Agentic Analytics Revolution: How HockeyStack & AirOps Transform Business Intelligence

Agentic Analytics Revolution: How HockeyStack & AirOps Transform Business Intelligence

According to Deloitte’s 2025 forecast, 25% of companies using generative AI will launch agentic AI pilots this year, but most organizations struggle to bridge the gap between raw data and actionable intelligence as these AI-powered systems can now complete complex tasks with little or no human supervision. Despite investing billions in analytics tools, businesses find that 62% of marketers still spend over 10 hours weekly on manual data analysis tasks that could be automated, according to recent industry surveys.

TL;DR: Agentic analytics represents the next evolution in business intelligence—AI systems that not only analyze data but autonomously make decisions and take actions based on that analysis. Platforms like HockeyStack and AirOps are at the forefront of this revolution, using AI agents to transform how businesses extract value from their data. By combining multiple AI models with human-in-the-loop workflows, these platforms save marketing teams substantial time while delivering deeper insights and driving measurable business impact through automated, contextually-aware analysis and execution.

What Is Agentic Analytics?

Agentic analytics refers to AI-powered systems that can autonomously analyze data, identify patterns, make decisions, and take actions with minimal human intervention. Unlike traditional analytics tools that merely present data for human interpretation, agentic analytics platforms use AI agents to close the loop between data analysis and business execution.

These systems combine advanced machine learning, natural language processing, and workflow automation to transform how businesses extract value from their data. They’re designed to understand context, learn from interactions, and continuously improve their performance over time.

Featured Snippet Target (40 words): Agentic analytics uses autonomous AI systems to analyze data, make decisions, and execute actions with minimal human input. Unlike traditional analytics that just present information, agentic platforms like HockeyStack and AirOps actively transform raw data into automated workflows and business outcomes.

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Why It Matters in 2025

The Agentic AI Boom

Discussions regarding agentic AI reached 2.2% of earnings calls in Q1 2025, rising 275% quarter-over-quarter, surpassing mentions of related AI systems like copilots, chatbots, and ChatGPT. This dramatic increase reflects the growing recognition that AI systems capable of autonomous action represent the next frontier in business technology.

The global enterprise agentic AI market is experiencing explosive growth, expected to expand from $5.4 billion in 2024 to approximately $50 billion by 2030, representing a CAGR of over 45% as more businesses adopt these systems for automation, enhanced decision-making, and operational efficiency improvements.

The Analytics Evolution

Analytics has traditionally followed a predictable progression: descriptive (what happened), diagnostic (why it happened), predictive (what will happen), and prescriptive (what should be done). Agentic analytics adds a crucial fifth stage: autonomous execution—actually implementing the recommended actions without requiring human intervention for every step.

From Insights to Outcomes

Modern businesses are drowning in data but starving for actionable intelligence. Agentic analytics bridges this gap by not only providing insights but also translating them directly into business outcomes through automated workflows and decision-making processes.

HockeyStack: Revenue Intelligence Through Agentic Workflows

HockeyStack has emerged as a leading platform in the agentic analytics space, focused specifically on marketing and revenue analytics. Recently raising $20 million in Series A funding, the platform is transforming how B2B companies approach data-driven marketing.

Core Capabilities

HockeyStack primarily serves B2B companies looking to optimize their marketing analytics and attribution. The platform has shown impressive growth, with revenue increasing 4.5x from 2023 to 2024 while managing more than $20 billion of campaign spend for its over 130 customers.

Key features of HockeyStack include:

1. Multi-touch attribution: Tracking customer journeys across all touchpoints to accurately attribute revenue to marketing efforts
2. AI-driven insights: Using machine learning to identify patterns and opportunities in marketing data
3. Cookieless tracking: Privacy-compliant analytics that doesn’t rely on third-party cookies
4. No-code report builder: Custom analytics dashboards without requiring technical expertise

Agentic AI Integration: Meet Odin

The most significant development in HockeyStack’s platform is the introduction of “Odin,” an AI agent that takes marketing analytics to a new level of autonomy. Odin automates responses to marketing queries and enhances customer research using sales data and web analytics, creating a truly agentic experience.

Odin’s capabilities include:

• Automated account research and insights
• Weekly email reports with actionable insights
• Creation of custom reports from natural language requests
• Dashboard analysis and opportunity identification
• Collaborative brainstorming with marketing teams

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Real-World Impact

HockeyStack’s agentic approach is delivering measurable results for B2B companies. As one customer testimonial notes: “Thanks to HockeyStack, we can now see all marketing-influenced closed deals. It gives us better visibility into pipeline source and ROI.”

The platform is particularly effective at illuminating the “dark funnel” – marketing touchpoints that typically go untracked in traditional analytics systems. This comprehensive view allows marketing teams to make more informed decisions about resource allocation and strategy.

AirOps: Content Intelligence Through Agentic Workflows

While HockeyStack focuses on marketing attribution and revenue analytics, AirOps has carved out a niche in content intelligence and SEO-driven growth. The platform helps marketing teams scale content creation while maintaining quality and brand consistency.

Core Capabilities

AirOps allows businesses to build AI-powered workflows for content research, creation, and optimization. AirOps is the first AI-workflow platform built for content teams blending human expertise with AI automation to drive demand at scale.

Key features include:

1. AI workflow builder: A drag-and-drop interface for creating complex, multi-step content workflows
2. Multi-model flexibility: Leveraging various AI models (GPT-4, Claude, etc.) for different content tasks
3. Knowledge base integration: Connecting brand guidelines and expertise with AI systems
4. Human-in-the-loop quality control: Built-in review steps to ensure content quality
5. CMS integrations: Direct publishing to content management systems

The AirOps Evolution

AirOps has undergone a significant transformation since its inception. When initially launched, the company had a broader remit to help any business create AI-enabled applications, but has since focused specifically on content intelligence after identifying where AI models could deliver the most value.

In October 2024, AirOps secured $15.5 million in Series A funding to further develop its platform and expand its go-to-market operations, indicating strong investor confidence in its approach to agentic content analytics.

Real-World Applications

AirOps excels in several key content workflows:

• SEO content creation: Generating optimized content based on keyword research and competitive analysis
• Content refresh: Systematically updating existing content to maintain relevance and performance
• Topic cluster development: Building comprehensive content ecosystems around central themes
• Competitive gap analysis: Identifying content opportunities based on competitor weaknesses
• Content performance prediction: Using AI to forecast the potential impact of content before creation

The Convergence of Analytics and Agency

What makes platforms like HockeyStack and AirOps truly revolutionary is their ability to combine deep analytics with autonomous action. This represents a fundamental shift in how businesses approach data-driven decision making.

From Analysis to Automation

Traditional analytics tools require humans to bridge the gap between insight and action. Agentic platforms automate this connection, creating closed-loop systems where data insights trigger specific actions without constant human intervention.

The Role of Orchestration

One of the most powerful aspects of agentic analytics is the ability to orchestrate complex workflows across multiple systems and data sources. In 2025 and beyond, enterprises are looking to bring domain-specific intelligence to ensure AI agents deeply understand industry nuances and deliver precise responses and actions.

Both HockeyStack and AirOps excel at this orchestration, creating seamless workflows that span different data sources, AI models, and business systems.

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Comparing Key Features

Feature	HockeyStack	AirOps
Primary Focus	Marketing attribution & revenue analytics	Content intelligence & SEO workflows
Key AI Agent	Odin	AI Workflow Builder
Target Audience	B2B marketing & sales teams	Content marketers & SEO specialists
Core Metrics	Revenue impact, attribution modeling	Content performance, SEO visibility
Pricing (Starting)	$2,200/month	$199/month
Notable Integrations	CRM systems, ad platforms, web analytics	CMS platforms, SEO tools, AI models
Unique Strength	Multi-touch attribution modeling	Customizable content workflows

Pros & Cons of Agentic Analytics

Pros

• Time Efficiency: AI technologies have been shown to boost productivity and efficiency, with 63% of executives stating that their AI portfolio will financially impact their organization in the next two years
• Deeper Insights: AI agents can analyze more data points and identify patterns humans might miss
• Consistent Execution: Automated workflows ensure consistent implementation of best practices
• Scalability: Analytics processes can scale without proportional increases in human resources
• Adaptive Learning: Systems improve over time based on results and feedback

Cons

• Implementation Complexity: Integrating agentic systems with existing tools can be challenging
• Potential Oversight Gaps: Autonomous systems may require careful monitoring for quality control
• Cost Considerations: Enterprise-grade platforms require significant investment
• Change Management: Organizations may face resistance to AI-driven decision making
• Data Quality Dependencies: Systems are only as good as the data they access

Pricing & ROI

HockeyStack Investment

HockeyStack’s pricing starts at approximately $2,200 per month, positioning it as an enterprise-grade solution for serious B2B marketing teams. While this represents a significant investment, customers report substantial ROI through:

• Improved marketing attribution accuracy
• Better budget allocation across channels
• Increased conversion rates through insight-driven optimization
• Time savings from automated reporting and analysis

AirOps Economics

AirOps offers more flexible pricing options, with plans starting around $199 per month and scaling based on usage and features. The platform delivers ROI through:

• Reduced content production costs
• Improved organic traffic from optimized content
• Time savings in research and content planning
• More consistent content quality and brand voice

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How to Get Started

1. Assess Your Analytics Maturity

Before implementing agentic analytics, organizations should assess their current analytics capabilities and identify specific use cases where automation would deliver the greatest value.

2. Start With a Focused Use Case

Rather than attempting a complete analytics transformation, begin with a specific workflow or problem that agentic analytics can address. For example:

• With HockeyStack: Implement multi-touch attribution for a specific marketing channel
• With AirOps: Create an automated workflow for refreshing underperforming content

3. Integrate With Existing Systems

Ensure your agentic analytics platform can access the necessary data sources and integrate with your existing martech or content stack.

4. Establish Clear Metrics

Define specific KPIs to measure the impact of your agentic analytics implementation, focusing on both efficiency gains and business outcomes.

5. Build Human-AI Collaboration

As AI-powered automation and generative AI agents become more popular, it is critical for enterprises to establish strong governance frameworks. The most successful implementations maintain an appropriate balance between AI autonomy and human oversight.

Key Takeaways

• Agentic analytics represents a fundamental evolution in business intelligence, moving beyond passive reporting to active decision-making and execution.
• Platforms like HockeyStack and AirOps are pioneering this approach in marketing analytics and content intelligence respectively.
• The market for agentic AI is growing rapidly, with projections suggesting it will reach $50 billion by 2030.
• Successful implementation requires a thoughtful approach to use cases, integration, and human-AI collaboration.
• Despite the power of automation, human expertise remains essential for strategy, creativity, and ensuring AI systems deliver maximum value.

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