Cost to add user analytics to your SaaS

Adding user analytics to your SaaS in 2026 typically costs $0 to $1,000+ per month for hosted tools (PostHog, Mixpanel, Amplitude), or $3,000 to $60,000 in one-time engineering if you build it yourself with a Postgres events table and Metabase. The biggest drivers are event volume, depth of analysis (basic tracking vs full funnels with cohort retention), and whether you self-host or buy.

Most SaaS teams pick a hosted tool because the engineering payback rarely justifies the build. The exception is when you already track most events for product reasons and just need a dashboard layer.

What "user analytics" actually means

The phrase covers four very different things, and the cost depends entirely on which you need:

• Event tracking. Capture clicks, page views, signups, button presses. Table stakes.
• Funnels. Watch how users move from step A to step B to step C. Where do they drop off?
• Cohort retention. Of users who signed up in March, how many came back in week 4? Week 8?
• Session replay and heatmaps. Watch what users actually do on a page.

A landing page with a signup button needs option 1. A SaaS trying to improve activation needs all four. A B2B product with 200 customers can probably get by with PostgreSQL queries and a Metabase dashboard. A consumer app with 50,000 daily actives cannot.

If you do not know which bucket you fall into yet, default to a free tier of PostHog or Mixpanel for the first six months. The cost to start is zero, and you can always swap later.

Cost breakdown by approach

The build-vs-buy decision usually comes down to event volume and whether you want session replay. Here is the honest comparison.

Approach	Cost	Timeline	Pros	Cons
PostHog (cloud, hobby tier)	$0 up to 1M events/mo, then ~$0.00031/event	Hours to integrate	Open-source, all-in-one (events + replay + flags + experiments), generous free tier	UI denser than Mixpanel; pricing climbs at scale
PostHog (self-hosted)	$0 in licenses, $50 to $400/mo in infra	1 to 3 days to deploy	Full data ownership, no per-event fees	You own the upgrades, backups, scaling
Mixpanel	$0 up to 1M events/mo, then $25 to $1,000+/mo	Hours to integrate	Cleanest funnel and retention UI in the category, strong cohort builder	No session replay until top tier; pricier above 10M events
Amplitude	Free up to 10M events/mo, then enterprise pricing (typically $40k+/yr)	Hours to integrate	Largest free tier in the market, strong behavioral analysis depth	Enterprise pricing is opaque and steep; sales-led
Segment (as a router)	$0 up to 1k MTUs, then $120/mo and up	Half a day to set up	Send one event to many tools; future-proof	Cost stacks on top of destination tools; not analytics itself
DIY (Postgres events + Metabase)	$5,000 to $20,000 engineering + $50/mo infra	2 to 6 weeks	Full ownership, no vendor risk, integrates with your app data	No session replay, no out-of-the-box funnels, you maintain it
Cadence engineer (build the integration or the DIY)	$500 to $2,000/week	48-hour trial, ship in 1 to 4 weeks	AI-native by default, weekly billing, replace any week	Less suited to multi-year enterprise procurement

A few notes that the pricing pages do not spell out:

• Mixpanel's free tier is generous on event count but caps you at 5GB of data retention. For most startups under 10k users, that is fine for a year.
• Amplitude's free tier at 10M events is the most aggressive in the category, but the jump to enterprise is the steepest. Get a written quote before you commit.
• PostHog self-hosted is excellent if you already run Kubernetes or have a senior engineer who is comfortable with Postgres tuning. If you do not, the cloud version is almost always the right call.

Engineering effort by depth

Hosted tools take hours to integrate. The cost we hear founders underestimate is the cost of instrumenting the events themselves and keeping them clean. Here is how that scales:

Basic event tracking (~10 events): $3,000 to $8,000

You define a list of high-signal events (signup, first action, paid, churned, key feature used) and wire them up. A mid-tier engineer can ship this in a week.

The work: agree on the event schema, install the SDK, add posthog.capture() calls in the right code paths, write a short doc explaining what each event means and who owns it. Skip the doc and you will regret it within a quarter.

Full funnel instrumentation (30 to 60 events): $10,000 to $25,000

This covers every step of activation, every paywall, every empty state. Now you can actually answer "where do users drop off in onboarding?"

The work expands because you need an event taxonomy, a naming convention, and a review step before new events ship. We have seen teams that skipped this end up with 400 events, 60% of them duplicates with different names. Cleaning that up costs more than doing it right the first time.

Funnel plus cohort retention plus custom dashboards: $25,000 to $60,000

Now you are not just tracking, you are answering questions: which acquisition channel produces users who stick? What is the activation rate for self-serve vs sales-led? Does the new pricing page convert better for SMB or mid-market?

This is where a senior engineer earns their rate. Expect 4 to 8 weeks for a real implementation, plus another 2 weeks to wire the dashboards to Slack alerts. If you have a related lift, like adding a referral program to your app, it pays to plan both at once because they share the same event backbone.

DIY with Postgres + Metabase: $5,000 to $20,000

If your event volume is low (under 100k events/day) and your team is already comfortable with SQL, a DIY stack is genuinely viable. The recipe:

1. An events table in Postgres with user_id, event_name, properties (JSONB), created_at.
2. A small wrapper in your app code (track('signup', { plan: 'pro' })).
3. Metabase connected to a read replica.
4. Saved dashboards for each metric you care about.

The reason teams underestimate this is that the dashboard layer (funnels, cohorts) is non-trivial to recreate in SQL. Mixpanel and Amplitude shipped their query engines because window functions over millions of rows on Postgres get slow. If your DAU is under a few thousand, you will not hit that wall for years.

Feature-by-feature cost

For a typical mid-stage SaaS, here is what the full analytics layer breaks down to in monthly run-rate:

Component	Hosted (PostHog/Mixpanel)	DIY
Event capture SDK	included	$0 (open-source libs)
Funnel analysis	included	$0 (SQL + Metabase)
Cohort retention	included	engineering time
Session replay	$0 to $200/mo	$50/mo (LogRocket or similar) or skip
Feature flags	included (PostHog)	$50/mo (LaunchDarkly low tier) or build
A/B testing	included (PostHog)	engineering
Hosting	$0	$50 to $400/mo (DB + app server)
Data warehouse export	$100 to $500/mo	included (it is your DB)

The all-in number for a Series A SaaS using PostHog cloud is usually $200 to $1,500/mo. The same setup with Mixpanel and a separate session replay tool runs $400 to $2,500/mo. A self-hosted PostHog stack on Render or Railway runs $80 to $300/mo plus the engineering cost to babysit it (call it half a day per quarter).

How to reduce costs without cutting corners

Five practical moves we recommend to every founder we talk to:

• Pick a free tier and start tomorrow. Do not spend a week comparing PostHog vs Mixpanel vs Amplitude. Pick one, ship the integration in an afternoon, swap later if you outgrow it. Decision paralysis is more expensive than choosing wrong.
• Define 10 events before you write any code. Write them on a whiteboard, get the founders to agree, then instrument. Adding events later is cheap. Renaming them after dashboards exist is painful.
• Route through Segment if you might switch tools. A $120/mo Segment subscription means you can pipe events to PostHog today and add Amplitude next year without re-instrumenting. For larger teams this is a no-brainer.
• Self-host only if you have the operational muscle. PostHog self-hosted is fantastic, but it adds a database, a worker queue, and a service to your ops surface. If you are 3 people and one of you is the CTO who already runs on-call, the hosted tier is cheaper.
• Treat session replay as a debugging tool, not a daily feed. Most teams over-buy session replay. Sample at 10% of sessions and you cut the cost by 90% with almost no loss in signal.

The fastest path from zero to instrumented

If you are starting from nothing and want a complete analytics layer in 2 to 4 weeks, this is the path we recommend:

1. Week 1: pick a tool and instrument 10 events. A mid-tier engineer can do this end-to-end. The events are: signup, email_verified, first_session, first_meaningful_action (depends on your product), paywall_view, paid, churned, plus 3 product-specific ones.
2. Week 2: build the dashboards. Activation funnel (signup → paid), weekly retention cohort, channel attribution if you run paid ads.
3. Week 3 to 4: add depth where it pays. This is where you wire alerts to Slack, build a paywall A/B test, set up session replay sampling.

If you do not have an engineer free for this work, the fastest way to get an analytics layer is to book a mid-tier Cadence engineer for two weeks. Every engineer on Cadence is AI-native by default (vetted on Cursor, Claude Code, and Copilot fluency before they unlock bookings), and instrumentation work is exactly the kind of scope where AI-paired engineering moves fast. Two weeks of mid-tier at $1,000/week gets you the full PostHog integration with 30+ events and four working dashboards, total spend $2,000.

For more ambitious lifts, like wiring analytics into a custom HubSpot integration or sending events from a customer portal, expect a senior tier at $1,500/week for 2 to 4 weeks.

If you are not sure whether to build or buy, the Cadence 48-hour free trial is the lowest-risk way to find out. Book an engineer, give them the scope, and you have two days to evaluate before any charge. We move our 12,800+ engineer pool against your spec and shortlist in 2 minutes.

FAQ

How long does it take to add analytics to a SaaS?

Integrating a hosted tool like PostHog or Mixpanel and tracking your first 10 events takes 1 to 5 days of engineering. A full funnel-and-cohort setup with 30+ events and custom dashboards takes 2 to 4 weeks. A DIY Postgres-and-Metabase stack takes 2 to 6 weeks depending on the depth of the dashboards.

Should I build or buy user analytics?

Buy for almost every SaaS under 100k MAU. Hosted tools are cheap at low volume, generous free tiers exist, and the engineering payback for building rarely beats the run-rate cost. Consider building only if your event volume puts you over $2k/mo in hosted fees, you already have a Postgres data warehouse, and you have an engineer who can own SQL-heavy dashboards.

Which analytics tool is cheapest for an early-stage SaaS?

Amplitude has the largest free tier (10M events/mo), so if you stay under that volume it is free. PostHog cloud is free up to 1M events/mo and bundles session replay, feature flags, and experiments, which would cost extra elsewhere. For pure cost, Amplitude wins at low volume but locks you into enterprise pricing if you scale. PostHog scales more predictably.

Do I need Segment if I am using PostHog?

Probably not. PostHog has its own SDKs and a clean integration path. Segment is most useful when you want to send the same events to multiple destinations (analytics + email + a CDP + a data warehouse). If you are committed to one analytics tool, Segment is overhead. If you might switch in the next 18 months, the routing layer pays for itself.

How much should I budget for ongoing analytics costs?

A typical Series A SaaS spends $200 to $1,500/mo on analytics tooling, depending on event volume and whether session replay is included. Add another $500 to $2,000/mo if you are running a Customer Data Platform, paid attribution tooling, or a data warehouse export. Engineering maintenance on a hosted stack is roughly 4 to 8 hours per quarter. A DIY stack runs closer to a day per quarter, more during migrations.