IT Spend
Modeled technology budgets at the company and category level
What is it
IT Spend provides a bottom-up, forward-looking 12-month budget estimate of how much companies will spend on IT across 140 categories spanning hardware, software, services, and telecom.
This includes both absolute spend (one company's own budget) and relative spend (spend redistributed across a corporate hierarchy so it can be totaled safely across any group of companies), enabling account-level qualification and market sizing.
What problem it solves
Every GTM organization needs a credible view of technology spend, as it’s the dollar lens behind the decisions that shape growth: which markets to enter, where to invest, how to balance territories, and how much opportunity remains.
Most companies attempt to create that view by stitching together spend estimates from internal assumptions, manual analysis, broad market reports, revenue and employee-count proxies, installed technologies, and historical performance. The result is often difficult to validate, too broad to segment in the ways the business needs, and disconnected from the accounts teams need to act on.
HG Insights IT Spend gives GTM teams a more precise, actionable foundation for market sizing, territory planning, account prioritization, and wallet-share analysis—so the numbers used in strategic planning can also guide field execution.
Understanding the three spend models
IT Spend Intelligence comes in three distinct models. Each answers a different question, and picking the right one depends on what you're trying to find out.
Absolute spend
A modeled dollar estimate of what a single company spends annually on a technology category (cloud, software, infrastructure, services, and so on). It rolls up the company's own spend plus any subsidiaries under it, but not its parent.
- Sizing the opportunity at one account: “How big is their cloud budget?”
- Qualifying accounts by spending power
- Prioritizing targets by budget magnitude
- Understanding total addressable spend inside one account, subsidiaries included
- Adding budgets across multiple companies. Subsidiary spend is already rolled into the parent's number, so summing Absolute Spend across a group double-counts it. Use Relative Spend instead.
- Historical trend analysis. It's a forward-looking, point-in-time estimate, not a time series.
- Precise contract values. It's modeled, not invoice data.
Relative spend
A dollar-value spend figure with subsidiary spend already divided back out. Where Absolute Spend rolls a parent and its subsidiaries into one number, Relative Spend distributes that spend across the group, so you can total it across any collection of companies without double-counting.
- Market sizing: total addressable spend across a territory, industry, or custom segment (for example, all SAP banking clients in the UK)
- Aggregating spend across any group of companies you define
- Category-level sizing (total storage spend in your territory)
- Segmenting a market by country, industry, or any other cut, since the totals stay accurate at any level
- Stating one company's actual budget. That's Absolute Spend. Relative Spend is a proxy built for grouping, not a standalone claim about what one company spends.
- Peer benchmarking or over/under-spend comparisons. Relative Spend isn't an index against peers.
- Qualifying a single account. Use Absolute Spend.
AI spend
A specialized model estimating spending specifically on AI and machine learning technologies, separate from the general IT spend categories.
- Understanding AI investment levels at target accounts
- Separating AI-forward companies from AI laggards
- Targeting AI-adjacent solutions: MLOps, AI infrastructure, data platforms
- Gauging AI maturity and commitment
- General IT budget sizing. Use Absolute Spend.
- Peer comparison on AI. There is no Relative AI spend yet.
- Understanding which AI tools a company uses. That's Technographics.
| “How much does this one company spend on cloud?” | Absolute spend |
| “What's the total addressable spend across my territory or segment?” | Relative spend |
| “Are they making big AI investments?” | AI spend |
| “Which accounts have the biggest IT budgets?” | Absolute spend |
| “Which companies show high legacy infrastructure spend?” | Absolute spend (category breakdown) |
| “Who should I target for my MLOps platform?” | AI spend |
What you can do with it
- Market Sizing: Size your TAM, SAM, and SOM using category-level technology spend
- Territory Planning & Balancing: Allocate coverage and set equitable territories based on spend potential
- Account Prioritization: Focus sales and marketing on accounts with the greatest budget opportunity
- Wallet Share Analysis: See your share of an account’s category spend—and the whitespace remaining
Real-world example
Cloud Migration Targeting
A cloud services provider wants to find companies with significant on-prem infrastructure spend who haven't migrated. Using IT Spend along with technographics, they identify companies spending $10M+ on data center infrastructure. These are prime migration targets with proven budget and clear modernization opportunity.
Example Data
Salesforce IT Spend (from firmographic data)
“Salesforce spends $4.1B/year on IT (9.9% of revenue), which is above the software industry average. With ~$1.6B in cloud spend alone, they're a prime target for cloud optimization, FinOps, and observability tools. Their high IT spend per employee ($49K) indicates they're tech-forward and willing to invest in productivity tools.”
See the full data dictionary
Business impact
Increases: More accurate deal qualification
Increases: Higher ASP from better pricing precision
Increases: More marketing budget focused on accounts with proven category spend
Decreases: Less rep time on accounts that can’t afford the solution
Directional outcomes HG customers commonly report. Actual results vary by program and data application.
Under the hood
How it's unique to the market
What's unique about HG Insights' IT Spend is that it delivers company-level spend estimates built from the bottom up, not top-down market abstractions.
Analyst firms publish broad TAM numbers (e.g., "storage in Europe will grow 12%"), but those figures cannot be easily segmented by country, industry, revenue band, or technology footprint — and they provide no visibility into the actual companies that make up the market.
HG's model works in the opposite direction. By starting with individual companies and their actual technology environments, IT Spend can represent highly specific segments, such as a particular industry in a specific country with a defined infrastructure profile. Users can then drill directly from a market view into the exact companies that comprise it, enabling both strategy and execution to operate from the same data.
Competitors like ZoomInfo and 6sense do not provide market-level spend models or account-level forecasts, so teams must rely on analyst data for strategy and separate datasets for execution. This creates misalignment. HG resolves that gap by providing a single dataset used by strategy, operations, and execution teams — ensuring a shared view of markets and the accounts within them.
How it's derived
Three interconnected data pillars
Macroeconomic & Supply/Demand Data
- GDP metrics: Growth rates, services sector contribution across 87 countries
- Vendor financials: Revenue tracking from 400+ leading IT vendors
- Industry analysis: Sector-specific performance across 22 industries mapped to NAICS
Proprietary HG Datasets
- Technographic data: 100M+ technology installations across 25,000+ products
- Contract intelligence: 35,000+ IT service contracts identifying outsource spending patterns
- Deployment trends: Year-over-year changes in technology adoption by cohort
Consensus-Based Forecasting
- Third-party validation: Alignment with Gartner, IDC, and Forrester market projections
- Industry surveys: IT spending intentions and budget allocation data
- Expert insights: Key opinion leader perspectives on market trajectories
The result: By triangulating these data sources, HG creates spending projections that are both directionally accurate at the market level (aligning with top-down analyst views) and granular at the account level (reflecting individual company characteristics).
Five pillars of underlying research
Every spend projection is built on extensive, multi-dimensional data analysis.
Economic Analysis
- GDP growth metrics across 87 countries
- Services sector contribution to economy
- Country-specific economic indicators
- Regional IT spending trends
- Currency and inflation adjustments
Vendor Financials
- 400+ leading IT vendors tracked
- 5-year historical revenue analysis
- Product line revenue breakdowns
- Granular alignment to taxonomy nodes
- Supply-side market validation
Industry Analysis
- 22 industries mapped to NAICS codes
- Industry-specific IT spending behaviors
- Performance relative to GDP
- Sector growth trajectories
- Vertical-specific technology adoption
Technographic Data
- 100M+ installation detections
- 20,000+ software products tracked
- 200+ product categories
- Deployment trends by cohort
- Year-over-year adoption changes
Contract Intelligence
- 35,000+ IT service contracts
- Mapped to 65+ service sub-classes
- Outsource spending patterns
- GSI and regional SI relationships
- Contract value estimations
Data integration
These five pillars work together to create a comprehensive view of IT spending:
- 1.Economic context sets baseline expectations
- 2.Vendor data validates market size
- 3.Industry analysis refines cohort behaviors
- 4.Technographic signals show adoption patterns
- 5.Contract data grounds outsource spending
Validation & accuracy
HG works with 95% of Fortune 500 tech companies who have validated the spend model. Their consistent feedback: HG's spend projections are accurate within ±6% at the account, subsidiary, and market levels.