and BI tools; spend data from ad platforms
Security & Compliance
- SSO / SAML: SAML 2.0
- RBAC / permissions: Yes
- Audit logs: Yes
- Certifications: SOC 2 Type II
- Data residency: US
Implementation & Ownership
- Time to first value: 2–4 weeks
- Implementation complexity: Medium — pixel, platform connections, and data warehouse setup
- Typical owners: VP Marketing, Marketing Analytics Lead, RevOps
Strong fit for mid-market to enterprise brands with $500K+ ad spend across multiple digital channels
Proof & Buyer Signals
Ratings: G2: 4.5/5 (80+ reviews)
What buyers praise:
- Clean centralized marketing data
- Multi-touch models are flexible
- Good data warehouse integration
Common complaints:
- Setup requires technical resources
- Less ML sophistication vs Northbeam for DTC
Often Compared With
- Northbeam — Northbeam uses more advanced ML attribution for DTC; Rockerbox provides more flexible channel aggregation for enterprise marketing teams
- Triple Whale — Triple Whale is DTC/Shopify-native; Rockerbox serves broader enterprise use cases across B2B and B2C channels
- Windsor.ai — Windsor.ai focuses on connector/aggregator for ad reporting; Rockerbox adds attribution modeling and journey analysis on top of aggregated data
