# HockeyStack

> HockeyStack is a B2B revenue data intelligence platform that unifies website, CRM, marketing automation, ad, and product data into one model, then layers multi-touch attribution, buyer journey analytics, account scoring, and two AI agents (Odin for analytics, Nova for sales) on top, sold at custom pricing to mid-market and enterprise GTM teams.

- Category: GTM Analytics (https://saastracker.org/categories/gtm-analytics)
- Website: https://www.hockeystack.com
- Starting price: Custom (not published)
- Free plan: No
- Free trial: Demo-led evaluation; trials are arranged through sales, and there is no self-serve trial or free tier
- Founded: 2022, HQ: San Francisco, California, US, Ownership: Venture-backed
- Profile last reviewed: 2026-08-22
- Canonical profile: https://saastracker.org/products/hockeystack

## Overview

HockeyStack came out of Y Combinator in 2023 and grew abnormally fast by attacking the question every B2B CMO gets asked: what is actually driving pipeline? Its answer is a unified GTM data model: a cookieless tracking script for web behavior plus integrations into CRM (Salesforce, HubSpot), marketing automation (Marketo, Pardot, Eloqua), ad platforms (Google, LinkedIn, Meta, Microsoft), and sales tools, all resolved into account-level buyer journeys that run from first anonymous touch to closed-won.

The analytics layer is the sell: every attribution model with configurable lookbacks and custom weighting, lift reports that estimate the incremental impact of campaigns rather than just credited touches, funnel and deal-journey views that expose where accounts stall, and a no-code report builder that lets marketers assemble dashboards without SQL. Since 2025 the platform has been explicitly AI-first, with two agents: Odin, an analyst that answers natural-language questions against the full dataset, builds reports from prompts, and sends insight digests; and Nova, a sales-side agent that scores accounts using buyer journeys, automates account research, and drafts stakeholder maps inside Salesforce workflows.

The commercial reality: this is an enterprise-shaped product. There is no free tier and no published pricing; third-party reporting in 2026 places entry contracts at roughly $1,400 to $2,200 per month scaling well into six figures annually, with ABM, sales intelligence, and warehouse-sync sold as add-ons. Customers skew mid-market and up (Outreach, RingCentral, Tipalti, RealPage, Dice), and the company, founded by three Turkish founders and based in San Francisco, raised a $20M Series A led by Bessemer in January 2025 on the back of 4.5x annual revenue growth.

## How it works

1. You place HockeyStack's cookieless script on your web properties and connect your GTM systems: CRM, marketing automation, ad platforms, and optionally product and sales-engagement tools. The platform deduplicates and joins everything into a single account-level model, so an ad click, a pricing-page visit, a webinar attendance, an SDR call, and a stage change all land on one timeline per account.

2. Attribution and reporting run over that model: you choose attribution models (first-touch through custom-weighted multi-touch) with lookback windows, read pre-built dashboards that work from day one, and use the no-code builder for custom cuts, pipeline by channel, deal velocity by segment, content influence on closed-won, without writing SQL. Lift reports go a step beyond credited attribution, estimating the incremental effect of specific campaigns on pipeline.

3. Account Intelligence adds scoring and prioritization: transparent, configurable scores combining first-party journey data with third-party intent, plus AI-driven account research that merges public web data with the account's observed journey. High-scoring accounts flow to sales through alerts, dashboards, and a Salesforce-embedded view on the sales intelligence add-on.

4. The AI agents sit across all of it. Odin answers questions like 'which campaigns drove the most pipeline from enterprise accounts last quarter' in natural language, builds the corresponding report, and ships scheduled insight emails; Nova handles account research, scoring, and outreach-preparation workflows for reps. Workflow automation syncs audiences and triggers actions in connected tools, so findings become campaign and sales motions rather than dashboard trivia.

## Best for

Mid-market and enterprise B2B GTM teams, with RevOps capacity and Salesforce or HubSpot at the core, that spend enough on marketing and sales for attribution, lift measurement, and AI-driven account prioritization to change real budget decisions.

## Not the right fit for

- Early-stage startups with simple lead flows and no RevOps function; the platform's depth (and its four-figure monthly entry price) is wasted before there is pipeline complexity to analyze.
- B2C and ecommerce businesses; the data model is built around accounts, deals, and long multi-stakeholder cycles.
- Teams that need published pricing or a self-serve start; everything runs through a sales process, and there is no free tier.
- Buyers wanting classic web analytics or product analytics as the primary job; a lighter or broader tool does that for a fraction of the cost.
- Organizations requiring on-premise deployment; HockeyStack is cloud only.

## Features

### Unified GTM data model

One account-level dataset spanning web, CRM, marketing, ads, and sales activity.

- **Cookieless web tracking**: First-party, cookie-free script capturing site behavior, with EU-based data storage options for privacy review.
- **CRM integration**: Salesforce and HubSpot (plus Pipedrive and Freshsales) supply accounts, contacts, deals, and stages as the model's backbone.
- **Marketing automation and ad ingestion**: Marketo, Pardot, Eloqua, ActiveCampaign, and HubSpot Marketing on one side; Google, LinkedIn, Meta, and Microsoft Ads with spend data on the other.
- **Identity and account resolution**: Touches from anonymous web sessions through named CRM contacts are stitched into per-account journeys automatically.
- **Data warehouse sync (add-on)**: Bidirectional connectivity with the customer's warehouse for teams that want HockeyStack's model inside their own analytics stack.

### Attribution and measurement

The analytical core: flexible models plus incrementality, not just credit-splitting.

- **Every standard attribution model**: First-touch, last-touch, linear, U/W-shaped, and custom-weighted multi-touch, with configurable lookback windows.
- **Lift (incrementality) reports**: Estimates the incremental impact of campaigns on pipeline and revenue, addressing the classic critique that touch-based attribution rewards presence rather than causation.
- **Pre-built attribution dashboard**: A ready-made dashboard that reports on day one, before custom modeling work begins.
- **Funnel and deal-journey analytics**: Multistep pre-conversion paths and deal-journey views that expose where accounts stall between stages.
- **No-code report builder**: Custom dashboards and reports assembled without SQL, the main interface for marketers rather than analysts.

### AI agents

The 2025-era layer that turned HockeyStack from dashboards into an assistant.

- **Odin, the AI analyst**: Answers natural-language questions across the full dataset, builds reports and visualizations from prompts, and sends scheduled insight emails; positioned for tasks up to board-deck preparation.
- **Nova, the AI sales agent**: Scores accounts from buyer journeys, automates account research, builds stakeholder maps, and prepares personalized outreach inside Salesforce-centered workflows.
- **AI account research**: Combines public web data with the account's observed journey to produce research summaries for target accounts automatically.
- **AI governance controls**: The company documents that customer data is not used to train global models, with encryption and access controls around agent features.

### Account intelligence and activation

Turning journey data into prioritization and action for sales and ABM.

- **Configurable account scoring**: Transparent scores combining first-party behavior, CRM signals, and third-party intent (6sense integration among sources), tunable rather than black-box.
- **Sales intelligence add-on**: AE/SDR dashboards, real-time rep alerts on account activity, and a Salesforce-embedded iframe view of journeys.
- **ABM add-on**: Audience sync to ad platforms, account scoring, and CRM sync for account-based programs.
- **Workflow automation**: Triggers and syncs across connected tools so scoring and journey events kick off campaigns, alerts, and list changes.
- **Slack and collaboration hooks**: Alerts and reports delivered where teams work, including Slack.

## Use cases

- **CMO at a mid-market SaaS company facing board scrutiny**: Marketing claims influence on most pipeline, finance sees only last-touch lead sources, and the disagreement resurfaces every quarterly board meeting. Outcome: HockeyStack's multi-model attribution and lift reports give a defensible pipeline-contribution story, and Odin assembles the recurring board reporting that used to consume an analyst's week each quarter.
- **RevOps director rationalizing a bloated GTM stack**: Attribution lives in spreadsheets, intent in one vendor, web analytics in another, and account scoring in a fourth; nobody trusts any of them because none agree. Outcome: One unified model replaces the reconciliation work, with scoring, journeys, and attribution reading from the same data, and warehouse sync keeps the analytics team's stack in the loop.
- **Demand gen lead running seven-figure paid programs**: Needs to know whether the LinkedIn ABM program is incrementally creating pipeline or just touching accounts that would have converted anyway. Outcome: Lift reports separate incremental impact from correlated presence, and the deal-journey view shows where influenced accounts stall, redirecting budget between programs with evidence.
- **Enterprise sales team ignoring MQLs**: Reps distrust marketing's lead scores and spend hours researching accounts before outreach. Outcome: Nova's journey-based account scores and automated research briefs land inside Salesforce, so reps prioritize accounts showing real buying behavior and start conversations already informed.

## Pricing

Custom-quoted annual contracts scaled on tracked contact/account volume, data ingestion, and feature tier, with ABM, sales intelligence, and data warehouse sync priced as separate add-ons.

- **Platform**: Custom annual contract. Unified data model, attribution, journeys, dashboards; Odin AI analyst; Scales by tracked contacts and data volume. Third-party reports in 2026 place entry pricing roughly between $1,400 and $2,200 per month; HockeyStack itself publishes no figures.
- **Add-ons (ABM, Sales Intelligence, Warehouse Sync)**: Custom annual, per add-on. ABM: audience sync, account scoring, CRM sync; Sales intelligence: rep dashboards, alerts, Salesforce iframe; Warehouse sync: bidirectional warehouse connectivity.

Billing notes:

- No pricing is published on hockeystack.com; every figure in circulation is third-party reporting, and quotes vary with tracked contact volume, ingestion, and add-ons.
- Reported entry contracts run roughly $12,000 to $24,000 per year for 10,000 to 25,000 tracked contacts, scaling to $75,000 to $150,000+ annually above 100,000 contacts (per 2026 third-party pricing research).
- Budget realistically above the platform fee: implementation, CRM cleanup, and onboarding effort commonly push first-year cost 30 to 50% over the quoted subscription, per the same research.
- Add-ons are separately priced, so the ABM and sales-intelligence capabilities that feature in demos are not automatically in the base quote.

Value assessment: For a GTM organization spending seven figures across marketing and sales, HockeyStack's price is small against the reallocation decisions it informs, and consolidating attribution, intent, scoring, and reporting tools can offset much of the contract. Below that scale the math inverts quickly: a five-figure annual analytics contract plus implementation effort is hard to justify before pipeline complexity exists, and the quote-only model means you cannot even price the decision without a sales cycle. This is a tool priced for companies where a single budget-shift decision exceeds the contract value.

## Strengths

- Genuinely unified GTM data model: web, CRM, marketing automation, ads, and sales activity resolved to account journeys, which most rivals only partially achieve.
- Attribution flexibility plus lift reporting; incrementality analysis is a real answer to the standard objections against multi-touch attribution.
- Odin and Nova are ahead of the category on applied AI: natural-language analysis, prompt-built reports, automated account research, and rep-facing workflows rather than a chatbot veneer.
- No-code report builder lets marketing self-serve custom dashboards instead of queueing behind analysts.
- Fast-moving, well-funded vendor ($20M Series A led by Bessemer, January 2025; 4.5x revenue growth the prior year) with credible mid-market and enterprise logos: Outreach, RingCentral, Tipalti, RealPage, Dice.
- Cookieless tracking with EU data storage and SOC 2 documentation via a public trust portal eases privacy review for a tool this data-hungry.

## Limitations

- Quote-only pricing with a reported four-figure monthly entry point excludes small teams and makes evaluation slow; total first-year cost routinely exceeds the sticker quote.
- Steep learning curve on advanced reports and data modeling; without dedicated RevOps ownership the platform's depth goes unused.
- Attribution quality inherits CRM hygiene: dirty Salesforce data or inconsistent campaign tagging degrades every downstream number.
- AI agents concentrate analysis into vendor-generated answers; teams still need someone able to sanity-check Odin's outputs against raw data.
- No self-serve tier, trial, or public sandbox, so proof requires committing to a sales-led pilot.
- Young company scaling very fast (roughly 65 to 100 employees in 2026); product surface is expanding quicker than polish in places, and some users report wanting broader integrations and more mature web-analytics basics.

## Comparisons

- **HockeyStack vs Dreamdata**: The head-to-head B2B attribution decision: Dreamdata offers a free tier, EU data processing, published-ish accessibility, and the strongest ad-platform activation loop (audience and conversion sync); HockeyStack counters with deeper analytics (lift reports, deal journeys), stronger AI (Odin, Nova), and a sales-side story Dreamdata lacks. Marketing-led teams optimizing ad spend usually fit Dreamdata; revenue organizations that want marketing and sales working one account model fit HockeyStack, at a higher price.
- **HockeyStack vs PostHog**: PostHog is a usage-priced behavioral data platform for engineers; HockeyStack is a quote-priced attribution and intelligence layer for GTM leadership. PostHog can store everything HockeyStack analyzes but ships none of the attribution, scoring, or AI-agent workflow out of the box. Product-led companies start with PostHog; sales-led companies with attribution budgets buy HockeyStack, and the largest run both.
- **HockeyStack vs Fathom Analytics**: Only nominally the same category: Fathom counts anonymous website traffic for $15/month with privacy as the product; HockeyStack tracks identified account journeys across the whole revenue motion for four figures monthly with intelligence as the product. If the question is 'how is the site doing', buy Fathom; if it is 'which programs create pipeline', Fathom cannot answer it and HockeyStack exists to.

## Implementation

- Setup time: The script and core integrations connect within days, and the pre-built attribution dashboard reports immediately; a trusted, tuned deployment (stage mapping, scoring, custom reports, CRM validation) typically takes weeks and real RevOps involvement.
- Learning curve: Moderate to high: pre-built dashboards and Odin lower the entry bar, but advanced report design and data modeling take dedicated learning, a limitation users consistently cite.
- Onboarding: Sales-led with implementation support and customer success; reviewers rate the CS teams responsive and implementations fast for the category.
- Migration: HockeyStack reads from your systems, so adoption is additive rather than rip-and-replace, but plan for CRM cleanup work up front: attribution surfaces every data-hygiene sin. Leaving later costs you the unified model and history, not your source data.

## Platform, API & security

- Platforms: Web app (cloud), Cookieless tracking script, Salesforce-embedded views (sales intelligence add-on)
- API: Integration-led architecture with a bidirectional data warehouse sync add-on; no self-serve public API positioning comparable to developer-first tools.
- Compliance: SOC 2 (trust portal), GDPR (documented cookieless tracking posture)
- Data residency: EU-based data storage available for web tracking data.
- SSO: Enterprise account controls handled through the sales process; not publicly detailed.
- Security notes: Customer data is not shared with third parties or used to train global AI models, per company documentation; fingerprint-based tracking is documented for GDPR review, and a public trust portal covers controls.

## Support

- Channels: Dedicated customer success and implementation support, In-app and email support, Slack-based alerting into customer workspaces
- Documentation: Public docs covering tracking, integrations, AI security, and privacy, plus HockeyStack Labs, a research arm publishing B2B benchmark studies.
- Community: No open community; the company runs an aggressive content and media operation (Labs benchmarks, podcasts) that functions as its public presence.

## Company

- Founded: 2022
- Founders: Bugra Gunduz (CEO), Emir Atli (CRO), Arda Bulut (CTO)
- Headquarters: San Francisco, California, US
- Ownership: Venture-backed
- Employees: ~65-100 (2026; 65 per the YC profile, ~100 per Owler mid-2026)
- Funding: $22.7M+ disclosed: a $2.7M seed led by General Catalyst (2023) and a $20M Series A led by Bessemer Venture Partners (January 2025), with Y Combinator among investors.

Funding history:

- Seed (2023): $2.7M. Led by General Catalyst; Y Combinator batch.
- Series A (2025): $20M. Led by Bessemer Venture Partners, with YC, Uncorrelated Ventures, and QNBeyond; announced January 2025.

Timeline:

- 2022: Founded by Bugra Gunduz, Emir Atli, and Arda Bulut, who began building the product as students in Turkey before relocating to San Francisco.
- 2023: Goes through Y Combinator and raises a $2.7M seed led by General Catalyst; revenue grows 4.5x over the following year.
- 2024: Establishes itself among the leaders in B2B revenue attribution, landing customers including Outreach, RingCentral, Tipalti, RealPage, and Dice.
- 2025: Raises a $20M Series A led by Bessemer (January) and ships the AI-first roadmap: Odin and Nova agents, Account Intelligence, and self-serve product improvements.
- 2026: Roughly 65 to 100 employees; positions itself as an AI GTM platform spanning attribution, account intelligence, and agent-driven workflows.

## Integrations

Salesforce, HubSpot (CRM and Marketing Hub), Marketo, Salesforce Pardot, Eloqua, ActiveCampaign, Google Ads, LinkedIn Ads, Meta Ads, Microsoft Advertising, 6sense, Outreach, Slack, Pipedrive and Freshsales, Data warehouses (bidirectional sync add-on)

## FAQ

### What is HockeyStack?

HockeyStack is a B2B revenue data intelligence platform that unifies website, CRM, marketing automation, ad, and sales data into account-level buyer journeys, then provides multi-touch attribution, lift reporting, account scoring, dashboards, and two AI agents (Odin for analytics, Nova for sales). It sells to mid-market and enterprise GTM teams on custom-priced annual contracts.

### How much does HockeyStack cost?

HockeyStack publishes no pricing; contracts are quoted on tracked contact volume, data ingestion, and add-ons. Third-party research in 2026 reports entry contracts around $12,000 to $24,000 per year (roughly $1,400 to $2,200 per month) scaling to $75,000 to $150,000+ annually for large deployments, with first-year totals often 30 to 50% above the platform fee once implementation is counted. Treat those as reported figures, not vendor list prices.

### Is there a free version or trial of HockeyStack?

No free tier, and no self-serve trial: evaluation runs through demos and sales-arranged pilots. Teams that want to validate B2B attribution on a free plan first typically start with Dreamdata's free tier and graduate to a paid comparison.

### What are Odin and Nova?

HockeyStack's two AI agents, launched with its 2025 AI-first push. Odin is the analytics agent: it answers natural-language questions across the unified dataset, builds reports and dashboards from prompts, and sends scheduled insight emails. Nova is the sales agent: it scores accounts from buyer journeys, automates account research and stakeholder mapping, and prepares outreach inside Salesforce-centered workflows.

### Which attribution models does HockeyStack support?

Effectively all of them: first-touch, last-touch, linear, position-based, and custom-weighted multi-touch models with configurable lookback windows, plus lift reports that estimate the incremental impact of campaigns on pipeline rather than only distributing credit across touches.

### What does HockeyStack integrate with?

CRMs (Salesforce, HubSpot, Pipedrive, Freshsales), marketing automation (Marketo, Pardot, Eloqua, ActiveCampaign, HubSpot Marketing), ad platforms (Google, LinkedIn, Meta, Microsoft), intent and sales tools (6sense, Outreach, Slack), and data warehouses via a bidirectional sync add-on.

### How does HockeyStack track website visitors?

Through a first-party, cookieless script whose data is stored in the EU, joined with CRM and third-party data to resolve activity to accounts. The company documents its GDPR posture, including guidance that the script belongs in your consent-banner list where one is used, and states tracking data is never sold or shared.

### Who are HockeyStack's typical customers?

B2B companies with multi-touch buying cycles, an existing Salesforce or HubSpot deployment, and GTM programs spanning paid media, content, events, and outbound, mostly mid-market and enterprise. Public customers include Outreach, RingCentral, Tipalti, RealPage, and Dice; early-stage startups with simple funnels are an explicit anti-fit.

### How hard is HockeyStack to implement?

Basic deployment is quick (script plus integrations, with a pre-built attribution dashboard reporting from day one), but a trusted rollout takes weeks of stage mapping, scoring configuration, and CRM validation, and reviewers consistently flag a steep learning curve on advanced reports. Plan for RevOps ownership, not a set-and-forget install.

### Who founded HockeyStack and how is it funded?

Bugra Gunduz (CEO), Emir Atli (CRO), and Arda Bulut (CTO) founded the company in 2022, went through Y Combinator in 2023, and are based in San Francisco. Disclosed funding totals $22.7M+: a $2.7M seed led by General Catalyst and a $20M Series A led by Bessemer Venture Partners announced in January 2025.

## Editorial verdict

HockeyStack is the maximalist option in GTM analytics: the widest data model, the most attribution machinery, and the most convincing applied AI in the category, and for a revenue organization with real budget and RevOps muscle it can legitimately replace three or four point tools while answering questions none of them could. But it is priced and shaped strictly for that buyer: no free tier, quote-only contracts reportedly starting in the four figures monthly, meaningful implementation lift, and dependence on the CRM hygiene of the company deploying it. Mid-market-and-up teams should shortlist it against Dreamdata and decide between HockeyStack's analytical and AI depth and Dreamdata's activation loop and friendlier entry; everyone smaller should wait until the question it answers is worth its price.

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Source: SaaSTracker (https://saastracker.org), an independent editorial project. This profile is compiled from public information, carries no peer reviews or paid placement, and was last reviewed 2026-08-22. Awards are judged on published criteria: https://saastracker.org/methodology