AI-native B2B revenue analytics unifying marketing, product, and sales touches into attribution.
HockeyStack is a B2B revenue analytics and attribution platform. It stitches together website behavior, ad exposure, product usage, and CRM activity into account-level journeys, then attributes pipeline and revenue across those touches so marketing leaders can defend and reallocate budget. Demand-gen and marketing ops teams at B2B SaaS companies are the core users, typically asking which channels and campaigns actually produce pipeline rather than clicks.
Which of the capability map's modules HockeyStack covers — each links to the module's own page, with every tool that supports it.
| Module | Phase | Depth | Note |
|---|---|---|---|
| Create Demand | |||
| Multi-Touch Attribution | Demand & Campaign Ops | Core | Account-level multi-touch attribution across marketing, product, and sales activity. |
| Paid Media ROI Tracking | Demand & Campaign Ops | Core | Channel and campaign ROI against pipeline and revenue, not click conversions. |
| Web & Product Analytics | Demand & Campaign Ops | Supported | Site and product behavior captured as journey inputs rather than a standalone analytics suite. |
Two things stand out against attribution incumbents: a no-SQL, dashboard-first experience aimed at marketers rather than data teams, and an AI layer that answers journey questions in natural language. Folding product analytics signals into the same account journey — relevant for PLG-flavored B2B — also distinguishes it from attribution tools that stop at marketing touchpoints.
1 of the companies the Blueprint tracks — from public job posts, engineering blogs, and filings. Every claim links to its evidence on the company page.
Both do B2B revenue attribution; the practical differences are posture and inputs. Dreamdata leans on a transparent warehouse-based data model, while HockeyStack pitches a faster, marketer-operated experience with AI-assisted analysis and product-usage signals in the journey. Teams with strong data engineering often prefer transparency; lean marketing teams prefer speed.
No model observes causation — every attribution tool allocates credit by rule or model, and dark-funnel touches stay invisible. Treat the outputs as directional evidence for budget shifts, validated with holdout tests or incrementality experiments before making large reallocations.
By overlap on the capability map — computed, not curated.