Financial Data Collection

Financial data is the quantitative backbone of competitive intelligence. For public companies, SEC filings provide audited revenue, margins, headcount, and segment breakdowns. For private companies, the data landscape is sparser — funding announcements, revenue estimates from analyst firms, and financial signals derived from hiring patterns, office expansions, and technology spend. Building a financial data collection system requires different approaches for public and private companies, unified under a common schema that enables comparison.

1. Public Company Pipeline EDGAR RSS feeds for SEC filings. Earnings transcript APIs for quarterly call data. Financial data APIs for standardized metrics. The public company pipeline is well-defined because the data is structured and legally required. Automate completely.
2. Private Company Pipeline Crunchbase or PitchBook for funding data. Revenue estimation models based on hiring velocity, web traffic, and technology spend. Press releases and news coverage for ad hoc financial signals. The private company pipeline is inherently uncertain — assign appropriate confidence levels to every estimate.
3. Unified Financial Schema Both pipelines feed into a common schema: company identifier, metric type, value, currency, period, source, confidence level. This enables cross-comparison between public and private competitors despite the difference in data quality. The confidence level is critical — it prevents treating a private company revenue estimate with the same trust as a 10-K filing.