Five connected levels
Navigate consistently from Industry to Sub Industry, Category, Market, and Company instead of relying on a single coarse classification.
04 / Shared market intelligence
SoftwareIQ maps companies through a common Industry, Sub Industry, Category, and Market hierarchy, then carries those definitions into every dataset and research workflow. Benchmarks are one expression of that shared market layer.
The SoftwareIQ difference
Generic third-party classifications are too broad for software research. SoftwareIQ maintains a versioned hierarchy from Industry to Company so every observation can be compared at the same market level.
Navigate consistently from Industry to Sub Industry, Category, Market, and Company instead of relying on a single coarse classification.
Resolve public and private companies to the markets they actually serve, with governed identity, ownership, and coverage records.
Use the same market definition across Operating KPIs, Job Postings, Developer Signals, and Market Benchmarks.
Move from a market view into underlying company evidence without silently changing the category or peer-set definition.
Market structure · Common taxonomy
Which companies actually belong together—and at what level of the market?
The SoftwareIQ hierarchy connects broad industries to focused end markets and their underlying companies. Researchers can compare Infrastructure Software with Application Software, study a category such as Data Platforms, or resolve the analysis to Operational Databases without rebuilding the cohort.
Those definitions persist when the view changes. A market selected in the map remains the same market in operating, hiring, developer, valuation, and company-level research.
A lightweight view of the hierarchy used throughout SoftwareIQ
One taxonomy application · Index performance
Is a company move idiosyncratic, or part of a broader software-market change?
SoftwareIQ indices compare the broad Software industry with Application Software, Infrastructure Software, and Vertical Software sub-industries, using both capitalization-weighted and equal-weighted views. The chart makes concentration effects and sub-industry divergence visible across the same period.
Index constituents inherit the maintained SoftwareIQ mapping, connecting return comparisons to the exact hierarchy used throughout company and alternative-data research.
Five-year chart rebased to 100
| Index | YTD | 1M | 1Y | 3Y CAGR | 5Y CAGR |
|---|---|---|---|---|---|
| Software | 7.3% | -2.5% | 4% | 9.8% | 2.3% |
| Application | -0.4% | -0.6% | -1.5% | 1.9% | -5.9% |
| Infrastructure | 33.2% | -2.4% | 31.8% | 20.6% | 7.7% |
| Vertical | -14.3% | -6.4% | -21.2% | 4.8% | 4.6% |
One taxonomy application · Valuation context
How does today’s software valuation compare with its own history?
A current EV/revenue observation becomes more useful beside the historical SoftwareIQ index and cross-sectional median. The exhibit preserves the distinction between an aggregate index measure and the median company experience.
The same governed universe supports both the price-performance and valuation histories, reducing the cohort drift that can make market comparisons look more precise than they are.
Five-year index and cross-sectional median history
| Benchmark | Current | 1Y avg. | 3Y avg. | 5Y avg. | 10Y avg. |
|---|---|---|---|---|---|
| Software index | 7.7x | 7.8x | 8.7x | 8.4x | 7.5x |
| Software median | 4.4x | 4.2x | 5.6x | 6.2x | 6.7x |
Shared research infrastructure
The taxonomy is maintained as a common data layer, not recreated independently for each dataset or chart.
Maintain company identity, ownership status, business model, and research coverage in a governed universe.
Map each company through Industry, Sub Industry, Category, and Market using versioned definitions.
Attach Operating KPIs, Job Postings, Developer Signals, and Market Benchmarks to that shared structure.
Research workflows
A shared taxonomy keeps top-down context connected to bottom-up evidence across SoftwareIQ.
Compare operating KPIs and management guidance within stable market and category cohorts.
Read job postings, partner trends, and developer activity against the same company and market mappings.
Translate the governed universe into market maps, return indices, historical multiples, and transaction context.
Distinguish a company-specific change from a category, market, or sub-industry movement without cohort drift.
One connected research system