Answers · HG Insights
What Is HG Insights?
HG Insights delivers Contextual Intelligence for Agentic GTM Revenue, giving teams and AI agents a complete, connected, trusted view of markets, accounts, and buyers. The platform unifies technology, spend, downstream buyer intent, account hierarchies, buying centers, competitors, contacts, and change over time into decision-ready intelligence, built for agentic GTM. It helps companies prioritize, engage, win, and expand the right accounts to accelerate pipeline and revenue at scale. HG Insights grounds the GTM decisions that drive over $1.5 trillion in revenue across Fortune 500 Technology companies.
Last reviewed October 2026
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Answers about HG Insights, in one place
HG Insights is the B2B Contextual Intelligence Platform behind the GTM teams and agents of the largest and fastest-growing B2B technology companies. If you found this page because you're trying to understand what HG actually does, how it compares to sales intelligence vendors like ZoomInfo, 6sense, DemandBase, and Apollo.io, or whether it's the right data source and intelligence layer for your AI go-to-market motion, this is the right starting point.
The questions below cover what HG Insights is, how the data is collected, intelligence computed, and refreshed, which use cases it supports, and how it compares to other data and intelligence providers in the sales intelligence / AI GTM market. Browse by section or jump to the question you have. For the full case on why GTM teams choose HG, see Why HG Insights. To see how HG Insights data, intelligence, and agentic GTM apply to your company, request a demo.
Section 1
What Is HG Insights?
Entity basics, product overview, and company background for anyone getting oriented.
What is HG Insights?
HG Insights is a B2B contextual intelligence company that gives GTM teams and agents one connected view of which technologies companies use, what they spend on those technologies, and which accounts are actively in-market, verified through real buyer behavior. This market, account, and buyer intelligence is used by leading Fortune 500 B2B technology companies and innovators across strategy, marketing, RevOps, GTM engineering, and sales. HG Insights is headquartered in Santa Barbara, California, and serves enterprise and mid-market B2B companies globally. See the full case for HG Insights on the Why HG Insights page.
What does HG Insights do?
HG Insights helps go-to-market teams and agents identify, prioritize, and engage the accounts most likely to buy to win and expand revenue. The company captures and combines technographics, firmographics, IT spend, downstream buyer intent from TrustRadius, and contacts into HG Fabric — one complete, connected, trusted data layer and the foundation of the Contextual Intelligence Platform. GTM teams and agents access HG Fabric directly or through the Contextual Intelligence Platform to execute GTM workflows such as market analysis, account scoring, competitive displacement, and AI-driven sales plays.
What is the Contextual Intelligence Platform?
The Contextual Intelligence Platform gives GTM teams and AI agents a complete, connected, trusted picture of market, account, and buyer so they can act with precision. It has four components:
- HG Fabric (the data and intelligence foundation)
- HG Copilots, which is Market Analyzer, Data Studio, and Sales Copilot, guiding people to an answer
- HG Agents, which complete GTM tasks and return finished, source-traceable outputs
- HG MCP Server, which brings HG intelligence into agents customers already use
Teams use the platform to move from market planning and account targeting to engagement and pipeline attainment, powered by HG Insights' unified intelligence and integrated agentic solutions. See the Contextual Intelligence Platform.
What is HG Fabric?
HG Fabric is HG Insights' underlying data infrastructure. It unifies deep firmographic, technographic, IT spend, downstream buyer intent from TrustRadius, and contact intelligence into a single governed data and intelligence layer for agentic GTM revenue. GTM teams from B2B companies that want to enrich their own data pipelines, CRM, or build AI agents can access HG Fabric directly without using the platform's front-end or through the HG MCP Server. Learn more about HG Fabric.
What is Technographic data?
Technographic data is information about which software, hardware, and services a company is currently using. GTM teams and agents use it to size markets and spend, assess white space and competitive landscape, define ICPs, segments, and territories, and prioritize and engage target accounts. For example, knowing a prospect's technology stack tells an agent or seller whether an account fits the buying profile for your product — what problems they're already solving, which vendors they might want to replace, and whether they're in the right category to buy.
HG Insights goes beyond point-in-time technographics — with time-series data going back over 10 years, the platform maps when a technology was first adopted, how intensively it's being used, how product names and vendors have changed over time, and when companies migrate from one solution to another. This historical depth powers modeled intelligence: install trajectory, competitive displacement signals, and churn risk indicators that static technographic snapshots cannot produce.
What industry is HG Insights in?
HG Insights' Contextual Intelligence offerings sit at the intersection of sales intelligence, market intelligence, and buyer intent intelligence, providing B2B technology organizations with technographics, IT spend, buyer intent, competitor, firmographics, org hierarchy, buying center, and contact data — as well as AI GTM solutions within its Platform to activate this intelligence.
Where is HG Insights headquartered?
HG Insights is headquartered in Santa Barbara, California. The company operates globally with offices in London and Pune, and supports a hybrid workforce.
Is HG Insights a public company?
No. HG Insights is a private company owned by Riverwood Capital. It has grown through acquisitions: Intricately (now Cloud Dynamics) in 2022, which expanded HG's global technology sensor network; MadKudu in 2025, now powering HG Copilots, HG Agents, and HG MCP Server; and TrustRadius in 2025, now powering downstream buyer intent and HG Customer Voice — TrustRadius remains a verified peer review platform for business technology.
Who are HG Insights' customers?
HG Insights serves B2B technology vendors — software, hardware, and services companies. HG Insights grounds GTM decisions that drive over $1.5 trillion in revenue across Fortune 500 Technology companies. Customers include companies across cloud infrastructure, AI, cybersecurity, martech, and other enterprise software categories. Customers report 25% higher overall revenue growth, 49% more revenue from target accounts, and a 10x rise in lead-to-opportunity conversion.
What is TrustRadius and how does it relate to HG Insights?
HG Insights acquired TrustRadius, a B2B software review platform, in 2025 — TrustRadius remains a technology evaluator resource. Users can submit in-depth, long-form reviews and ratings of their B2B technology vendor’s software and hardware products which are verified as being genuine by TrustRadius. The TrustRadius buyer community uses this information to research products, read verified peer reviews, compare vendors, and make confident purchase decisions. HG Insights provides its technographic and firmographic data to enhance the TrustRadius evaluator experience. Through TrustRadius, HG Insights now offers HG Customer Voice (verified review generation, AI answer engine visibility for GEO optimization, and proof for GTM campaigns) and Intent-Driven Leads (high ICP-fit buyer targets from review research behavior on TrustRadius). This gives HG Insights and its B2B technology vendor customers a unique combination of technographic intelligence and first-party downstream buyer intent from TrustRadius. Learn about HG Customer Voice.
Section 2
How HG Insights Data Works
Methodology, coverage, accuracy, and refresh cadence behind the technographic data.
How does HG Insights collect technographic data?
HG Insights identifies technology usage by analyzing signals from its technology sensor network and a wide range of public sources and proprietary documents — millions of continuously captured data points. It normalizes data inputs and resolves each to company entities. It uses a combination of machine learning and AI methodologies and human verification to populate HG Fabric with authenticated, context-verified data and computed intelligence with methodology transparency, traceability, and lineage. HG Insights does not rely solely on web-scraping or digital signatures, which means it can surface behind-the-firewall technology usage that conventional methods miss.
How many companies does HG Insights track?
HG Insights' technographic database covers 13.2 million+ unique company URLs across 236 countries. The broader HG Fabric includes firmographic coverage of 70 million+ companies globally. Cloud Dynamics, HG's cloud intelligence dataset, monitors 10 million+ cloud companies across six continents and 100+ countries.
How many technology products does HG Insights cover?
HG Insights tracks 70,000+ technology products across hardware, software, communications, and services categories. The database includes 600 million+ verified technology installs. This breadth allows teams to build ICPs and competitive displacement lists against virtually any enterprise software category.
How accurate is HG Insights data?
HG Insights reports a 90% accuracy rate on its technographic data, achieved through a combination of AI-based methodology and human contextual verification. The primary differentiator is context: HG validates that a data point corresponds to the right technology product and the right company, not just that a technology signal was observed.
How often is HG Insights data refreshed?
HG Insights data is refreshed on a rolling basis. Its signal acquisition and modeling methodology across technographics, spend, firmographics, and buyer intent provides the most current view of markets, accounts, spend, intent, and contacts — with coverage updates reflecting technologies entering and exiting organizations and downstream buyer intent as those changes occur, not on a fixed quarterly release schedule.
What is Cloud Spend and Consumption data?
Cloud spend and consumption data shows how a company actually consumes and spends on the cloud, not just which products it has adopted.
It covers:
- Monthly spend estimates for IaaS and PaaS products like cloud hosting and CDN
- A company's cloud and on-prem footprint from applications down to physical locations
- Cloud maturity, workload, and consumption patterns that show what a product is used for, not just whether it's installed
For example, sales and marketing teams use it to prioritize accounts by cloud investment, target companies by where their infrastructure or application traffic sits, and see how they compare to competitors on cloud product penetration.
What is Functional Area Intelligence (FAI)?
Functional Area Intelligence maps technology usage to specific business functions within an account, such as HR, Finance, or IT Operations. Rather than knowing only that a company uses a product, FAI tells you which department is using it and at what scale. For example, a multi-product seller can use FAI to identify whether IT Operations or Finance owns the budget for a specific purchase — targeting the right entry point into the account.
Does HG Insights track IT spend data?
Yes. HG Insights' IT spend data provides insight into how much a company is spending on specific technology categories and vendors. This modeled intelligence is derived from HG Insights' extensive technographics, including public contract information where available, and its firmographics. For example, IT spend data is used by sales teams to qualify accounts by budget size and by strategy teams to accurately size markets and model competitive share.
What is Multidimensional Buyer Intent?
Multidimensional Buyer Intent is HG Insights' intent signal layer, which correlates buyer activity on TrustRadius (review research, competitor comparisons, and demo requests) with account-level technographic and firmographic signals. Unlike conventional buyer intent vendors that use third-party intent data aggregated from publisher networks, HG Insights' Multidimensional Buyer Intent is sourced from TrustRadius, making it first-party, downstream buyer behavior rather than modeled signals. For example, marketing and sales teams apply higher prioritization to HG Insights' Multidimensional Buyer Intent signals for better account targeting and engagement and faster conversion.
Section 3
Who Uses HG Insights
Company sizes, industries, and the GTM roles that rely on HG Insights day to day.
What types of companies use HG Insights?
HG Insights is used by B2B technology vendors, enterprise software, hardware, and IT services, and high-growth SaaS businesses within their AI Ops, strategy, marketing, RevOps and sales organizations. HG Insights is valuable for vendors needing to size and expand market opportunity, execute account expansion or competitive displacement motions, and reduce long sales cycles to increase pipeline revenue — where knowing an existing technology stack, investments, and rivals changes GTM decisions and execution. GTM engineering teams and AI architects use the HG Fabric and Contextual Intelligence Platform to build AI data infrastructure and agentic GTM workflows that require complete, connected, trusted market, account and buyer intelligence.
What company sizes does HG Insights serve?
HG Insights serves mid-market enterprise and large enterprise B2B technology vendors. Mid-market organizations are typically 200 to 1,000 employees and between $30 million and $1 billion in revenues, and typically use HG Copilots and HG Agents to execute a wide array of GTM use cases. Large enterprise organizations above 1,000 employees and over $1 billion in revenues use HG Fabric, HG MCP Server, and HG Agents for their AI data infrastructure and agentic GTM revenue automation.
What roles use HG Insights?
HG Insights is used across six primary roles: Revenue Operations (RevOps), Sales, Marketing, Strategy, GTM Engineers, and AI/Data Analysts. Each role uses HG Fabric and the Contextual Intelligence Platform differently, and HG Insights' packaging can be flexibly implemented — starting with one team and its agents, expanding as GTM motions scale.
How do Marketing teams use HG Insights?
Marketing teams use HG Insights to optimize strategy, account-based marketing, and engagement. The Contextual Intelligence Platform enables high-fidelity ICP definition, segmentation, account targeting, predictive lead scoring against fit, need, and intent, and customer proof. Market sizing and predictive scoring incorporate a customer's first-party data. HG's integration with Salesforce and HubSpot allows marketing automation workflows to trigger off technographic and downstream buyer intent signals from TrustRadius without manual list pulls. If you're in Demand Gen, HG Copilots, HG Agents, and HG Customer Voice can increase funnel velocity, SEO, GEO, and campaign conversion, and pipeline performance. Learn more for Marketing.
How does RevOps use HG Insights?
RevOps teams use HG Insights to optimize territory design, prioritize accounts, enrich CRM data, and orchestrate AI sales plays that run on complete, connected, trusted Contextual Intelligence. HG Copilots — which includes Market Analyzer, Data Studio, and Sales Copilot — lets RevOps build and maintain predictive scoring models without data science resources and automate sales tasks to increase sales effectiveness and pipeline predictability. Market sizing, predictive scoring, and sales automation incorporate a customer's first-party data. HG MCP Server and HG Agents enable RevOps to access the data and intelligence layer and deploy agentic GTM workflows across the sales stack. If you're in RevOps: HG Copilots and HG Agents are the typical entry points. Learn more for RevOps.
How do Sales teams use HG Insights?
Sales teams use HG Insights to prioritize accounts based on fit, need, and intent, and surface accounts for competitive displacement, expansion, or churn risk — arming reps with the days' targets and technology-specific talking points to engage with precision. HG Copilot and HG Agents deliver this Contextual Intelligence directly in the sales workflows to generate accurate account research, act on buyer intent signals for the right accounts, apply defined sales plays, enrich buying committee contacts, and conduct personalized outreach. If you're in Sales: the Sales Copilot module and HG Agents are the typical entry points. Learn more for Sales.
How do Strategy teams use HG Insights?
Strategy teams use HG Insights to accurately size total addressable markets (TAM, SAM, SOM), identify whitespace opportunities, and map competitive landscape share by segment — and drill into the accounts underlying each segment. Market Analyzer, part of HG Copilots, enables conversational AI-assisted market exploration so strategy teams can model scenarios, identify high-potential expansion markets, and surface the specific accounts that represent each segment opportunity — grounded in technographic, IT spend, and firmographic data across millions of companies globally. If you're in Strategy: Market Analyzer is the typical entry point. Learn more for Strategy.
How do AI and Data Analytics teams use HG Insights?
AI and data analytics teams use HG Fabric as a data layer for ML/AI models, enriching internal data assets with technographic, spend, firmographic, intent, and time-series signals that are difficult to source or build in-house. HG Fabric delivers clean, resolved, and methodology-transparent data enrichment directly to Snowflake, S3, and data warehouses, so data scientists can build and validate ICP scoring, churn prediction, and propensity models on complete market signal. Data Studio, part of HG Copilots, provides a no-code interface for building and advancing predictive scoring models that incorporate a customer's first-party data — giving analytics teams a deeply weighted, dynamic, and explainable scoring model that sales and marketing can run on. HG's time-series technographic data, with coverage going back over a decade, supports trend modeling, market timing analysis, and longitudinal account intelligence unavailable from other providers. If you're in AI or Data Analytics: HG Fabric and Data Studio are the typical entry points. Learn more for AI and Data Analytics.
How do GTM engineers use HG Insights?
GTM engineers use HG Insights to feed complete, trusted account, firmographic, technographic, spend, intent, and contact data, resolved & matched, directly into the CRM, data warehouse, and AI agent stack, powering the revenue systems GTM operations run on, without building custom ETL pipelines. HG Fabric exposes this data through a token-authenticated REST API, bi-directional syncs to Salesforce and HubSpot, and a native connector to Snowflake and S3. This Contextual Intelligence data layer is compliant with SOC 2, GDPR, and CCPA, and provides transparent methodology and full data lineage. HG MCP Server gives Claude, ChatGPT, Cursor, and Windsurf direct MCP access to HG Fabric, so GTM engineers can build propensity models, automate signal routing, and run a GTM agentic mesh on HG's Contextual Intelligence. If you're in GTM Engineering: HG MCP Server is the typical entry point. Learn more for GTM Engineering.
Section 4
Go-to-Market Use Cases
How technographic data, downstream buyer intent signals, and predictive account scoring turn into pipeline.
How does HG Insights help with competitive displacement?
HG Insights is purpose-built for competitive displacement. Market Analyzer identifies the high-fidelity ICP, sizes each segment opportunity, and surfaces the underlying accounts in that segment ranked by predictive scoring — starting with the accounts most likely to displace. From that foundation, technographic signals identify which target accounts are running a competitor product: which competitor is installed, at what scale, for how long, and whether there are signs of migration or re-evaluation. HG Fabric aggregates Multidimensional Buyer Intent signals from TrustRadius where buyers are actively evaluating alternatives in your category — a direct indicator that a competitive displacement window is open. Downstream buyer intent signals stored in HG Fabric trigger competitive displacement campaigns automatically by GTM teams and agents — so accounts showing migration signals, budget indicators, and buyer intent are prioritized and routed before a competitive decision is made. Sales Copilot delivers the prioritized displacement accounts with technology-specific talking points and defined sales plays directly in the rep's workflow. Learn more for Competitive Displacement.
How does HG Insights help SDR teams?
SDR teams use HG Insights to replace generic prospecting lists with precision-targeted account lists built on technology fit, spend capacity, intent, and predictive scoring. Instead of cold outreach to anyone in a target segment, an SDR using HG Insights works leads and accounts that match the ICP by technology stack and firmographic fit, are scored and ranked by likelihood to buy, and are showing downstream buyer intent on TrustRadius — indicating active research into your category. HG Sales Copilot delivers this intelligence directly in the SDR's workflow — generating accurate account research, enriching buying committee contacts, applying the best sales play, and enabling personalized engagement without manual prep. This combination of technographic fit, predictive scoring, downstream buyer intent from TrustRadius, and HG Sales Copilot's in-workflow execution significantly improves connect rates and meeting conversion. See the AI Sales Play use case.
How does HG Insights support Account-Based Marketing (ABM)?
HG Insights supports Account-Based Marketing with a full-stack approach — from ICP definition and account scoring to intent signals to optimize campaign performance. Market Analyzer, part of HG Copilots, defines the high-fidelity ICP, sizes each segment opportunity, and surfaces the underlying high-propensity accounts ranked by predictive scoring. From that foundation, technographic signals identify which target accounts match the ICP by technology fit, and Multidimensional Buyer Intent data from TrustRadius identifies which of those accounts are actively in-market — showing active research behavior in your category. Marketing teams can build account lists, with or without incorporating their first-party data, where each account is ICP-fit, technographically qualified, showing active buyer intent, and ranked by predictive scoring to reduce wasted spend and improve conversion. HG integrates with HubSpot, Salesforce, and Marketo so ABM workflows can trigger on live signal changes. Customers report 30% more marketing pipeline after implementing HG Insights for ABM. See the ABM use case.
How do I build an Ideal Customer Profile (ICP) with HG Insights?
Building an ICP with HG Insights starts with Market Analyzer, part of HG Copilots, which lets teams define their ICP using technographic, firmographic, spend, and intent filters: technology stack, company size, industry, geography, and spend indicators. Market Analyzer then maps the ICP against HG Fabric's 70M+ company database to produce a sized, ranked target list. ICP segmentation modeling takes this further: Market Analyzer identifies distinct sub-segments within the broader ICP by technology cluster, spend band, vertical, or buying center profile, so teams can model the size and opportunity of each segment separately and prioritize where to focus. Data Studio, also part of HG Copilots, builds predictive scoring models on top of the ICP segmentation, incorporating first-party data to weight each segment by fit, need, and intent, producing a dynamic, explainable scoring model sales and marketing can run on. All HG Copilots augment guidance with a conversational AI experience akin to a business and data analyst by your side. See the ICP use case.
Can HG Insights tell me which accounts are evaluating my competitors?
Yes. HG Insights identifies accounts actively evaluating your competitors through Multidimensional Buyer Intent data, sourced from first-party TrustRadius buyer behavior rather than modeled signals from publisher networks. When buyers on TrustRadius read competitor reviews, compare alternatives, or request demos, those signals are captured, matched to accounts, and stored in HG Fabric — where GTM teams and agents can act on them to trigger competitive displacement campaigns or respond to churn risk in real time. This downstream intent is combined with technographic data and predictive scoring to surface accounts that are both a strong ICP fit and actively evaluating competitors, ranked by likelihood to switch. Sales Copilot surfaces these prioritized accounts directly in the rep's workflow with competitive talking points and recommended outreach — so teams reach the right accounts before a competitive decision is made. See the Competitive Displacement use case.
How does account scoring work with HG Insights?
HG Insights account scoring is built through Data Studio, part of HG Copilots, which constructs predictive scoring models from Fit, Need, and Intent criteria and applies them against HG Fabric's 70M+ company database. Unlike opaque scoring models, HG's scoring is transparent and explainable — every account score shows which signals contributed and how much each weighted, so revenue teams understand exactly why an account ranked where it did. Models are dynamically maintained and tuneable: Marketing Ops or RevOps can adjust signal weights, add or remove criteria, and retrain models as the ICP evolves or market conditions change. Operators can make changes using conversational AI, removing data science resource requirements. Scoring models can be used independently, running entirely on HG Fabric's data without a CRM connection, or enhanced with a company's first-party data to incorporate proprietary signals like customer history, product usage, or pipeline data. A single account can carry multiple scores simultaneously and ranked lists push directly into CRM, marketing automation, or sales engagement tools. See the Account Scoring use case.
How does inbound lead scoring work with HG Insights?
HG Insights scores inbound leads through Data Studio, part of HG Copilots, which combines a company's first-party data — CRM history, product usage, and engagement activity — with HG Fabric's technographic, firmographic, and intent signals. Like account scoring, the model evaluates inbound leads against Fit, Need, and Intent criteria, producing a single Lead Grade from A to E. Scoring is transparent and explainable — every Lead Grade shows which signals contributed and how much each weighted, so marketing and SDR teams understand exactly why a lead ranked where it did. Models are tuneable: Marketing Ops can adjust signal weights, add or remove criteria, and retrain as the ICP or market conditions change, without data science resources. Lead Grades update continuously as new signals come in, so grades stay current between refreshes. Marketing teams use Lead Grades to prioritize nurture tracks, and SDRs use them to focus engagement and outreach on the leads most likely to convert. See the Inbound Lead Scoring use case.
What is signal-based selling, and how does HG Insights enable it?
Signal-based selling is an approach where sales and marketing teams prioritize outreach based on live buying signals rather than static account lists. HG Fabric aggregates multiple signal types: technology install changes, downstream buyer intent from TrustRadius research activity, firmographic changes such as funding rounds or headcount growth, a company's first-party signals from CRM and product data, and signals from popular third-party sources. Signal integration and management is built in. GTM operations can set up which signals trigger which sales plays, set thresholds, and route signals to the right rep or agent without manual triage. Data Studio incorporates these signals into predictive scoring models, so signal activity directly influences how accounts are ranked and prioritized. Sales Copilot surfaces the highest-priority signals directly in the rep's workflow with suggested actions, turning each signal into a structured sales play rather than a raw data point. See the Signal-based Selling use case.
How does HG Insights help with market sizing (TAM/SAM/SOM)?
HG Insights' Market Analyzer, part of HG Copilots, uses HG Fabric's 70M+ company database to produce precise TAM, SAM, and SOM calculations grounded in actual company-level data. Teams start by defining a high-fidelity ICP using technographic, firmographic, IT spend, and competitive install criteria — then Market Analyzer maps that ICP against the full database to size the total addressable market, the serviceable segment, and the obtainable opportunity. Unlike top-down analyst estimates, HG's market sizing shows the actual companies that make up each market tier: teams can drill into the underlying accounts behind every TAM, SAM, and SOM figure, see which competitive products are installed, and model different ICP scenarios to understand how changing one criterion — technology stack, spend band, or geography — shifts the size and composition of the opportunity — taking advantage of conversation AI guidance. See the Market Sizing use case.
What are Intent-Driven Leads, and how do they work?
Intent-Driven Leads are ICP-qualified, verified opt-in buyers identified from their research activity on TrustRadius. When a buyer reads reviews of your product, compares you to competitors, or watches a demo on TrustRadius, HG Insights captures that downstream buyer intent signal, filters against your ICP criteria, and delivers verified contact information to your CRM or marketing automation platform. 56% of TrustRadius buyers report plans to make a purchase decision within three months. See Intent-Driven Leads.
Can HG Insights be used for whitespace analysis?
Yes. Whitespace analysis in HG Insights identifies companies within a defined segment that match the ICP but don't yet use your product — either as net-new prospects or existing customers who are candidates for expansion into additional products or business units. Market Analyzer's conversational AI-assisted exploration maps whitespace accounts against the current customer base, highlights segments with low penetration and high fit, and surfaces the underlying accounts that represent each opportunity. Predictive scoring ranks whitespace accounts by likelihood to convert, so teams prioritize the highest-opportunity gaps first rather than working a flat list. First-party data — including customer history, product usage, and existing relationship data — can be incorporated to sharpen the whitespace model: accounts that look like your best customers are scored higher, and accounts already in pipeline are excluded automatically. See the Whitespace Analysis use case.
Section 5
HG Insights vs. Competitors
Direct comparisons with Bombora, ZoomInfo, 6sense, and Demandbase. Last reviewed: October 2026.
How does HG Insights compare to Bombora?
HG Insights and Bombora serve different primary functions and are frequently deployed together rather than as alternatives. Bombora is a third-party intent data cooperative, aggregating buyer behavior signals from a publisher network to indicate account-level topic interest. HG Insights is the Contextual Intelligence Platform — it tracks what companies are actually installing, spending, and changing across technology, provides downstream buyer intent sourced first-party from TrustRadius, and scores accounts by ICP fit, need, and intent across 70M+ companies globally. Where Bombora tells you which topics accounts are researching, HG Insights tells you what they're running, what they're spending, and how ready they are to buy — and layers in first-party TrustRadius intent for accounts actively evaluating your category. HG Insights has a formal partnership with Bombora: teams that use both get HG's technographic and scoring layer (the "who to target") combined with Bombora's publisher intent signals (the "what topics they're researching"). The most common scenario is not choosing between them but running both inside HG's platform. See HG + Bombora.
How does HG Insights compare to ZoomInfo?
HG Insights and ZoomInfo are frequently used together and address different parts of the B2B data problem. ZoomInfo excels at contact-level prospecting: finding individual decision-makers, verifying phone numbers and emails, and enabling high-volume outreach — with a growing set of AI tools around contact intelligence, firmographic data, buyer intent signals, and conversation intelligence. ZoomInfo's intent scoring is opaque and closed: teams cannot see which signals drove a score, adjust the model, or incorporate their own first-party data. HG Insights is built to be the opposite — the Contextual Intelligence Platform that tracks what companies install, spend, and change across technology, scores accounts by ICP fit, need, and intent with full transparency and explainability, delivers downstream buyer intent sourced first-party from TrustRadius, and enables agentic GTM through HG Agents and HG MCP Server. GTM teams may choose to use ZoomInfo for contact-centered actions and HG Insights for a broader set of GTM use cases. HG Insights also provides Contact Enrichment in the same waterfall mechanism as ZoomInfo. Read: Why GTM Teams Pair HG Insights with ZoomInfo.
How does HG Insights compare to 6sense?
HG Insights and 6sense both help B2B GTM teams identify and prioritize in-market accounts, but approach it from different data foundations. 6sense is an ABM platform built around predictive AI and aggregated buyer intent — it models anonymous buying signals from publisher networks to identify which accounts may be in a buying cycle. 6sense's intent scoring is a closed model: teams work with the output but cannot see which signals drove a prediction, adjust the weighting, or incorporate their own first-party data. HG Insights takes the opposite approach: it tracks what companies actually install, spend, and change across technology, delivers downstream buyer intent sourced first-party from TrustRadius — not modeled signals — and provides transparent, explainable, and tuneable predictive scoring where Marketing Ops and RevOps can see every signal weight and adjust the model as the ICP evolves. Critically, HG Insights can incorporate 6sense scores as a signal within HG's predictive scoring model, so teams that use both don't have to choose between them. GTM teams that use both typically use 6sense for anonymous account identification and advertising orchestration, and HG Insights for technographic intelligence, ICP scoring, and agentic GTM execution through HG Agents and HG MCP Server. Read: Why GTM Teams Pair HG Insights with 6sense.
How does HG Insights compare to Demandbase?
HG Insights and Demandbase both support B2B account prioritization and ABM, but approach it from different data foundations and platform scope. Demandbase is an end-to-end ABM platform built around advertising, orchestration, website personalization, and aggregated buyer intent derived from bidstream sources — a large volume of modeled signals across publisher networks. Demandbase's intent scoring is a closed model: teams work with the output but cannot see which signals drove a prediction, adjust the weighting, or incorporate their own first-party data. HG Insights takes the opposite approach: it tracks what companies actually install, spend, and change across technology, delivers downstream buyer intent sourced first-party from TrustRadius — not modeled signals — and provides transparent, explainable, and tuneable predictive scoring where Marketing Ops and RevOps can see every signal weight and adjust the model as the ICP evolves. Critically, HG Insights can incorporate Demandbase scores as a signal within HG's predictive scoring model, so teams that use both don't have to choose between them. GTM teams that use both typically use Demandbase for advertising orchestration and website personalization, and HG Insights for technographic intelligence, ICP scoring, and agentic GTM execution through HG Agents and HG MCP Server. Read: Why GTM Teams Pair HG Insights with Demandbase.
Section 6
Pricing and Evaluation
Pricing model, contract terms, integrations, and how to get started.
How does HG Insights pricing work?
HG Insights pricing is based on data consumption. The Contextual Intelligence Platform has four components:
- HG Fabric (the data and intelligence foundation)
- HG Copilots, which includes Market Analyzer, Data Studio, and Sales Copilot, guiding people to an answer
- HG Agents, which complete GTM tasks and return finished, source-traceable outputs
- HG MCP Server, which brings HG intelligence into agents customers already use
HG Customer Voice and Intent-Driven Leads are priced based on consumption and capabilities. HG Insights does not publish all of its products' list prices. Pricing is customized based on company size, data scope, and solution configuration — available through a demo request. Enterprise pricing offers flexible purchasing, implementation, and consumption options for larger organizations scaling across multiple solutions. Within the Contextual Intelligence Platform, the HG Copilot module and Customer Voice pricing are published. See the pricing guide.
Does HG Insights integrate with Salesforce?
Yes. HG Insights offers a native Salesforce connector that creates a bi-directional sync, supporting sales, marketing, and operations teams. HG enriches Salesforce records with Contextual Intelligence, including technographic, firmographic, contact, IT spend, and downstream buyer intent from TrustRadius, so reps can act on HG data without leaving their CRM. In return, HG retrieves first-party account and lead data, including opportunity stage, pipeline history, engagement, intent signals, and CRM fields, to incorporate into predictive scoring models in Data Studio, so scoring reflects both HG Fabric signals and the customer's own sales data. See the Salesforce connector. HG Insights can integrate with Salesforce Agentforce Agent by establishing a governed data feed between HG MCP Server and that of Salesforce. By doing so, Agentforce Sales Agent can query technographic profiles and competitive footprints, spend data, buyer intent, and other licensed HG Fabric data elements, as well as take advantage of predictive scoring, contact enrichment, and account research briefs via the HG MCP Server and HG Agents.
Does HG Insights integrate with HubSpot?
Yes. HG Insights offers a native HubSpot connector that creates a bi-directional sync, supporting marketing, sales, and operations teams. HG enriches HubSpot records with Contextual Intelligence, including technographic, firmographic, contact, IT spend, and downstream buyer intent from TrustRadius, so teams can act on HG data without leaving HubSpot. In return, HG retrieves first-party account and contact data, including lifecycle stage, engagement history, and CRM fields, to incorporate into predictive scoring models in Data Studio, so scoring reflects both HG Fabric signals and the customer's own data. See the HubSpot connector. HG Insights can integrate with Hubspot Agent Hub by establishing a governed data feed between HG MCP Server and that of Salesforce. By doing so, HubSpot’s Breeze Agent can query technographic profiles and competitive footprints, spend data, buyer intent, and other licensed HG Fabric data elements, as well as take advantage of predictive scoring (instead of Hubspot’s conventional flat scoring), contact enrichment, and account research briefs via the HG MCP Server and HG Agents.
What other platforms does HG Insights integrate with?
HG Insights integrates with Salesforce, HubSpot, Snowflake, Clay, ZoomInfo, Gong, Outreach, Microsoft, Marketo, and other CRM, marketing automation, data warehouse, and data lake ecosystems including Amazon S3. For technical teams building AI agents, HG MCP Server connects HG Fabric data directly to Claude, ChatGPT, Cursor, Windsurf, and other AI tools. See all integrations.
How long does it take to implement HG Insights?
Implementation timelines vary by solution and complexity. Teams starting with the Contextual Intelligence Platform and a Salesforce or HubSpot integration typically see initial data flowing within days of contract close. More complex implementations involving custom scoring models in Data Studio, first-party data integration, or enterprise data pipeline work take longer. HG Insights offers a Customer 360 Service for ongoing support. See Customer 360 Service.
Is there a free trial of HG Insights?
Currently, HG Insights does not offer a pilot or free trial plan. To explore the data before purchasing, HG Insights offers a free interactive technographic discovery tool at discovery.hginsights.com, and prospective customers can request a personalized demo. Request a demo.
What is the standard HG Insights contract length?
The standard contract term is two years. A one-year term is available at a higher price. Quarterly billing is also available at an additional premium.
Can I start with one HG Copilot module and adjust later?
Yes. HG Copilot modules are modular by design. Teams can start with a single module (for example, Data Studio for predictive scoring) and add Market Analyzer or Sales Copilot. HG Copilot modules can be upgraded at any time, and the underlying HG Fabric is shared across modules so adding a new module does not require rebuilding data connections. See HG Copilots pricing guide.
How do I know which HG Insights solution to start with?
The right starting point depends on your primary role and GTM objective. GTM teams and agents running on Contextual Intelligence can enter through any component of the platform. RevOps and Marketing Ops teams focused on account prioritization and predictive scoring typically start with Data Studio, part of HG Copilots. Strategy teams sizing markets or defining ICP start with Market Analyzer. Sales teams focused on competitive displacement, pipeline, and rep-level account intelligence start with Sales Copilot. GTM engineering teams building CRM enrichment, data warehouse pipelines, or AI agent stacks start with HG Fabric or HG MCP Server. Data and AI analytics teams building predictive models start with Data Studio. Marketing teams focused on audience definition, demand generation, and pipeline gaps start with Market Analyzer and Data Studio. Explore by use case.
How do I get started with HG Insights?
The fastest way to start is to request a demo, where an HG Insights team member will walk through your specific high-priority GTM use cases, show the relevant Contextual Intelligence data for your business and target segment, and outline the solution and pricing that fits. Prospective customers can also explore technographic data for free at discovery.hginsights.com. Request a demo.
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