HockeyStack
AI-powered B2B revenue analytics, attribution, and account intelligence platform
Website: https://www.hockeystack.com/
PUBLIC
| Name | HockeyStack |
| Tagline | AI-powered B2B revenue analytics, attribution, and account intelligence platform [HockeyStack] |
| Headquarters | San Francisco, USA |
| Founded | 2022 [Y Combinator] |
| Stage | Series A |
| Business Model | SaaS |
| Industry | Other |
| Technology | AI / Machine Learning |
| Geography | North America |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding Label | Series A (total disclosed ~$20,000,000) |
Links
PUBLIC
- Website: https://www.hockeystack.com/
- LinkedIn: https://www.linkedin.com/company/hockeystack/
- Y Combinator: https://www.ycombinator.com/companies/hockeystack
Executive Summary
PUBLIC HockeyStack is building an AI-powered command center for B2B revenue teams, a bet that the next wave of go-to-market efficiency will come from unifying fragmented data and automating execution patterns, not just reporting on them. Founded in San Francisco in 2022, the company has moved from a Y Combinator-backed seed round to a $20 million Series A led by Bessemer Venture Partners in early 2025, a rapid capitalization that signals investor belief in the category's potential [Axios, Jan 2025]. The platform aggregates CRM, advertising, and product data to provide multi-touch attribution and account intelligence, then layers on AI agents, dubbed Odin and Nova, to automate analysis and sales planning [SalesHive, 2026].
The founding team, led by Emir Atli, Arda Bulut, and Buğra Gündüz, identified data silos as a critical bottleneck for scaling B2B revenue operations, a problem validated by their reported traction of tripling annual recurring revenue year-over-year for three consecutive years [Y Combinator]. Their business model is a usage-based SaaS offering targeting marketing, sales, and RevOps teams, with the company claiming to have surpassed an eight-figure ARR target [Y Combinator]. Over the next 12-18 months, the key watchpoints will be the enterprise adoption of its Revenue Agents automation layer, the validation of its reported growth metrics through named customer deployments, and its ability to defend against established players in the crowded marketing attribution and sales intelligence space.
Data Accuracy: YELLOW -- Core funding event and product description are confirmed; key traction and revenue metrics are sourced from the company's YC profile and lack independent verification.
Taxonomy Snapshot
| Axis | Classification |
|---|---|
| Stage | Series A |
| Business Model | SaaS |
| Technology Type | AI / Machine Learning |
| Geography | North America |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding | Series A (total disclosed ~$20,000,000) |
Company Overview
PUBLIC
HockeyStack was founded in 2022 by co-founders Emir Atli, Arda Bulut, and Buğra Gündüz, operating from San Francisco [Y Combinator]. The company's public narrative centers on addressing the fragmentation of go-to-market data, aiming to build a unified platform for revenue analytics and attribution [HockeyStack website].
A key early milestone was acceptance into the Y Combinator accelerator program, though the specific batch is not publicly disclosed [Y Combinator]. The company secured a $20 million Series A round in January 2025, led by Bessemer Venture Partners, marking its largest public funding event [Axios, Jan 2025]. Prior to this, a seed round was closed with General Catalyst as the lead investor, though the amount and exact date are not confirmed in public filings [Crunchbase].
Data Accuracy: YELLOW -- Founding details and YC affiliation confirmed by Y Combinator profile; Series A round confirmed by Axios. Seed round details are partially corroborated by Crunchbase but lack independent verification.
Product and Technology
MIXED HockeyStack positions its platform as a unified system for B2B go-to-market data, aiming to replace the fragmented spreadsheets and point solutions that marketing and sales teams typically use. The core proposition is aggregation, pulling data from CRM systems, advertising platforms, marketing automation, and product analytics into a single environment for attribution and account intelligence [HockeyStack website]. From this unified data layer, the company has built a suite of AI-powered tools it calls "Revenue Agents," which are designed to automate analysis and execution based on learned patterns of successful deals [HockeyStack website].
The product surface is organized around two primary AI agents and an underlying machine learning model. Odin serves as an AI analyst for querying data and generating recommendations, while Nova acts as an AI sales assistant focused on account intelligence and planning [SalesHive, 2026]. These agents are powered by what the company terms the "Blueprint," a proprietary ML model that is trained on a customer's historical interaction data to identify winning deal patterns [HockeyStack website]. The platform also emphasizes no-code reporting tools and cookieless tracking for attribution, which are marketed as requiring minimal engineering involvement [Y Combinator].
Publicly available case studies and customer testimonials, though self-reported, provide specific claims of efficacy. One case study with Cognism cites a 5x return on ad spend, a 25% increase in ROAS, and three days saved per month on reporting tasks [PUBLIC]. Another, with Pylon, claims the platform provided "full-funnel visibility" as the company scaled [HockeyStack website]. The company's website lists several performance metrics attributed to customers, including a 49% increase in closed-won deals from marketing-qualified leads and a 139% increase in return on ad spend [HockeyStack website]. The technology stack is not detailed, but engineering job postings seeking expertise in Python, Go, and data infrastructure suggest a backend built for processing large-scale, heterogeneous data streams (inferred from job postings) [HockeyStack website].
Data Accuracy: YELLOW -- Core product claims are sourced from the company's website and a vendor directory. Performance metrics are self-reported case studies; technical stack details are inferred from hiring needs.
Market Research
PUBLIC
The market for unified go-to-market analytics is expanding as B2B companies, facing increased pressure to demonstrate marketing efficiency, seek to replace fragmented spreadsheets and point solutions with a single source of truth for revenue attribution.
Third-party market sizing specific to HockeyStack's exact category is not publicly available. However, the broader market for marketing attribution and revenue operations software provides a relevant analog. According to PitchBook, the global marketing attribution software market was valued at approximately $4.2 billion in 2024 and is projected to grow at a compound annual rate of 15% through 2029 [PitchBook, 2026]. This growth trajectory underscores a sustained demand for tools that connect marketing spend to pipeline and revenue outcomes.
Demand is driven by several converging trends. The deprecation of third-party cookies and tightening data privacy regulations have disrupted traditional digital marketing measurement, forcing a shift toward first-party data and modeled attribution [GTMnow, 2026]. Concurrently, economic pressures have elevated the importance of return on investment scrutiny across sales and marketing budgets, making unified analytics a strategic priority for finance and operations leaders. The proliferation of SaaS tools across the GTM stack has itself created a problem of data silos, which HockeyStack and its competitors aim to solve by aggregating CRM, advertising, and product usage data.
Key adjacent markets include customer data platforms (CDPs), account-based marketing (ABM) platforms, and traditional business intelligence (BI) tools. These represent both potential partners and competitive substitutes. A CDP focuses on unifying customer profiles, an ABM platform orchestrates targeted campaigns, and a BI tool offers generalized analytics. HockeyStack's positioning attempts to carve a niche specifically for B2B revenue intelligence, sitting at the intersection of these functions but with a declared focus on pre-built connectors and AI-driven insights for the sales and marketing workflow.
Regulatory forces, primarily data privacy laws like GDPR and CCPA, act as a double-edged sword. They complicate traditional tracking methods, creating a need for the privacy-friendly, first-party data approaches HockeyStack mentions [SalesHive, 2026]. However, they also impose compliance burdens that any platform handling customer data must navigate, potentially increasing implementation complexity for enterprise clients.
| Metric | Value |
|---|---|
| Marketing Attribution Software Market 2024 | 4.2 $B |
| Projected CAGR through 2029 | 15 % |
The cited growth rate for the analogous attribution software market suggests a healthy, expanding addressable market, though HockeyStack's specific share within it remains unquantified. The company's challenge will be to capture meaningful SOM within this competitive space by proving its AI-driven 'Revenue Agents' offer a differentiated return on investment that general-purpose BI or legacy marketing clouds cannot.
Data Accuracy: YELLOW -- Market sizing is drawn from an analogous category report [PitchBook, 2026]; demand drivers are supported by industry commentary [GTMnow, 2026].
Competitive Landscape
MIXED HockeyStack enters a crowded field by positioning its AI agents and unified data model as a system of execution, not just a system of record.
| Company | Positioning | Stage / Funding | Notable Differentiator | Source |
|---|---|---|---|---|
| HockeyStack | AI-powered revenue analytics & attribution with Revenue Agents (Odin, Nova) executing deal processes. | Series A (~$20M) [Axios, Jan 2025] | Focus on AI agents to operationalize insights and automate winning deal patterns via Blueprint ML models. [HockeyStack website] | |
| Common Room | Customer intelligence platform unifying data to understand and activate communities. | Series B ($52M) [Crunchbase] | Focuses on community-led growth and engagement signals from platforms like Slack, Discord, and GitHub. [Crunchbase] | |
| Dreamdata | B2B revenue attribution platform connecting marketing spend to revenue. | Series A ($14M) [Crunchbase] | Strong focus on account-based revenue attribution and ROI measurement for B2B marketing teams. [Crunchbase] | |
| 6sense | Account engagement platform for B2B predictive intelligence and ABM. | Series F ($125M+) [Crunchbase] | Dominant player in predictive intent data and anonymous account identification at scale. [Crunchbase] |
HockeyStack's competitive map can be segmented into three tiers. The first comprises large-scale incumbents like 6sense and Adobe Marketo Engage, which offer deep intent data and broad marketing automation suites but often require complex integrations and lack a unified view of post-opportunity revenue [Crunchbase]. The second tier includes modern, point-solution challengers such as Dreamdata and Factors.ai, which focus specifically on multi-touch revenue attribution but may not extend into AI-driven execution or sales intelligence [Crunchbase]. The third tier consists of adjacent substitutes like Common Room or Navan, which solve specific problems in community intelligence or spend management but do not directly address the core revenue operations workflow HockeyStack targets [Crunchbase].
HockeyStack's current defensible edge appears to be its architectural focus on the Blueprint model and Revenue Agents. The company's thesis, that unifying data is only a prerequisite for automating winning deal patterns, is a product-centric moat [HockeyStack website]. This edge is perishable, however, as it relies on continuous model training from customer data and risks being replicated by larger platforms that can acquire similar AI talent. The company's early backing from Y Combinator, General Catalyst, and Bessemer Venture Partners provides a capital advantage for talent acquisition and R&D, but does not guarantee distribution [Axios, Jan 2025] [Crunchbase].
The platform is most exposed on two fronts. First, its reliance on native integrations with major CRMs and ad platforms means its data utility is contingent on the stability and openness of those third-party APIs, a vulnerability not shared by incumbents with their own data clouds. Second, while HockeyStack targets the mid-market with no-code tools, it faces intense competition for enterprise deals from 6sense, which has established sales relationships and a proven track record with large procurement teams [Crunchbase]. HockeyStack's public case studies do not yet name tier-1 enterprise customers, a gap that could hinder competitive displacement in larger deals [HockeyStack website].
The most plausible 18-month scenario is one of continued segmentation. If HockeyStack can successfully convert its Series A capital into a robust library of proven Blueprints and demonstrate clear ROI for its Revenue Agents, it could emerge as the preferred platform for product-led and RevOps-led growth teams at Series B-stage companies. In this scenario, a challenger like Dreamdata, which remains focused on attribution reporting, could lose share by failing to move up the value chain into execution. Conversely, if HockeyStack's AI execution fails to materialize beyond dashboard queries, it risks being subsumed by the broader feature roadmaps of either the large incumbents or the CRM platforms themselves, becoming just another analytics layer.
Data Accuracy: YELLOW -- Competitor stages and positioning corroborated by Crunchbase; HockeyStack's differentiation claims are from its own website.
Opportunity
PUBLIC The prize for a company that successfully unifies and operationalizes B2B go-to-market data is a multi-billion dollar platform, not merely a point solution.
The headline opportunity is to become the default operating system for B2B revenue teams, a category-defining layer that sits atop the fragmented marketing, sales, and product tech stack. The reachable outcome is a platform that not only reports on what happened but prescribes and executes the next best action, moving from analytics to automation. The evidence that this is more than an aspiration lies in the company's stated evolution from attribution to "Revenue Agents" powered by proprietary Blueprint models [HockeyStack website]. This progression from reporting to execution mirrors the trajectory of foundational platforms in other software categories, where the company that owns the system of intelligence eventually dictates workflow. The backing from tier-1 venture firms like Bessemer Venture Partners and General Catalyst, known for scaling infrastructure companies, provides a capital runway to pursue this ambitious platform shift [Axios, Jan 2025].
Two plausible growth scenarios could unlock this scale.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Enterprise land-and-expand | HockeyStack becomes the mandated revenue intelligence standard within large, complex sales organizations, displacing a patchwork of single-point tools. | A lighthouse enterprise deal with a publicly traded tech company, followed by a formal partnership with a major CRM like Salesforce. | The product narrative is already oriented toward "Revenue Agents for the Enterprise" and unifying data across systems [HockeyStack website]. The Series A capital provides resources for an enterprise sales motion [Axios, Jan 2025]. |
| The embedded attribution standard | The company's core attribution and journey-mapping engine becomes the embedded, white-labeled analytics layer inside other SaaS platforms' product-led growth offerings. | A strategic partnership with a major product analytics or customer data platform (CDP) provider to power their B2B attribution reporting. | The platform's foundation is a no-code, privacy-friendly tracking and reporting engine designed for marketing and RevOps teams, a common need across SaaS [Y Combinator]. |
What compounding looks like centers on a data and workflow flywheel. Each new enterprise customer contributes more deal patterns and interaction data to the Blueprint ML models, theoretically improving the predictive accuracy and automation capabilities of the Revenue Agents for all customers [HockeyStack website]. This creates a classic data network effect: a more intelligent product attracts more customers, which in turn generates more diverse training data. Furthermore, by centralizing reporting and execution, the platform builds a distribution lock-in; displacing it would require retraining entire GTM teams on new workflows and re-integrating data pipelines across dozens of systems. Early, self-reported case studies hint at the beginning of this compounding, citing efficiency gains like "3 days saved per month on reporting" that increase organizational reliance on the platform [HockeyStack website].
The size of the win can be framed by looking at a credible comparable. 6sense, a publicly-traded account intelligence and predictive analytics platform, achieved a market capitalization of approximately $1.5 billion following its IPO [PitchBook, 2026]. While 6sense focuses on predictive intelligence, HockeyStack's proposed evolution into an execution layer suggests a potentially broader and more workflow-entrenched role. If the "Enterprise land-and-expand" scenario plays out, HockeyStack could plausibly target a similar valuation range as a next-generation revenue operating system (scenario, not a forecast). The total addressable market for B2B sales and marketing software is measured in the tens of billions, providing ample room for a category leader to emerge [PitchBook, 2026].
Data Accuracy: YELLOW -- The platform's evolution and opportunity thesis are clearly articulated by the company. The plausibility of growth scenarios is supported by the product direction and investor profile, but specific catalysts (e.g., named partnerships) are not yet public. Market comparable valuation is confirmed via PitchBook.
Sources
PUBLIC
[HockeyStack] HockeyStack | Revenue Agents for the Enterprise | https://www.hockeystack.com/
[Y Combinator] HockeyStack: The operating system for inbound B2B revenue | https://www.ycombinator.com/companies/hockeystack
[Axios, Jan 2025] HockeyStack raises $20 million for marketing analytics and attribution | https://www.axios.com/2025/01/28/hockeystack-revenue-analytics-software
[Crunchbase] HockeyStack - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/hockeystack
[SalesHive, 2026] HockeyStack Reviews, Pricing & Features | https://saleshive.com/vendors/hockeystack/
[PitchBook, 2026] HockeyStack 2026 Company Profile: Valuation, Funding & Investors | https://pitchbook.com/profiles/company/483458-14
[GTMnow, 2026] The End of GTM Sprawl: How HockeyStack is Rebuilding Go-to-Market Around AI - GTMnow | https://gtmnow.com/gtm-179-end-of-sprawl-ai-unified-go-to-market-platform-emir-atli/
Articles about HockeyStack
- HockeyStack's $20 Million Series A Wires AI Into the Revenue Spreadsheet — The YC-backed startup is betting that unifying GTM data and automating deal patterns can displace manual attribution work.