Attribution & marketing mix modeling · Rockerbox
Rockerbox
Marketing measurement platform combining multi-touch attribution with media mix modeling on the advertiser's own data.
Rockerbox reads marketing and conversion data from the advertiser's own warehouse or ad-platform APIs rather than relying on its own tracking pixel, then produces both multi-touch attribution (which touchpoints a converting customer passed through) and media mix modeling (aggregate spend-to-outcome relationships across channels over time) from the same underlying data. Running both methods side by side is the point: multi-touch attribution explains individual customer paths but struggles with platforms that block tracking, while MMM is privacy-resilient but coarser, and Rockerbox lets advertisers reconcile the two rather than picking one. It is used mainly by mid-market and enterprise advertisers with in-house analytics capacity to act on the output, not as a plug-and-play dashboard for small teams.
At a glance
| Vendor | Rockerbox |
|---|---|
| Pricing model | Quote only |
| Free tier | No |
| Deployment | Cloud |
| Open source | No |
| Best for | Mid-market and enterprise advertisers wanting multi-touch attribution and MMM reconciled from their own warehouse data. |
Pricing
Custom quotes scoped to ad spend and data sources; pricing is not published.
Pricing has not been verified yet — see the vendor's site.
Features
- Multi-touch attribution reading from the advertiser's own data, not a proprietary pixel
- Media mix modeling alongside multi-touch attribution
- Warehouse-native data ingestion
- Cross-channel budget allocation recommendations
- Incrementality test design support
- Custom attribution model configuration
Integrations
Profile last reviewed September 21, 2026