technographics

theirstack/technographics is a Technographics & Tech Stacks data product published on TheirStack and indexed by The Alternative Data Encyclopedia.

Which of 33k technologies each company runs, inferred from what they hire for. One row per company and technology with confidence score, number of postings mentioning it and first/last-seen dates; technologies catalog and companies file included.

The field grew out of the sales-intelligence market — BuiltWith began profiling web technologies in 2007 and vendors like Datanyze followed — and funds adopted it after 2015 as a way to track cloud migrations, security spend and vendor churn. Technology-adoption change is now a standard ingredient in software and IT-services equity research.

The publisher is covered in its own article: TheirStack.

The signal

Detection of technology stacks per company: which technologies each business uses, with evidence and date of observation, plus adoption-change events.

Stack changes flag investment, migrations and vendor churn before they surface in revenue or surveys. Rows typically map a company to a technology, a detection method (DNS, certificate, pixel, job ad) and a first/last-seen date. The derived layer adds adoption and abandonment events.

The datasets behind this category's featured listing — job-postings, technographics, buying-intents — each have their own article on this encyclopedia.

Data characteristics and access

License: Commercial license. Size: 52M technology signals · 33k technologies · 13M companies. Delivery: API, S3, Snowflake, Parquet. History: 2021 — present. Refresh: Daily.

Vendors combine several collection techniques: crawling public web assets and partner badges, scanning DNS records and TLS certificates, and reading hiring signals from job postings. Each detection carries a confidence score and a timestamp, and change-detection pipelines compare successive snapshots to emit adoption and abandonment events rather than raw states.

Caveats and compliance

Detection coverage is uneven across stacks; web-only signals miss back-office software. History depth matters because change events, not stock levels, drive most of the alpha.

Signals are derived from public web artifacts and job ads, so personal-data exposure is low. Buyers should still check scraping terms of service and ensure job-posting text is stripped of applicant names before use.

Who uses this signal

Software equity analysts, GTM teams and VC read stack changes as churn, migration and investment signals.

Complementary signals

This kind of signal pairs naturally with adjacent categories of the encyclopedia:

Further reading

About the provider

Data company that builds and licenses investment-grade datasets from public signals: job postings, technology adoption and social activity.