If you're in a B2B product team and tired of analytics tools that promise the moon but leave you lost in a dashboard maze, this guide is for you. We're going deep on PostHog, a software tool that wants to be your all-in-one product analytics, session replay, feature flag, and experimentation platform. We'll pull apart what actually works, what’s still rough, and how it stacks up to other real options if you’re running product analytics for a SaaS or B2B team.
Who This Is For
- Product managers, data leads, and growth folks at B2B SaaS companies
- Teams who want to own their analytics (or at least understand where their data lives)
- People sick of paying for three tools just to answer basic product usage questions
If you just want to slap a dashboard on your app and never think about it again, skip this. But if you want to dig into how users actually use your product — and maybe run some experiments — read on.
What Is PostHog, Really?
PostHog pitches itself as a "suite" for product analytics. That means:
- Event tracking (who did what, when)
- Funnels and retention
- Session replays (see exactly what users did)
- Feature flags (toggle features for some users)
- A/B testing and experiments
It's open source at its core — you can self-host, but most B2B teams just use their cloud service. They’re gunning for the Segment/Amplitude/Hotjar crowd, but with a single login and, ideally, less vendor lock-in.
What Makes PostHog Different?
- Self-hosting option: You can run it yourself for privacy or compliance (but most just use their cloud).
- All-in-one: You get analytics, session replay, and feature flags in one UI. No more Frankenstack.
- Open core: You can see (and contribute to) the codebase, if you’re into that.
- Transparent pricing: No sales calls just to get a number. Pricing is public, but can get steep if you scale fast.
But — as with any tool promising to replace three others — there are tradeoffs.
The Good: Where PostHog Stands Out
1. Setup and Data Ownership
Quick to get started: The JavaScript snippet works like any other analytics tool. SDKs exist for most stacks (Node, Python, Go, etc.). Data starts flowing in minutes.
Own your data: If you self-host, you control the database and logs. Even on their cloud, data export is straightforward. This is a breath of fresh air compared to, say, Mixpanel’s walled garden.
GDPR and compliance: Easier to handle privacy and compliance requests since you have more control. This won’t solve all your legal headaches, but it helps.
2. The All-in-One Promise (Mostly Delivered)
- Product analytics: Funnels, retention cohorts, and event breakdowns are all here. The UI is pretty direct — less “look at our pretty graphs” and more “here’s the data.”
- Session replays: Not as slick as FullStory, but works. Find a user, watch what happened. Great for debugging weird support tickets.
- Feature flags: Add them in code, flip them on/off in the UI. Supports gradual rollouts and targeting.
3. No-Nonsense Pricing
- Usage-based: You pay for what you use (tracked events, recordings, etc.). Public calculator, no opaque “call us” pricing.
- Startup-friendly tier: Generous free plan for early-stage teams.
4. Community and Documentation
- Active community: Open source means a lively Slack, GitHub, and forum scene. Good for weird edge cases or when docs are thin.
- Docs: Generally solid. Not perfect, but better than most open-source projects.
The Gaps: Where PostHog Struggles
1. B2B Data Model Pain
Accounts vs. Users: PostHog is user-centric by default. This can get messy if your product revolves around accounts, organizations, or workspaces. You’ll need to model these relationships yourself (think: custom properties, manual joins). Not out-of-the-box like in more mature B2B analytics tools.
2. UI and Usability Rough Edges
- Steeper learning curve: The UI can be confusing, especially when switching between analytics, session replays, and flags. It’s better than it was, but not as polished as Amplitude or Mixpanel.
- Dashboards are basic: You get the essentials, but don’t expect glossy executive dashboards or fancy reporting. Good for product teams, less good for showing off to the board.
3. Experimentation Is New(ish)
- A/B testing: It works, but it’s early days. Statistical methods aren’t as robust as dedicated tools like Optimizely. Fine for basic tests, not ideal for complex experiments or those needing deep stat-sig analysis.
4. Scaling and Performance
- Self-hosting gets complex: If you want to run your own infra at scale, plan for DevOps work. Database tuning, upgrades, and storage management all land on your plate.
- Cloud scales well, until it gets pricey: Their managed service is solid, but if you’re piping millions of events a day, your bill can spike.
How Does PostHog Compare to Other Tools?
Let’s stick to the most common alternatives B2B product teams ask about.
PostHog vs. Amplitude
- Amplitude: More mature for product analytics, especially for B2B (built-in account-level reporting, richer segmentation).
- PostHog: Better for teams who care about session replay, feature flags, and want everything in one tool.
- Amplitude is easier to use out of the box for classic product analytics. PostHog gives you more flexibility if you’re willing to tinker.
Pro tip: If you need best-in-class analytics and your budget is big, Amplitude wins. If you want good-enough analytics plus session replay and flags, PostHog is a strong bet.
PostHog vs. Mixpanel
- Mixpanel: Slick interface, solid funnels and retention, but less open and more focused on user-level analytics.
- PostHog: Similar depth, but you get feature flags and replays. Mixpanel’s free tier is stingier, and their paywall hits fast.
PostHog vs. FullStory/Hotjar
- FullStory/Hotjar: Best for user/session replays and heatmaps, not analytics.
- PostHog: Session replays are “good enough” for debugging, but not as rich as FullStory. If you care about analytics and not just watching user clicks, PostHog is better value.
PostHog vs. Segment
- Segment: Data pipeline — not analytics. Use it to send data to other tools, not analyze it directly.
- PostHog: You can use PostHog as a Segment destination, or skip Segment entirely and track directly.
What You Can Ignore (For Now)
- Mobile analytics: PostHog’s mobile SDKs exist, but aren’t the strongest. If you’re mostly web/SaaS, you’re fine.
- Advanced reporting: Don’t expect fancy, scheduled PDF reports or deep data warehouse integrations out of the box.
- Marketing attribution: Not PostHog’s strong suit. Use something else for full-funnel marketing analytics.
Common Gotchas and Pro Tips
- Plan your data model: B2B teams should map out how they’ll track accounts, users, and key actions before rolling out PostHog. Retroactive fixes are a pain.
- Don’t overtrack: Resist the urge to log every button click. Focus on events that answer real questions.
- Session replay costs: Don’t leave it on for everyone, or your bill (and S3 storage) will explode. Sample wisely.
- Feature flags: Start simple. Use for toggling features, not as a catch-all permissions system.
The Bottom Line
PostHog is a strong contender if you want a one-stop shop for product analytics, feature flags, and session replay — especially if you’re allergic to vendor lock-in and want more data control. The all-in-one nature is real, but it’s not perfect, especially if your B2B data model is complex or you need enterprise-grade reporting.
Best move? Keep it simple at first: track a handful of key events, review your funnels and replays each week, and don’t let the perfect be the enemy of getting answers. Iterate as your team’s questions get sharper. If PostHog’s gaps start to pinch, you'll know — and by then, at least you’ll understand your own data better.