A working analytics pipe
An end-to-end flow from your codebase into Amplitude, validated and visible on a dashboard.
Long-form guide
The SaaS Analytics Guide
A modular, end-to-end walkthrough of building product analytics for a SaaS, from a single page-view event through revenue and feature tracking.
14 chapters3 sections~3 hour readUpdated May 2026
What you'll have at the end
The four results this guide produces
Each module adds something concrete you can point at, not theory, not slides.
An event taxonomy you can defend
Naming conventions and structure that hold up as you add modules, instead of the usual taxonomy debt.
Revenue and feature tracking
Patterns for revenue events and feature usage that connect to the same user identity throughout.
Before you start
What you'll need
Nothing exotic. If you have these, you can work through every chapter without detours.
- Comfortable editing your product's codebase (frontend or backend)
- An Amplitude account (free tier is enough)
- A Stripe account if you're doing the revenue module
- Plan for ~3 hours total, or one chapter at a time over a week
Table of contents14 chapters
The full guide, chapter by chapter
Section 01
Introduction
Why most SaaS analytics fails, the modular framework that fixes it, and how to read the rest of this guide.
1 chapter
Section 02
Concepts
Ideas that apply regardless of which analytics tool you use. Event taxonomies, naming conventions, client vs. server, identifying users, mapping payment webhooks. Read these once and they apply forever.
9 chapters
- 8 min
Event-based tracking explained
Events, event properties, and user properties (the three primitives every analytics platform is built on).
- 9 min
Event taxonomy
The single source of truth for every event you fire and every property you attach. Without it, your tracking drifts.
- 9 min
Naming conventions for events and properties
The conventions you pick matter less than picking them and enforcing them. A set that works well as a default.
- 12 min
Identifying users
Why cookies aren't enough, and the three identifiers (user ID, device ID, session ID) you need to think about.
- 9 min
Client-side vs. server-side tracking
The trade-offs between firing events from the browser and from your server, and the rule of thumb for choosing.
- 11 min
Tracking on successful states
Track outcomes, not intent. The rule behind most analytics bugs.
- 8 min
Heavy events vs. micro events
Why state-changing events and UI-state events behave differently, and how conflating them confuses your data.
- 11 min
GTM vs. codebase tracking
Two ways to wire up analytics. They're not mutually exclusive, but the architectural choice matters.
- 18 min
Mapping Stripe webhooks to analytics events
What webhook to listen for, what conditions to check, and what analytics event to fire. Tool-agnostic.
Section 03
Amplitude implementation
Actually building each of the four modules in Amplitude. Future sections will cover PostHog and Mixpanel; the patterns translate, the code changes.
4 chapters
- 16 min
Setting up Amplitude
Install the SDK, configure it sanely, and verify page views are flowing. One hour, end to end.
- 24 min
Authentication tracking
User IDs flowing through every event. Sign-up and sign-in events firing reliably. The foundation for retention.
- 22 min
Feature tracking
A template for instrumenting feature usage. Apply once per major area of your product.
- 26 min
Stripe revenue tracking
Server-side revenue events tied to Stripe webhooks. The most complex module, and the one that has to be right.
Want this implemented on your stack?
The guide gives you the framework. If you'd rather have it set up, validated, and documented for your team, that's what we do.