Executive Summary

Many product and growth teams struggle to get reliable retention and cohort metrics because their event exports live in CSVs and are analyzed ad hoc in spreadsheets or one-off notebooks, producing slow, non-reproducible insights for teams without a full data stack. This pain is acute at small-to-medium businesses and early-stage product teams that cannot justify a $50k+ analytics stack but still need fast, actionable retention dashboards. You could build a lightweight Python-first SaaS that ingests CSVs, runs reproducible transformation scripts (notebooks or modular Python code), and automatically generates scheduled, production-ready retention/cohort dashboards and exports. The product would emphasize templates for common retention analyses, easy scheduling on serverless infra, and a developer-friendly deployment path for analysts. The market looks attractive right now: roughly a $6.0B addressable market (2M businesses × $3K ACV), with macro trends favoring product-led growth and Python-first analytics, and internal scoring of 88/100 market and 86/100 revenue potential. Many customers are actively seeking cheaper, faster ways to measure retention without building a data warehouse. You can differentiate by being code-native (not just a GUI) and optimizing for CSV-first teams, offering reproducibility, auditability, and low operational costs via managed serverless compute. The main challenges are high competition from BI vendors and open-source tools, so early traction will require razor-sharp UX for analysts, clear templates, and a focused go-to-market to SMB growth teams.

Market Opportunity

Automate retention dashboards from CSVs using Python scripts targets a $6.0B = 2M businesses × $3K ACV total addressable market with high saturation and a year-over-year growth rate of 12% YoY — product analytics and BI market growth (industry analyst summaries, 2024).

Key trends driving demand: Shift to product-led growth — product and growth teams increasingly rely on retention and cohort metrics to prioritize work, creating demand for fast-retention tooling.; Rise of Python-first analytics — more analytics teams prefer Python notebooks and reproducible code, enabling a product that combines code + dashboarding to fit workflows.; Serverless compute and managed infra reduce cost of running transformation pipelines — this lowers operational barriers to shipping a small analytics SaaS.; CSV and export-first workflows remain common for e-commerce and marketing platforms that lack modern event instrumentation — an opportunity to serve a large underserved segment..

Key competitors include Amplitude, Mixpanel, Mode Analytics, Metabase.

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Automate retention dashboards from CSVs using Python scripts

Executive Summary

Market Validation

Market Opportunity

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