Production guides for dynamic pricing systems, OTA integrations, occupancy forecasting, and rule-based pricing workflows in travel & hospitality.
Revenue Management is a production-focused engineering resource for the people who build and operate hotel pricing systems: revenue managers, hospitality technology developers, data analysts, and Python automation engineers.
It trades marketing fluff for implementation detail. Every article ships explicit data flows, idempotency boundaries, retry semantics, fault-tolerant routing, and runnable Python that survives real OTA payloads — the kind of material you actually reach for when you are mapping rate codes between Expedia and your PMS, taming a flapping Booking.com webhook, or tuning decay coefficients in a weighted occupancy model.
The library spans 51 in-depth articles organized into four connected areas, each moving from problem framing to architecture to runnable code to the operational guardrails that keep a pricing pipeline accurate under pressure.
| Area | What it covers |
|---|---|
| Core Architecture & Pricing Taxonomy | Deterministic frameworks for rate plans, channel-manager integration, seasonality, tax & fee resolution, and security boundaries across hospitality pricing stacks. |
| Data Ingestion & OTA API Integration | Async ingestion for OTA APIs, webhook-vs-REST sync, pagination, rate limits and retries, competitor-rate scraping, and schema-contract data quality. |
| Occupancy Forecasting & Demand Analytics | Weighted booking models, event-driven adjustments, lead-time and cancellation forecasting, pace & pickup analysis, and price-elasticity tuning. |
| Dynamic Pricing Rule Engines & Optimization | Deterministic rule engines, yield optimization, promotional orchestration, and low-latency rate-recommendation serving. |
- Runnable, not hand-wavy. Python examples come with type hints, structured logging, and explicit error handling — copy them into a service, not a slide.
- Operations-first. Circuit breakers, dead-letter queues, idempotency keys, drift detection, and observability thresholds are treated as first-class, not afterthoughts.
- Hospitality-specific. RevPAR, rate parity, length-of-stay optimization, overbooking limits, and tax-inclusive vs tax-exclusive math — the real problems of hotel revenue systems.
- Tightly cross-linked. Articles reference each other the way the systems they describe reference each other, so you can follow a signal from forecast to guarded published rate.
- Eleventy static site generator, authored in Markdown.
- Hand-authored inline SVG diagrams, KaTeX for revenue formulas, and Prism-highlighted code blocks.
- Accessible (WCAG 2 AA), fast (100/100 mobile performance), and theme-aware.
- Deployed on Cloudflare Pages.
npm install
npm run serve # local dev server with live reload
npm run build # production build into _site/Issues and pull requests that improve accuracy, add production detail, or fix errors are welcome. Please keep the house style: concrete, runnable, and operations-aware.