Many analysts and small fintechs spend hours scrubbing scattered financial data. This offers low-cost curated financial datasets plus $50 on-demand scraping and clean CSV/JSON delivery to eliminate that work and speed prototyping.
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Automated access to curated financial datasets + on-demand scraping targets a $9.0B = 300,000 financial & fintech organizations x $30K ACV (spend on financial data, feeds, and analytics) total addressable market with medium saturation and a year-over-year growth rate of 12-20% = growing spend on alternative & cleaned datasets and automation in finance.
Key trends driving demand: Alternative-data demand -- buy-side and quant teams increasingly use non-traditional datasets to gain edge, driving demand for curated, clean inputs.; AI-assisted ETL -- LLMs and programmatic scraping reduce time to extract and normalize messy financial pages, lowering delivery cost and improving accuracy.; Shift to pay-as-you-go data -- smaller firms prefer micro-payments and single-dataset purchases over expensive annual feeds.; Democratization of finance tooling -- more indie fintechs and researchers need low-cost, ready-to-use datasets to prototype models quickly..
Key competitors include Nasdaq Data Link (formerly Quandl), Alpha Vantage, Bright Data (formerly Luminati) / Bright Data Services, Zyte (formerly Scrapinghub), Kaggle / Public Dataset Workarounds.
Analysis, scores, and revenue estimates are for educational purposes only and are based on AI models. Actual results may vary depending on execution and market conditions.
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