Best Analytics for Django SaaS in 2026

Strengths

• ✓Funnels, retention and cohorts answer product questions page views never could.
• ✓Session replay lets you watch the exact path a confused user took.
• ✓Feature flags and experiments share the same identity data as the analytics.

Tradeoffs

• ✗Full event tracking makes it a privacy and consent conversation, not a free pass.
• ✗The client library is heavy compared to a simple page-view script.
• ✗Breadth of features means real onboarding time before anyone gets value.

Strengths

• ✓Script is tiny, so it has no measurable effect on page speed scores.
• ✓No cookies or personal data, which usually removes the consent banner requirement.
• ✓The entire dashboard fits one screen that a non-technical founder can read.

Tradeoffs

• ✗Aggregate only, so you can never inspect an individual user journey.
• ✗Custom events exist but the analysis depth stops well short of product analytics.
• ✗Paid from the beginning, unlike free ad-funded alternatives.

Strengths

• ✓Unlimited websites on one subscription suits people running many small projects.
• ✓Custom domain proxying recovers traffic that ad blockers would otherwise hide.
• ✓EU isolation option keeps European visitor data out of other jurisdictions.

Tradeoffs

• ✗Closed source, so you cannot audit or self-host the collection code.
• ✗Reporting stays deliberately shallow, with no funnels or cohort analysis.
• ✗Data export options are limited if you want your own warehouse copy.

Strengths

• ✓Self-hosting means the raw analytics data sits in a database you already run.
• ✓Stores into Postgres or MySQL, so you can query it with plain SQL.
• ✓No licence cost at all when you supply the hosting yourself.

Tradeoffs

• ✗Self-hosting means you own uptime, upgrades and database growth forever.
• ✗Analytics traffic writes to a database you must size and prune yourself.
• ✗Feature set trails commercial tools, especially around alerting and reporting.