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Datadog SaaS Expansion Scenario Model

SQL Status Data

Stack: PostgreSQL · SQL (CTEs, Window Functions) · Financial Modeling
Data: Real Datadog FY2025 public financials
Author: Oleksandra Hordieieva Built: April 2026


What this project does

Models how Datadog's geographic expansion into EMEA and APAC markets impacts ARR, churn, NRR, LTV/CAC, and unit economics. Three scenarios are compared over a 24-month horizon using verified FY2025 financial data as the baseline.


Datadog FY2025 baseline (verified public data)

Metric Value Source
Full-year revenue $3,427M (+28% YoY) Q4 FY2025 Earnings, Feb 10 2026
Q4 revenue $953M Q4 FY2025 Earnings
Customers > $100K ARR 4,310 Dec 31, 2025
Customers > $1M ARR 603 Dec 31, 2025
GAAP gross margin 80.0% FY2025
Free cash flow $915M FY2025

Source: Datadog Q4 FY2025 Earnings Release


Three scenarios modeled

Scenario ARR Growth Year 1 New Markets Investment
Base (core only) 20% None
EMEA Expansion ~23% EMEA_NEW ~$80M
Aggressive ~27% EMEA_NEW + APAC ~$180M

SQL techniques used

  • MRR / ARR by market — with LAG() window function for MoM growth rate
  • MRR Waterfall — monthly revenue bridge using CASE WHEN pivot
  • Cohort Retention — NRR analysis with AGE() and integer month indexing
  • Gross Churn Rate — monthly and annualized, with LEFT JOIN on churn events
  • LTV / CAC — by customer segment and market, with CAC payback period
  • Scenario Comparison — three-scenario ARR engine via scenario_revenue table
  • Expansion ROI — incremental ARR vs investment cost per market

Repository structure

data_model/

File Description
01_schema.sql Relational schema — 8 tables with relationships
02_seed_data.sql Reference data + verified modeling assumptions

sql_queries/

File Description
01_mrr_arr.sql MRR and ARR by market with MoM growth
02_mrr_waterfall.sql Monthly MRR movement bridge
03_cohort_retention.sql Revenue cohort NRR analysis
04_churn_rate.sql Gross churn rate monthly and annualized
05_ltv_cac.sql LTV / CAC by segment and market
06_scenario_comparison.sql Three-scenario ARR comparison
07_expansion_roi.sql Expansion investment ROI

docs/

File Description
assumptions_and_sources.md All data sources and modeling assumptions

Key business insight

New markets structurally start with lower NRR (~95% in year 1) due to higher churn, GDPR compliance overhead, and weaker local support coverage. The model shows that if expansion-market NRR crosses 100% by month 18, the investment becomes self-funding. Datadog's $915M FCF in FY2025 confirms the company can sustain ~$180M expansion spend without impairing cash generation.


Data sources

About

SaaS Expansion Scenario Model using real Datadog FY2025 data. SQL + Financial Modeling.

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