Traditional IT spend benchmarks are built on national averages or generic industry reports. They lack the resolution to support precise market sizing or account-level analysis.
This segment closes the gap by aligning directly with your taxonomies — country, sector, and sizeband — to deliver explainable, confidence-scored IT spend and growth benchmarks. Results can scale from market sizing to CRM enrichment.
Aligns your inputs (country, sector, sizeband) to your taxonomy.
Enriches with IT spend and growth metrics at segment level.
Provides last 12 months, next 12 months, and 3-year CAGR.
Confidence scores reflect data freshness, source coverage, and estimation method.
Outputs designed for Market Sizing, with CRM enrichment optional.
This segment is activated with a blend of trusted sources and your own inputs
AI reasoning
User Input
Web intelligence
Average IT spend per organization (EUR).
Growth rates: last 12m, next 12m, 3-year CAGR.
ISO country codes for clean dataset joins.
Confidence scores for all enriched fields.
Compatible with other Starzdata segments (e.g., headcount, digital intensity).
Explainable, segment-level IT benchmarks you can compare and trust.
Your questions on this segment, answered
Your questions on this segment, answered
How fast can results be delivered?
Platform mode: minutes to hours. Project mode: ~72h for tailored delivery.
How reliable are the metrics?
Each has a confidence score (0–100) based on data freshness, source coverage, and estimation method.
What growth horizons are provided?
Last 12 months, next 12 months, and 3-year CAGR.
Are the spend values averages?
Yes, values are average IT spend per organization in the segment.
How often is the data updated?
Update frequency is configurable by the client; data_as_of anchors the baseline.
How does this compare to Gartner, IDC, or consulting reports?
Analyst and consulting reports (e.g., Gartner, IDC, McKinsey) are valuable for directional insights but typically provide national or broad sector averages, often refreshed annually. Starzdata segments are different: they align to your own taxonomies (country × sector × sizeband), refresh on your chosen frequency, and return confidence-scored metrics ready to plug into models or CRM workflows.
{ "_meta": { "dictionaryColumns": ["Variable", "Data_Type", "Sample_Value", "Description"] }, "data": [ { "Variable": "country", "Description": "Human-readable country name", "Business_Rules": "VARCHAR; must match client-provided list.", "Source_System": "Client Data", "Data_Type": "VARCHAR", "Sample_Value": "France" }, { "Variable": "country_iso_code", "Description": "ISO 3166-1 alpha-2 code for country", "Business_Rules": "Derived from country input; optional for joins.", "Source_System": "Web+AI Reasoning", "Data_Type": "CHAR", "Sample_Value": "FR" }, { "Variable": "sizeband", "Description": "Human-readable sizeband label (revenue or headcount)", "Business_Rules": "VARCHAR; client-defined ranges and basis.", "Source_System": "Client Data", "Data_Type": "VARCHAR", "Sample_Value": "Medium 250–999 employees" }, { "Variable": "sector", "Description": "Human-readable sector label", "Business_Rules": "VARCHAR; client-defined taxonomy.", "Source_System": "Client Data", "Data_Type": "VARCHAR", "Sample_Value": "Software & IT Services" }, { "Variable": "it_spend_per_org_eur", "Description": "Average annual IT spend per organization (EUR)", "Business_Rules": "INTEGER ≥ 0; excludes consulting one-offs if specified by client.", "Source_System": "Web+AI Reasoning", "Data_Type": "INTEGER", "Sample_Value": "1250000" }, { "Variable": "it_spend_growth_l12m_pct", "Description": "Growth of average IT spend over last 12 months (%)", "Business_Rules": "DECIMAL between -50 and 50; signed percentage points.", "Source_System": "Web+AI Reasoning", "Data_Type": "DECIMAL", "Sample_Value": "3.2" }, { "Variable": "it_spend_growth_n12m_pct", "Description": "Projected growth of average IT spend next 12 months (%)", "Business_Rules": "DECIMAL between -50 and 50; signed percentage points.", "Source_System": "Web+AI Reasoning", "Data_Type": "DECIMAL", "Sample_Value": "4.1" }, { "Variable": "it_spend_cagr_n3y_pct", "Description": "Projected 3-year CAGR of average IT spend (%)", "Business_Rules": "DECIMAL between -50 and 50; compounded annual rate.", "Source_System": "Web+AI Reasoning", "Data_Type": "DECIMAL", "Sample_Value": "5.0" }, { "Variable": "data_as_of", "Description": "Reference date for L12M baseline and projections", "Business_Rules": "DATE; determines window for L12M and forecast anchors.", "Source_System": "Client Data", "Data_Type": "DATE", "Sample_Value": "2025-06-30" } ] }
