Crunchbase today launched Market Insights, a suite of private market signals built around a proprietary segmentation layer of more than 5,100 micro-industries, an updated competitive intelligence model with plain-language explanations, and a directional indicator that classifies market segments as emerging, growing, or declining. The announcement adds sector-level intelligence to a predictive platform that has already confirmed more than 17,700 company-level predictions.

What Crunchbase released

The launch, announced June 2, 2026 from San Francisco, comprises three distinct components. Each one addresses a different layer of private market analysis that, according to Crunchbase, teams have historically assembled through manual research and fragmented data sources.

The first component is micro-industries - a segmentation layer that organizes companies according to what they build rather than which broad industry category they have been assigned to. The second is an overhaul of competitor intelligence, adding ranked scores and plain-language reasoning to each competitive pairing. The third is the Market Insights signal, a standardized indicator that assigns a directional label and summary to each micro-industry segment.

Taken together, Crunchbase is positioning the release as a move from company-level predictions to sector-level intelligence - a layer above its existing forecasting work.

"We built market insights to solve a core challenge we kept hearing from customers: understanding private markets is still too manual, fragmented, and reactive," said Monika Abraham, Staff Product Manager at Crunchbase. "Building on years of developing AI-powered predictions and proprietary market intelligence, this launch introduces a new suite of signals - micro-industries, explainable competitor intelligence, and Market Insights - to help teams identify emerging markets, understand competitive dynamics, and track market momentum without stitching fragmented signals together manually."

The micro-industries architecture

Crunchbase's existing industry taxonomy classifies companies into broad categories that have long been the standard in private market databases. According to Crunchbase, these labels are often too coarse to support precise decisions around ideal customer profiles, whitespace mapping, or competitive analysis. Micro-industries are designed to operate below that taxonomy, adding specificity without replacing the broader structure.

The dataset covers more than 2.7 million private companies and 13.2 million mapped products. A proprietary clustering system first identifies how products naturally group together. A large language model layer then refines label quality, improves hierarchy consistency, and resolves company-to-category assignments. The process is continuous - the segmentation evolves as company and product data changes.

One concrete example Crunchbase offers is the autonomous vehicle category. A traditional North American Industry Classification System classification places every autonomous vehicle company into a single broad category. Crunchbase's micro-industries break that into distinct segments - Autonomous Mobile Robots, Autonomous Vehicle Systems, and Robo-Taxi and Autonomous Shuttle Services, among others. Each reflects meaningfully different competitive dynamics, customer bases, and growth trajectories.

Companies can belong to multiple micro-industries simultaneously, which Crunchbase says mirrors how modern companies actually go to market. A logistics software company might legitimately operate in segments for fleet management, supply chain visibility, and last-mile delivery - and the segmentation model captures that.

Micro-industries are now available within market maps in Crunchbase Business and in the Predictions and Insights API package. Business plan users can also access them in search.

The competitor intelligence overhaul

Alongside micro-industries, Crunchbase released a substantially updated competitive data model. The updated system flags a company's top competitors, ranks them, and assigns each a competitive score. It also introduces something new: plain-language explanations of why specific companies compete.

According to Crunchbase, the architecture is hybrid. A machine learning candidate generation model is trained on products and services data and generates competitor candidates. A targeted LLM layer then refines those results - improving relevance, correcting ordering, and surfacing competitors that the first model may have missed.

The performance metrics Crunchbase reports are specific. The model delivers 90% precision on each company's top three competitors and 87% precision on the top five. Overall list accuracy across the full competitor set stands at 88.7%, based on human review.

The addition of plain-language reasoning came directly from customer feedback. According to Crunchbase, the underlying competitive data was difficult to act on or defend internally without context explaining the pairing. The reasoning now surfaces product overlap, shared customer segments, and geographic context for each competitive relationship.

Access to the updated competitor data follows a tiered structure. Crunchbase Business users get full access to ranked competitor lists, competitive landscape maps, and search filter functionality. API customers accessing the Predictions and Insights package receive competitor scores alongside the full reasoning output.

The Market Insights signal

The third component functions differently from the other two. Rather than organizing companies or mapping competitive relationships, the Market Insights signal produces a single directional label for a given market segment - emerging, growing, or declining - along with a percentage change figure and a plain-language summary explaining the underlying dynamics.

According to Crunchbase, the signal is designed to replace a process that typically involves manually aggregating funding rounds, tracking exit activity, monitoring engagement trends, and synthesizing macroeconomic context. All of that analysis is compressed into a single indicator.

Each Market Insight aggregates multiple signals across companies within a micro-industry segment: changes in cluster composition, funding and exit activity, profile engagement, and broader macroeconomic context. Because the signal is built on micro-industries data, teams can look at a target account and understand whether the niche segment it operates in is gaining or losing momentum - without building that analysis from scratch.

For investors and venture or private equity firms, according to Crunchbase, the signal provides earlier conviction on sector bets before a market reaches consensus. For go-to-market teams, it serves as a warning system - early signals of market contraction can inform decisions before churn appears at renewal.

The Market Insights signal is currently available in the Predictions and Insights API package. Availability within Crunchbase Business is planned for later in 2026.

Commercial context: 900% ACV growth in Q1

The launch follows a period of strong commercial growth for Crunchbase's Predictions and Insights offering. According to Crunchbase, average contract value for the product grew 900% year-over-year in Q1 2026. The growth was driven by demand from financial services firms, investment organizations, and software and AI companies seeking trusted private market data to support AI-driven workflows.

Crunchbase also disclosed that its two largest deals in company history closed in the last two quarters.

"Imagine if you had spotted the opportunity in AI coding assistants when they were a handful of unknown startups, not when they had already raised billions," said Jager McConnell, CEO of Crunchbase. "That's what our new market insights can do: reveal where momentum is forming early, so you can get ahead of the next big market, instead of chasing it."

The predictive intelligence platform that underpins Market Insights debuted in early 2025. According to Crunchbase, it combines nearly 20 years of proprietary startup data with real-time activity signals from more than 80 million users. Crunchbase says more than 17,700 company-level predictions have been confirmed by real-world events since the platform launched.

Two examples Crunchbase cites publicly: the company flagged defense tech startup Anduril Industries as a likely fundraising candidate more than a month before its $5 billion round was announced in May. Crunchbase also identified modular nuclear power plant company Blue Energy's raise eight months before the company announced its $380 million round in April.

Leadership changes tied to the launch

Alongside the product announcement, Crunchbase disclosed two executive appointments. Ketaki Rao has joined as Chief Product Officer, and Ann Davis has been promoted to Chief Revenue Officer.

"Enterprises need trusted private market data and predictive intelligence, and they're increasingly turning to Crunchbase for it," said McConnell. "With the addition of Ketaki and Ann, our executive leadership team brings exactly the combination of AI product depth and enterprise go-to-market experience we need to scale what market insights represent, and execute on the opportunities ahead."

Rao, who comes to the role with a background in AI and data, offered context on why the data layer itself matters. "What drew me to Crunchbase is that the hardest problem in AI is the data," said Rao. "Crunchbase has built a proprietary foundation that no one else has. Market insights is what happens when you combine that data depth with AI and fundamentally change how people understand private markets, so they can find and act on opportunities faster than ever before."

The 2026 product roadmap

Crunchbase outlined several additions planned for the remainder of 2026. According to the company, the roadmap includes Model Context Protocol (MCP) connectors, a model-estimated current valuation signal, and expanded data coverage - including revenue and headcount data - as well as broader startup coverage globally.

The MCP connector work is particularly relevant to how enterprise software buyers are beginning to integrate AI agents into their workflows. MCP, the open protocol developed by Anthropic, has been gaining traction as a standard for connecting AI agents to data sources and tools. PPC Land has tracked the emergence of MCP in advertising and marketing technology as enterprise buyers move to standardize agentic access to data platforms.

Why this matters for marketing and GTM teams

For marketing professionals and go-to-market teams, the practical significance lies in how competitive and sector-level intelligence currently gets assembled. Most practitioners working at B2B companies either rely on broad industry labels that imprecisely define their market, or invest significant manual effort to build sector views from individual company signals. The friction is real and well-documented.

Crunchbase's release sits at the intersection of two trends that PPC Land has covered closely in 2026: the surge in enterprise investment in AI-powered sales and marketing tools, and the shift from historical data to predictive and forward-looking intelligence. According to Crunchbase data cited by PPC Land in May 2026, companies in the sales, marketing, and CRM category raised around $3.7 billion globally in seed-through-growth-stage funding in early 2026 alone - an indication of how much enterprise capital is flowing toward this problem.

The competitive intelligence component has particular relevance for account-based marketing practitioners. Identifying which companies compete with a target account - and understanding the nature of that competition - is a foundational input for messaging, positioning, and outreach prioritization. The addition of plain-language reasoning means teams can use competitor data without independently verifying each pairing.

The broader significance for B2B data users also connects to how Crunchbase data gets activated in the market. PPC Land reported in November 2025 that Bombora launched Curated Ecosystem Audiences with Crunchbase as one of the initial data partners, enabling marketers to activate Crunchbase's private company intelligence as addressable audiences across programmatic and social channels. As the underlying Crunchbase data becomes more granular through micro-industries, that activation layer gains precision as well.

"Modern companies rarely fit neatly into a single category anymore, which makes traditional market intelligence increasingly limiting," said Ketaki Rao, Chief Product Officer at Crunchbase. "New sectors form faster, competition shifts constantly, and traditional industry classifications cannot keep up. These market insights give teams a way to understand how markets are actually evolving in real time, so they can identify opportunities earlier and make decisions with far more precision."

The Market Insights signal itself addresses a structural limitation in how sector-level intelligence has traditionally been consumed. Funding rounds and exits are the most widely tracked indicators of market health, but they are lagging - they confirm where a market was rather than where it is heading. A company that closes a funding round today signaled growth many months ago. Crunchbase's directional indicator is intended to move that signal earlier in the information chain.

Timeline

  • 2007 - Crunchbase founded by Michael Arrington as a database supplementary to TechCrunch
  • Early 2025 - Crunchbase launches predictive intelligence platform, combining nearly 20 years of startup data with real-time signals from over 80 million users
  • October 30, 2025 - Bombora launches Curated Ecosystem Audiences with Crunchbase as an initial data partner, translating Crunchbase private company intelligence into programmatic ad audiences
  • Q3 and Q4 2025 - Crunchbase closes its two largest deals in company history
  • January 28, 2026 - Crunchbase is reported as victim of a cyberattack by the group ShinyHunters, who claimed to have stolen more than 2 million records
  • Q1 2026 - Crunchbase reports 900% year-over-year ACV growth for its Predictions and Insights product
  • May 8, 2026 - Crunchbase data on sales and marketing startup funding cited by PPC Land, showing $3.7 billion raised globally in the category in early 2026
  • May 2026 - Anduril Industries announces a $5 billion funding round, which Crunchbase had flagged as likely more than a month earlier
  • April 2026 - Blue Energy announces a $380 million round, which Crunchbase had predicted eight months prior
  • June 2, 2026 - Crunchbase announces Market Insights, comprising 5,100+ micro-industries, updated competitor intelligence with 88.7% overall accuracy, and the Market Insights directional signal; Ketaki Rao joins as CPO, Ann Davis promoted to CRO
  • Later in 2026 (planned) - Market Insights signal availability in Crunchbase Business; MCP connectors; model-estimated current valuation signal; expanded revenue, headcount, and global startup coverage

Summary

Who: Crunchbase, a San Francisco-based private company intelligence platform founded in 2007, announced Market Insights. The launch was made by Jager McConnell, CEO; Monika Abraham, Staff Product Manager; and Ketaki Rao, incoming Chief Product Officer.

What: A three-part product suite comprising micro-industries (a segmentation layer of 5,100+ granular market categories derived from 2.7 million companies and 13.2 million mapped products), an updated competitor intelligence model (delivering 90% precision on top-three competitors and 88.7% overall list accuracy) with plain-language competitive reasoning, and a Market Insights signal that classifies market segments as emerging, growing, or declining. The launch coincided with the appointments of Ketaki Rao as CPO and Ann Davis as CRO.

When: Announced June 2, 2026.

Where: Crunchbase is headquartered in San Francisco, California. Micro-industries and updated competitor data are available immediately in Crunchbase Business and the Predictions and Insights API package. The Market Insights signal is currently available in the API only, with Crunchbase Business availability planned later in 2026.

Why: Crunchbase says traditional industry classifications are too broad to support high-stakes commercial and investment decisions. The company reports that go-to-market teams and investors still manually aggregate fragmented signals to form sector-level views. The commercial rationale is reinforced by strong product momentum - 900% year-over-year ACV growth in Q1 2026 - and by a 2026 roadmap that includes MCP connectors and model-estimated valuation signals, positioning Crunchbase to serve the expanding enterprise market for AI-powered private market intelligence.