Enterprise SaaS Demand Signals

See which enterprise software vendors are gaining, retaining, or potentially losing enterprise demand share before it shows up in earnings.

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30+
Public Tickers Tracked
1m+
Monthly Job Postings
Since 2020
Historical Coverage
T+2
Signal Delivery

What we track

Job Postings Precede Procurement Decisions.

When companies hire for roles requiring Snowflake, Datadog, or CrowdStrike, those mentions are procurement signals for the named vendor, not just hiring signals for the company posting the job.

EarlySigns structures those signals into daily, point-in-time data covering 30+ publicly traded enterprise software tickers and 30+ private company names, surfacing new customer relationships, churn risk, and share shift before they appear in earnings.

Revenue trend nowcasting

Track aggregate vendor mention counts across all job postings over time. Rising counts signal expanding customer demand; declining counts signal contraction. Use signal inflection points in the weeks before a covered ticker reports to build or adjust positions.

Net new logo detection

Identify when a company begins requiring a specific technology product in job postings. First appearance of Snowflake, Datadog, or CrowdStrike in a company's job descriptions signals a likely new customer relationship, often months before the vendor discloses it in earnings.

Churn signal

Detect when a previously active company stops posting roles requiring a specific vendor. Using the AT_RISK status on a company surfaces potential contract loss before it surfaces in revenue figures.

Share shift analysis

Track QoQ and YoY momentum across competing vendors in the same category. Compare Datadog vs Dynatrace vs New Relic in observability, or CrowdStrike vs Palo Alto Networks vs Zscaler in cybersecurity, across the same company universe over time.

Coverage

What the data covers.

30+ publicly traded enterprise software tickers, including Snowflake, Datadog, CrowdStrike, and MongoDB, plus 30+ pre-IPO and private names including Databricks, Supabase, and Wiz.

  • DevOps & DevTools CI/CD, containers, artifact management, and incident response.
  • Data & Analytics Data warehouses, streaming pipelines, search, and NoSQL databases.
  • Cybersecurity Endpoint protection, identity, cloud security, and application security testing.
  • Observability Infrastructure monitoring, APM, and log management.
  • Cloud Infra CDN, cloud platforms, and developer deployment tooling.
Why it's different

Traditional workforce data answers 'is this company hiring?' EarlySigns answers 'who are Snowflake's customers, how many new ones did they add, and who churned?'

Time series Daily since 2020, backtestable
Signal outputs NEW, ACTIVE, GROWING, DECLINING, AT RISK, INACTIVE
Vendor coverage 30+ public tickers + pre-IPO names
Geo coverage US, CA, UK
Built for fundamental L/S, central data teams & quant funds

FAQ

Common questions.

What makes EarlySigns different from workforce data providers?
Traditional workforce data answers "is this company hiring?" EarlySigns answers a different question entirely — "who are Snowflake's customers, how many new ones did they add, and who churned?" The unit of analysis is the vendor being mentioned, not the company doing the hiring.
How is the data delivered and how frequently?
Data is delivered daily via S3 bucket file drop at T+2. The schema includes ticker symbols, NAICS codes, company size, revenue range, funding stage, and geographic fields — structured for straightforward ingestion into existing research and modeling pipelines. A dashboard is also available for fundamental analysts.
What is the historical coverage and is it backtest ready?
The full dataset is available from January 2020 in a point-in-time format with daily snapshots, no lookahead bias, and no revision to historical records. It is backtest ready out of the box.
How is the underlying job posting data licensed?
EarlySigns sources job posting data exclusively from licensed commercial data providers. All source data is used in accordance with applicable terms. Derived signals are delivered as aggregated, vendor-level outputs rather than raw job posting content. Compliance documentation and DDQ materials are available upon request.
How do you handle data quality and company name normalization?
Raw job postings contain inconsistent and noisy employer name strings. EarlySigns runs a normalization pipeline that maps employer names to canonical entities, enriched with firmographic metadata including ticker symbols, NAICS codes, company size, and funding stage. This ensures signals are accurately attributed before delivery and eliminates double-counting across sources.

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Ready to see the signals others miss?

Sample data available on request. Full historical dataset backfilled to January 2020.

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