/awesome-billing

💰 Billing & Payments Knowledge for Cloud Platforms

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💰 Awesome Billing and Payments Awesome

In a Stanford class on Cloud computing overview, the software architecture is described as in the right diagram:

This knowledge base cover the first of the far perimeter of the cloud stack. It is one of the pillar of the cloud ecosystem, where customers, products and business meets. The other pillar being Identity and Access Management (IAM) 👤.

Contents

Basics

Pricing

From monthly subscription to commodity-like on-the-go consumption, and including shopping-cart like funnel, there's plenty of scheme out there to structure your product's pricing.

Usage-based Pricing

The default, dynamic scheme for cloud resources.

  • Why I Love Usage-Based Pricing - “The most important reason I like this pricing model is that it heavily incentivizes both the customer and the service provider to act in everyone's best interest.” Also details issues with other pricing models.
  • Socially Optimal Pricing of Cloud Computing Resources - “The socially optimal operating point is unique, and can be sustained by a linear, usage-based tariff, which charges a fixed price per unit resource and unit time.” This paper justify of usage-based pricing for cloud resources.
  • “Billing is not complex on purpose: it's the price to pay for elasticity.” (source) - Or why you're likely to get an endless stream of complaining users if choosing utility pricing scheme: while accurate to the (milli-)cent, this model is frustrating for customers not ready to invest time grasping the underlaying concepts.
  • Riemann sum - The starting point about quantization of usage.
  • Allen's interval algebra - Implementing usage-based pricing is tricky, and this algebra will help you organize temporal reasoning. Also see this Stack Overflow question with clean schema.
  • Reconcile Your Monthly GCP Invoice with BigQuery Billing Export - Behind the quest of this developer to track its expenses, you get a glimpse on cloud billing difficulties. While not explicitly pointed out, pricing cloud resources is hard and the result of quantization, granularity and rounding, between space, time and currencies.
  • AWS EC2 T2 Instances Demystified: Don't Learn The Hard Way - An example of really tricky burstable instances which accrues and limits its own amount of CPU usage credits.

Subscription Plans

Highly popular for SaaS businesses, subscription plans are easy to comprehend.

  • f-license - Open-source license key generation and verification tool in Go.

Hybrid

Uncommon pricing schemes.

  • The Three Part Tariff - Beyond linear pricing, there is a place for an additional platform fee and free-tier component in the pricing structure.
  • Google Ads API: BillingCap enum - Capped actuals: monthly with rollover, an optimized pricing scheme to limit surprises from customers, in which we more or less sell quotas.

Strategy

Theory and practical insight to help you choose the right price point.

Product Catalog

The central repository of all available services, products, variants, options and pricing available to the customer to purchase.

Calculator

Simulate a virtual invoice depending on the resource you plan to use.

Cost Forecast

Help your customers predict their upcoming and future consumption based on their past usage.

Marketplace

A marketplace connect supply with demand that lead to a financial transaction. If there is no payment involved, then it is an aggregator, or a hub. Not a marketplace.

Cloud Resources

This sub-section focus on bid/ask mechanism matching resource producer with consumers. Most of the time these are one-sided markets with the big platform trying to amortized under-utilized inventory.

Online Ads

Targeted online advertisements marketplaces have a lot in common with traditional cloud marketplace. Some good inspiration there, from concepts to tech

Accounting

Coupons and Vouchers

Taxes

Invoice

The invoice materialize a consumed service or purchased product, waiting to be settled by a payment transaction.

Payments

Receipt

A receipt materialize the payment transaction.

Credit Cards

The most popular payment device.

Bank Accounts

The old-fashioned way of payment: by the way of banks.

Online Payments

The usual money transfer services.

  • The untold story of Stripe - In which we learn that “once turnover hit a certain level, Paypal automatically put the business on a 21 to 60 day rolling reserve, meaning that up to 30 per cent of a company's revenue could be locked up for up to two months.”

Fraud

There's monetary incentives to exploit your business. Be prepared to fight hordes of fraudsters and shady users.

Cards

The majority of fraud is exploiting the most common popular payment device: credit cards.

Trust Score

Synthetic score based on a collection of signals are often the best proxy of user's trustworthiness. Customer support most of the time rely on them to take action when these actions are not triggered automatically.

Statistics

Best tools to automate fraud detection.

Billing

UX/UI

Users gets easily angry when it comes to money. UX and UI might helps a lot to reduce frustration.

Business Intelligence

As stakeholder of the billing pipeline, you sat on all the critical data to measure and report on the health of the business.

Metrics

Definition and collection of Key Performance Indicators (KPIs) worth monitoring.

Data Engineering

To industrialize data production and consumption, your need data engineers to clean up, persist and consolidate data. Only after you get these data foundation you might think of onboarding data scientists.

  • AI vs Data Science vs Data Engineering - “Data Engineers build data pipelines and infrastructure to ensure a constant availability of transformed data. Data Scientists analyze and build models from these data to develop new product features or drive the bottom line of the business.” As for AI professionals, their focus is on cognitive automation.
  • Ten Ways Your Data Project is Going to Fail - You don't need data scientists. “For ETL, hire data engineers. For reporting, hire BI analysts. The end.”
  • Cargo cult data science - “Data science is best viewed as a form of company culture, rather than a set of technologies. However, many firms will try to create that company culture by acquiring data-science technology, rather than working on their culture.”
  • Why not use Double or Float to represent currency? - Because of precision: floats and doubles cannot accurately represent the base 10 multiples that we use for money.
  • Never Use Floats for Money - “This is precisely the problem we have when trying to represent 10^-1, or 0.1 in binary. There is not an exact binary representation of 0.1 or 0.01.”
  • European Spreadsheet Risks Interest Group - Horror Stories - A collection of cases in which uncontrolled and untested spreadsheet models led to lost revenue, mispricing, poor decision making, fraud and systemic financial failure.

Tools

  • Practical Business Python - A blog collecting and spreading ideas on how to use Python more effectively in the business setting.
  • redash - Connect and query your data sources, build dashboards to visualize data and share them with your company.
  • Metabase - Metabase is an open source solution to explore and visualize data and supports lots of databases.
  • Apache Superset - Enterprise-ready business intelligence web application.
  • Meltano - Open source convention-over-configuration product for the whole data lifecycle, all the way from loading data to analyzing it.
  • insights - Insights is a tool to visually explore a PostgreSQL database, with an emphasis on generating graphs that show business performance over time.

Competitive Analysis

A bunch of resources to keep track of the current status and progress of all companies operating in the domain.

Commercial Solutions

History

Contributing

Your contributions are always welcome! Please take a look at the contribution guidelines first.

License

CC0 Content of this repository is licensed under the Creative Commons CC0 license. To the extent possible under law, Kevin Deldycke has waived all copyright and related or neighboring rights to this work.