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Research Comparison

Updated

Markdown

Summary

AI-powered B2B revenue data intelligence platform that unifies marketing and sales data to provide holistic buyer journeys, multi-touch attribution, and actionable insights.

Funding

50

Founded

2021

Team

60

hockeystack.com

Critical Notes

- Event-based data architecture (Atlas) replaces legacy systems-of-record; cookieless tracking captures dark funnel - $50M raised April 2026 to launch AI Revenue Agents platform (Odin, Nova) compiling natural language into deterministic workflows - Processes 60+ TB of revenue data monthly - Deep LinkedIn integration tracks ad impressions and engagements at account level - 8-figure ARR, expanding to large enterprise

Key Features

- Holistic Buyer Journeys - Multi-Touch Attribution - Lift and Incrementality Reporting - Custom Reports and Dashboards - Data Syncing with Source Systems - Forward-Looking Insights via AI Agents - Identity Resolution and Data Categorization

Details

Fully in-person San Francisco team of about 60, growing fast in go-to-market, sales, engineering. $50M round April 2026 after $20M Series A (Bessemer) in late 2025 and $2.7M Seed. 300+ customers, 8-figure ARR. ~80K monthly visits, ~25K social (co-founder Emir Atli 22K+ LinkedIn followers). Sales-led: demo-gated, outbound SDR team, enterprise CTAs. Not product-led: no self-serve or free trial; live preview and template library only. Proprietary closed-source; Atlas and AI agents commercial. Industry: B2B SaaS (revenue operations, attribution, sales intelligence).

Signalscompared to Common Room

1st Party

  • Bi-directional CRM/MAP (Salesforce, HubSpot, Marketo, Pardot, Pipedrive); cookieless fingerprint web visitor tracking; product usage; instant historical CRM backfill
  • Chat/support signals (Intercom, Qualified); customer success signals (Gainsight, Vitally); sales engagement ingestion (Outreach, Salesloft, Apollo, Groove, Nooks, Gong Engage, Smartlead); Zoom Engage/Dialer

2nd Party

  • LinkedIn Ads impression-level data; Google Ads; Meta; audience and offline conversion sync back to LinkedIn Campaign Manager
  • Open source (GitHub, Scarf); community (Discord, Slack, Discourse, Stack Overflow, Reddit, Khoros, InSided, Influitive); organic social (Twitter/X, YouTube, Medium, DEV, LinkedIn page activity); events (Bevy, Meetup, Gradual, Skilljar); Shopify

3rd Party

  • Waterfall enrichment (Clearbit, Apollo, ZoomInfo, Clay); intent (G2, Bombora, 6sense, Demandbase); funding and hiring signals
  • Native job change; native news/events; native technographics; TechTarget, Scarf, Toplyne; no owned data asset (licensed pass-through)

Custom

  • API, SDK, webhooks, Zapier, CSV, Snowflake/BigQuery warehouse ingestion into Atlas
  • none

1st party: bi-directional CRM/MAP (Salesforce, HubSpot, Marketo, Pardot, Pipedrive), cookieless fingerprint web and product usage, instant historical CRM backfill, unified timeline from anonymous touch to closed-won. 2nd party: LinkedIn Ads impression-level data, Google Ads, Meta; syncs offline conversions and high-intent audiences to LinkedIn Campaign Manager; updates dynamic target account lists. 3rd party: waterfall enrichment (Clearbit, 6sense, Demandbase, Apollo, ZoomInfo, Clay); intent from G2 and Bombora; feeds AI account scoring. Custom: API, SDKs, webhooks, Zapier, CSV, Snowflake/BigQuery into Atlas.

Identitycompared to Common Room

Enrichment

  • Contact Enrichment Node in workflows; verified email retrieval; licensed third-party providers; reverse IP account enrichment
  • No proprietary contact database; no out-of-box waterfall; no premium phone tier; no AI quality control on enrichment

AI Powered

  • Odin/Nova natural-language queries over stitched profiles and journeys; predictive forecasting and journey analysis trained on resolved data; prompts compile to deterministic workflows and reports
  • AI not used for identity resolution; no AI matching across handles/images/social; no auto-enrichment trigger for net-new contacts

Identity

  • Cookieless fingerprinting + reverse IP across devices/sessions; personal email to corporate domain stitching; hashed emails, CRM IDs, auth events; automated CRM normalization, dedupe, reconciliation
  • Account-centric not person-centric; no social handle/image/community matching; no human-review merge or manual merge; fingerprinting privacy risk (GDPR/CCPA); no profile persistence through job changes

Identity: cookieless fingerprinting + reverse IP for continuity across devices, browsers, sessions; stitches anonymous browsing, personal email, corporate domain into one account journey; deterministic signals (hashed emails, CRM IDs, auth events); automated normalization, dedupe, reconciliation at person and account level. Enrichment: Contact Enrichment Node retrieves verified emails and reachability attributes; licensed third-party providers; real-time reverse IP maps anonymous activity to company domains. AI: Atlas feeds predictive forecasting and journey analysis; Odin and Nova query stitched profiles, journeys, attribution in natural language.

Automationcompared to Common Room

Combine

  • Combine first-party behavior, third-party intent (G2, Bombora, keywords, funding, hiring), CRM, and ad engagement in filters, triggers, segments without engineering
  • Limited to ingested sources; no community, open source, or job-change combinations

Score

  • ML account and intent scoring 0-100 trained on historical conversions; multiple custom models; explainable; CRM sync
  • Cold-start problem needing closed-won history; no rules-first impact-points scoring; contact-level scoring not documented

AI Message

  • Nova generates message snippets and talking points from journey and intent context
  • No sequence/sales engagement delivery path; new capability with minimal proof; quality unsure

AI Research

  • Odin analyst agent; prompt library (demand gen, ABM); save/schedule prompts via email; recurring Auto Research on account lists by persona; MCP server
  • Weighted to internal analytics over external account research; no community, OSS, or social context; out-of-box prompt depth unsure

Workbench: AI-assisted GTM workbench, not a standalone to-do app; creates, assigns, prioritizes tasks in CRM. Workflow: visual if-this-then-that canvas (Source, Transform, Logic, Destination); GTM-native objects. Alert: Slack node with @mentions, custom instructions, dynamic variables. Combine: first-party, intent, CRM, ad data usable together in workflows without engineering. Score: ML 0-100 account and intent scores, multiple models, explainable, CRM sync. AI Message: Nova writes snippets and talking points. AI Research: Odin prompt library, scheduled prompts via email, recurring Auto Research on account lists.

Supportcompared to Common Room

Systems

  • Pylon ticketing with AI triage; shared Slack and Teams channels; live chat; email; docs site; Notion guides
  • Single-site in-person SF team; SLAs by tier unsure

Content

  • docs.hockeystack.com (Getting Started, Marketing Intelligence, Deal DNA, MCP, Security Audit Logs); HockeyStack 101 video series; async written guides
  • Attribution-centric training; thin docs for agents/workflows/deals; no certification or academy

Community

  • Template library; live preview dashboard; founder-led LinkedIn presence; private per-customer Slack/Teams channels
  • No public user forum or community; no user-generated templates; no peer learning

...

Status: Watch

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