Updated: August 13, 2025 - 24 min read
Let’s be honest: there are a lot of product analytics tools on the market. Now, there’s AI as well. They all promise insights, dashboards, events, funnels, etc. So instead of giving you another generic list, we wondered what tools real product managers actually rely on. What helps them spot issues faster? What gives them clarity?
We rolled up our sleeves so you don’t have to. Here’s the list we ended up with.
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Here’s a quick snapshot of the tools and product analytics companies covered in this guide:
Mixpanel – Powerful event-based analytics with real-time reporting, advanced cohorts, and an AI assistant for querying. Best for SaaS companies that need granular insights.
Amplitude – Full-featured behavioral analytics and experimentation suite with AI insights. Best for mid-size to enterprise teams focused on growth and optimization.
Heap – Autocaptures all user interactions without manual tagging and includes heatmaps and session replay. Best for teams that want fast insights with minimal setup.
FullStory – Combines session replay with behavioral analytics to reveal the “why” behind user actions. Best for product and UX teams focused on experience improvement.
Hotjar – A Lightweight tool with heatmaps, recordings, and user surveys for quick UX feedback. Best for small to mid-sized teams, improving website usability.
Pendo – Combines product analytics with in-app guides and surveys to improve user onboarding and engagement. Best for B2B SaaS teams that want analytics plus in-product communication.
PostHog – Open-source analytics platform with feature flags, session replay, and experimentation. Best for technical teams that want full control and a free or self-hosted option.
Google Analytics (GA4) – Free tool for traffic, events, and funnel tracking with deep Google Ads integration. Best for teams needing marketing analytics or a basic product analytics layer.
Adobe Analytics – Enterprise-grade analytics for complex digital ecosystems with deep segmentation and predictive modeling. Best for large companies with high-volume data and dedicated analysts.
1. Mixpanel – Flexible event analytics for deep user insights
If you ask product managers which analytics tool they rely on day to day, Mixpanel almost always comes up. And for good reason. It’s one of the most established product analytics platforms out there. It’s incredibly good at helping teams understand how users interact with their product.
Mixpanel is an event-based analytics tool. That means instead of just tracking page views or sessions, it tracks what users actually do, like clicking a button, playing a video, or using a feature. It gives you the ability to dig into funnels, segment users into cohorts, and measure user retention with real granularity.
What product teams use Mixpanel for
Product managers typically use Mixpanel to:
Track user journeys across web and mobile
See where users drop off in a funnel
Measure product adoption over time
Create and monitor cohorts (e.g. “users who completed onboarding but didn’t return”)
Run A/B tests and analyze their impact
Tie product usage to business outcomes like conversions or upgrades
It’s especially popular among SaaS companies and digital products with complex user flows or multiple touchpoints. Teams use it to figure out what features are sticking, where users are getting lost, and what drives long-term retention.
Pros of this product analytics tool
The biggest strength of Mixpanel is how customizable and detailed it is. You can slice and dice your data almost any way you want. PMs love that it’s flexible but still feels modern and fast.
Here’s what stands out:
Intuitive UI and real-time dashboards
Funnels, retention curves, and cohorts that are easy to build and interpret
Deep segmentation based on user properties or behavior
Spark, an AI assistant that lets you ask questions in plain language and generates charts for you
Strong integration ecosystem (Segment, Snowflake, Slack, BigQuery, etc.)
Free plan is generous (enough to get real value out of it)
Cons of this product analytics software
That said, Mixpanel isn’t perfect.
It requires you to set up and name events manually. There's no automatic event capture like you’d get with Heap.
Advanced queries sometimes require workarounds or exporting to a warehouse for deeper product analysis.
The UI can feel overwhelming at first, especially if you haven’t worked with event-based analytics before.
Pricing can get steep at scale if your product generates millions of events monthly.
A few users also noted that while the platform is powerful, “a lot of features are hidden in the UI” or “require a bit of hunting.”
Who it is ideal for
Mixpanel is a great fit for:
SaaS and B2C product teams that care about long-term retention and feature adoption
Growth and product marketing teams running experiments
Startups (thanks to the free tier) all the way up to global enterprises with complex analytics needs
If you’re already thinking about things like “How can we improve activation?” or “What’s causing churn?”, Mixpanel is built for those kinds of questions.
Pricing
Mixpanel’s pricing is based on event volume:
Free plan: Up to 1M monthly events (It’s one of the free product analytics tools with a great feature set)
Growth plan: Starts around $20/month (for up to 20M events/year)
Enterprise plan: Custom pricing (starts around $833/month for 1T events/month)
Pricing can scale fast if you’re a high-traffic product, but the free plan offers plenty of headroom for smaller teams to explore the platform.
2. Amplitude – Scalable product analytics for teams that test, iterate, and grow
If your product team is serious about experimentation and optimization, Amplitude is probably on your radar. It’s one of the most feature-rich and best product analytics tools on the market. Plus, it’s built to handle big data, fast-moving teams, and complex user journeys.
Amplitude gives you the ability to understand how users move through your product, what keeps them engaged, and what actually drives business outcomes. With built-in experimentation and AI features, it goes beyond just reporting what happened. It helps you figure out why it happened and what to do next.
What product teams use Amplitude for
Data product managers and growth teams typically use Amplitude to:
Build detailed funnels and conversion flows
Segment users into behavior-based cohorts
Analyze user retention by feature, platform, or segment
Run experiments with built-in A/B testing tools
Track impact of feature releases across user journeys
Forecast behavior trends with machine learning models
It’s a tool that doesn’t just report the data but helps you act on it.
Pros of this product analytics platform
Amplitude really shines when you need to zoom out and see the bigger picture of how users interact across your entire product lifecycle. Teams love how robust and scalable it is.
Here’s what users consistently praise:
Powerful funnel, retention, and path analysis tools
Clean, modern UI with strong visualizations
Built-in A/B testing and feature flagging
AI assistants that surface trends and recommend actions
Integrates with everything from Segment to Snowflake
Free plan is generous enough to get started
As a verified G2 user reported:
“Amplitude is a tool I can't imagine running product management without. It gave me an easy way to understand deeply actions of my users... Running analyses, creating visualizations is really easy despite the variety of options. It’s the number one tool for product analysis I use nearly every day.”
Cons of this product analysis tool
Amplitude isn’t exactly plug-and-play. It’s a powerful tool, but that comes with a learning curve.
Requires a thoughtful tracking plan before you start
Implementation takes time and discipline (especially naming conventions)
The interface can feel overwhelming for new users
Performance can lag with large datasets
Some advanced features (like AI data analytics) are locked behind higher plans
Who it is ideal for
Amplitude is best for:
Mid-size to enterprise product teams with technical support
Growth teams running continuous experiments
Companies that want a data-driven approach to product decisions
If you’re building a high-traffic product and need to align product, data, and growth teams — Amplitude was made for that kind of complexity.
Pricing
Amplitude’s pricing depends on monthly tracked users and feature access:
Starter plan: Free, up to 50,000 monthly tracked users
Plus plan: $49/month, up to 300,000 users
Growth and Enterprise: Custom pricing (typically starts around $995/month)
It’s not the cheapest option. But, for companies that need scale and experimentation, it’s often worth it.
3. Heap – Auto-capturing analytics for teams that want instant insights without heavy setup
Heap takes a different approach to product analytics. Instead of requiring you to manually define every event you want to track, Heap just… tracks everything. Clicks, swipes, taps, form submissions, everything. It automatically captures all user interactions and lets you define events retroactively.
For busy teams who don’t want to spend weeks setting up their tracking plan, Heap offers a fast way to start learning from real user behavior right away.
What product teams use Heap for
Product managers and UX teams often turn to Heap when they want:
A complete picture of user behavior without tagging events manually
To retroactively create funnels and analyze user flows
Instant access to heatmaps, session replays, and conversion drop-offs
Journey maps to see what paths users take through a product
Real-time segmentation based on clicks, devices, or frustration signals (like rage clicks)
It’s particularly helpful during early product discovery or when teams need to move quickly.
Pros of this product usage analytics software
The biggest draw of Heap is how little work it takes to get started. With just one tracking snippet, you’re collecting everything.
What users love:
Auto-capture of every user interaction by default
Retroactive event creation. No need to predict what you’ll need later
Heatmaps and session replays built right in
Live view of user sessions for faster problem-solving
Intuitive UI with strong visualizations
Minimal engineering effort to launch
“Heap Analytics' autocapture and post-capture event definition combine to enable us to capture everything up‑front. Freed‑up opportunity cost to engineering is multiplicative because it really lets engineering focus on the development of customer features instead of implementing user analytics.”
Cons of this performance analytics tool
That convenience does come with tradeoffs.
The auto-captured data can pile up fast, which makes pricing a concern at scale
The interface takes time to master, especially when building complex reports
Segmentation and funnel logic can feel limited compared to tools like Amplitude
Doesn’t include in-app messaging or A/B testing (you’ll need other tools for that)
Also, while auto-capture is great early on, teams often need to clean up or rename events later to keep things usable.
Who it is ideal for
Heap works best for:
Fast-moving teams that want analytics without a long setup
Product and UX teams looking to identify drop-off points quickly
Startups, scale-ups, and even larger orgs who value speed over precision early on
If you’ve ever said “we don’t have time to tag everything”, Heap is for you.
Pricing
Heap offers usage-based pricing with flexible tiers:
Free plan: Up to 10,000 sessions/month with 6 months of data retention
Paid plans: Start around $3,600/year depending on volume and features
Growth, Pro, and Enterprise tiers: Custom quotes based on usage and team size
If you’re early stage, the free tier is more than enough to get going. For larger product-led organizations, it scales, but you’ll want to watch your session volume.
4. FullStory – Session replays meet analytics for teams who want to understand the why
FullStory, one of the Proddy Award winners, is what product teams reach for when they want to go beyond charts and dashboards. It combines product analytics with full session recordings, so you can watch real user sessions and pinpoint where things are going wrong.
It’s not just about watching videos. FullStory automatically captures every interaction (clicks, scrolls, rage clicks, console errors, DOM changes) and lets you layer that into funnels, journeys, and conversion analysis.
What product teams use FullStory for
Product teams often use FullStory when they want:
Session replays to understand how users experience a flow
To analyze rage clicks, dead clicks, and other frustration signals
Heatmaps to visualize where users spend time or get stuck
Funnels with video context to see why drop-offs happen
Debugging tools for product and engineering (with exact error context)
To surface hidden UX issues that traditional analytics can’t show
It’s a tool that’s especially valuable when numbers alone don’t tell the whole user story.
Pros of FullStory
FullStory is often described as a “power tool” for UX, product, and support teams. It helps teams move from “What happened?” to “Why did that happen?”
Here’s what stands out:
Auto-captures every user session, no tagging needed
Combines quantitative and qualitative insights in one place
Extremely detailed session replay (with click paths and rage-click detection)
Easy to set up and share insights across teams
Integrates with tools like Segment, data warehouses, and customer support tools
“Fullstory gives us a clear, visual understanding of how users interact with our product. The session replay feature is especially helpful for identifying pain points and validating feedback from users or support teams.”
Cons of FullStory
While the insights are rich, FullStory isn’t a deep funnel or cohort analysis tool in the way Mixpanel or Amplitude is.
Here’s what users often point out:
The UI can feel cluttered or hard to navigate for new users
Not ideal for complex segmentation or A/B testing
Session replays can be overwhelming to sift through without filters
Price can scale quickly if your product has high-traffic
It’s a tool better suited for uncovering product experience issues than for running advanced behavioral queries.
Ideal for
FullStory is a great fit for:
UX and product teams who want to diagnose friction fast
Teams that need both data and context to fix bugs or drop-offs
Mid-sized to large orgs focused on improving product usability
If your team asks “Why are users abandoning this page?” or “Where’s the friction in this flow?”, FullStory helps you answer that in minutes.
FullStory Pricing
FullStory offers several tiers depending on session volume and data retention:
Free plan: Up to 10,000 sessions/month with 1-month retention
Business plans: Custom pricing based on session count, features, and seats
Enterprise plans include longer retention, more integrations, and dedicated support
While there’s a free version to start with, larger orgs typically need a custom plan and pricing reflects that
5. Hotjar – Understand user behavior without diving into deep analytics
Hotjar isn’t trying to be a full-blown analytics suite. Instead, it focuses on helping teams quickly spot usability issues, understand what users care about, and collect in-the-moment feedback, without needing a product analyst to make sense of it.
It’s easy to install, easy to use, and gives you heatmaps, session recordings, and surveys right out of the box. For many teams, Hotjar is the first step toward building a more user-centric product.
What product teams use Hotjar for
Hotjar is often used to:
Watch real user sessions to see where people struggle
Visualize where users click, scroll, or drop off with heatmaps
Launch on-page surveys or polls to gather direct feedback
Improve landing pages and product-led onboarding flows
Get context on why a funnel might not be converting
It’s particularly useful during early product discovery, post-launch reviews, or when A/B test results need qualitative backup.
Pros of this web product analytics tool
Hotjar’s biggest strength is its simplicity. You can get valuable feedback and visual insights without needing to instrument anything manually.
What teams love:
Heatmaps that show user behavior at a glance
Session recordings to catch usability issues in context
Quick-launch surveys and NPS polls with no code required
Super simple setup, just one script and you’re live
Works well alongside other analytics tools like GA, Mixpanel, or Amplitude
One G2 reviewer shared their experience with Hotjar:
“Hotjar is incredibly intuitive, offering valuable heatmaps, session recordings, and feedback tools that help us better understand user behavior and improve our website performance.”
Cons of this user analytics tool
While Hotjar is great for quick insights, it has its limits.
Doesn’t offer deep behavioral analysis or cohort tracking
No built-in A/B testing or advanced funnels
Session recording playback can sometimes be slow or buggy
Free plan limits daily session recordings
Pricing jumps quickly as your traffic grows
Also, it’s primarily focused on websites, so mobile app teams may need to look elsewhere.
Ideal for
Hotjar is best for:
Teams that want visual insight into user behavior
Marketers and designers optimizing landing pages and sign-up flows
Startups and SMBs who don’t need complex analytics (yet)
It’s a great tool to pair with something more quantitative, especially if you want to understand why users behave the way they do.
Hotjar Pricing
Hotjar offers clear pricing based on session volume:
Basic plan: Free, with up to 35 sessions/day and unlimited heatmaps
Plus: $39/month for 100 daily sessions
Business: Starts at $99/month for 500 daily sessions
Scale: From $171/month for high-volume needs and advanced features
You can start using it for free, and upgrade as your site traffic (and questions) grow.
6. Pendo – For teams focused on user onboarding and feature adoption
Pendo, a Proddy-awarded tool, goes beyond just showing you how users behave. It helps you influence that behavior directly. It combines product usage analytics with in-app guides, tooltips, and surveys so you can both understand and improve the product experience, all in one place.
If your team cares about feature adoption, user onboarding, or collecting feedback without waiting on developers, Pendo is built for that.
What product teams use Pendo for
Product and customer success teams use Pendo to:
Track feature usage across user segments
Understand product adoption patterns and product stickiness
Launch no-code in-app messages, walkthroughs, and NPS surveys
Prioritize product roadmap decisions based on actual user behavior
Monitor how new features are performing post-release
It’s a unique blend of product analytics and engagement, ideal for teams that want to act on what they learn.
Pros of using Pendo
Pendo is especially useful when you want to improve the product experience without relying heavily on engineering.
Here’s what stands out:
In-app guides and tooltips without writing code
Clear dashboards showing which features are used (and by whom)
Built-in feedback tools like NPS and surveys
Easy tracking of usage across accounts, roles, or user types
Great customer support and user onboarding resources
According to a verified G2 user:
“Pendo makes it easy to understand user behavior within our product. The in‑app guides and onboarding flows are especially useful for driving adoption and reducing support tickets. Its visual tagging system for setting up analytics events without developer support is a huge plus.”
Cons of this performance analytics tool
The biggest downside? Complexity. Pendo packs a lot into one platform, and it takes time to get it all working smoothly.
Some common friction points:
Advanced analytics features can feel limited compared to Mixpanel or Amplitude
Setup and event taxonomy can be time-consuming
No session replays or auto-capture (you have to define events)
Pricing is quote-based and generally on the higher end
Reporting can feel rigid for teams that want full data flexibility
Many teams end up using Pendo alongside tools like FullStory for a more complete picture.
Ideal for
Pendo is a strong fit for:
B2B SaaS companies focused on onboarding and retention
Product teams that want to guide users through complex flows
Customer success and support teams aiming to reduce friction
If you want both analytics and a way to improve the user journey inside the product, Pendo brings those together in one platform.
Product Pricing
Pendo’s pricing depends on Monthly Active Users and selected features:
No public free tier, but some startups get access via programs
Paid plans are quote-based and typically mid-to-enterprise level
Plans scale with user count, analytics depth, and engagement features
It’s not the cheapest option, but for the right use case, the combination of insights and in-app action can pay off quickly.
7. PostHog – Open-source analytics for dev-first teams that want full control
PostHog is a product analytics platform built for engineers and technical product teams who want powerful analytics without giving up ownership of their data. It's open-source by default, but also offers a cloud-hosted option for teams that don’t want to self-manage.
What makes PostHog different is that it also includes feature flags, session recordings, heatmaps, A/B testing, and feedback tools. All in one stack. No juggling five different tools.
What product teams use PostHog for
Engineering-driven product teams often use PostHog to:
Track events, funnels, user retention, and cohorts
Run experiments with built-in feature flags and split testing
Replay user sessions to catch bugs or confusion
Use heatmaps to visualize behavior on specific pages
Collect product feedback and ship features faster
It’s ideal for companies that want to build fast, experiment often, and keep data in-house or on a budget.
Pros of PostHog
PostHog is especially appealing to teams who want to move fast without vendor lock-in.
What teams like:
Free and open-source (you can host it yourself, forever)
Generous free cloud tier (1 million events/month)
Built-in suite: analytics, replays, feature flags, surveys, heatmaps
Strong developer docs and open roadmap
Easy to set up in modern frameworks (Next.js, React, etc.)
As noted by a PostHog user on G2:
“I love that it's open source and self‑hostable, which ensures complete data ownership. The UI is intuitive, and the event tracking setup is straightforward. Session replays and feature flags are built‑in, reducing the need for multiple tools. It’s especially great for engineering‑led teams.”
Cons of PostHog
Because it’s dev-first, it’s not as plug-and-play as some other tools.
What to watch out for:
UI can feel rough in places, especially compared to enterprise tools
Self-hosting requires dev ops effort and some infrastructure knowledge
Advanced filtering and dashboards can be a bit less polished
Some users report bugs or a steep learning curve for non-technical users
It’s also still evolving fast, which means new features appear often, but they might need polish.
Ideal for
PostHog works best for:
Startups and technical product teams that want full-stack analytics
Companies that value open-source and want to avoid vendor lock-in
Teams that want to build and ship prototypes quickly with minimal overhead
If your team prefers cloning a GitHub repo over filling out a sales form, PostHog’s probably your kind of tool.
Product Pricing
PostHog offers flexible pricing for both cloud and self-hosted setups:
Self-hosted: Free, with no event limits
Cloud: Free up to 1 million events/month
Beyond that, pay-as-you-go pricing based on usage:
Events: $0.0001 each
Feature flags, recordings, and surveys priced per unit
It’s one of the most cost-effective options for small and mid-size teams, especially if you're comfortable managing infrastructure.
8. Google Analytics (GA4) – Free, flexible traffic and behavior tracking
Google Analytics is the most widely used analytics tool in the world. With the launch of GA4, it’s taken a more product-focused turn. GA4 is built around events (not just sessions and pageviews), giving teams better insight into what users actually do inside their app or website.
It’s not a full substitute for a dedicated product analytics platform, but it’s a strong, free starting point. It’s especially appealing for teams already deep in the Google ecosystem.
What product teams use GA4 for
Teams use GA4 to:
Track pageviews, events, conversions, and session data
Monitor where users come from and what they do once they land
Set up funnels and measure drop-off across key flows
Analyze user retention and lifetime value
Connect behavior data to ad campaigns in Google Ads
It’s often used alongside more advanced tools, but it covers the basics surprisingly well, especially for product-led marketing.
Pros of Google Analytics 4
The biggest advantage of GA4 is its combination of broad capabilities and zero cost.
What teams appreciate:
Free to use with generous data limits
Deep integration with Google Ads, Search Console, and BigQuery
Supports both web and mobile app tracking (via Firebase)
Offers real-time reports and user journey views
Reliable and well-documented
Cons of Google Analytics 4
GA4 comes with a learning curve, especially for teams used to the old Universal Analytics setup.
Some common challenges:
UI can feel confusing and unintuitive at first
Requires configuration to get meaningful product insights
Doesn’t support session replays, heatmaps, or experimentation
Funnels and retention reports are less flexible than dedicated tools
Sampling can occur on large datasets unless you connect to BigQuery
It’s powerful, but not always beginner-friendly.
Ideal for
GA4 is a solid choice for:
Startups and teams that want free analytics out of the box
Marketing and product teams who need basic behavior and conversion tracking
Any company using Google Ads or working within the Google ecosystem
If you need a low-cost way to track traffic, funnels, and product goals, and don’t mind learning the new structure, GA4 gets the job done.
Pricing
GA4 standard: Free, with up to 10 million events/month per property
GA4 360 (Enterprise): Custom pricing, starting around $150,000/year
Offers SLAs, more integrations, and no sampling
Most teams use the free version and upgrade only when scale or compliance demands it.
9. Adobe Analytics – Enterprise-grade analytics for companies with massive data
Adobe Analytics is in a league of its own when it comes to power, flexibility, and depth. It’s built for enterprises that need to stitch together user journeys across multiple channels, analyze complex behavior at scale, and generate highly customized reports (with help from dedicated analysts or consultants).
This isn’t a plug-and-play tool. But for the right company, Adobe Analytics can be a reporting powerhouse.
What product teams use Adobe Analytics for
Large organizations use Adobe Analytics to:
Analyze user behavior across websites, mobile apps, email, and offline touchpoints
Build custom key metrics, North Star, segments, and attribution models
Track performance in real-time, at scale, with unsampled data
Connect product analytics with marketing, personalization, and customer data
Power dashboards and reports for executive and stakeholder visibility
It’s often used by cross-functional teams across product, marketing, data, and analytics.
Pros of Adobe Analytics
Adobe Analytics is built for depth. If you have a mountain of data and need to break it down from every possible angle, this tool delivers.
Here’s what it’s great at:
Handles massive data volumes without sampling
Supports fully customizable dashboards and calculated metrics
Built-in attribution and predictive analytics capabilities
Integrates with the broader Adobe Experience Cloud (like Adobe Target and Campaign)
Ideal for multi-site, multi-region, multi-channel environments
Cons of Adobe Analytics
This is not a tool for small teams or anyone looking for quick insights without a heavy setup.
Common drawbacks:
Very steep learning curve (even for experienced analysts)
Complex implementation often requires external help
UI can feel outdated and overwhelming
Limited agility, making changes can be slow
Expensive, both in license and in the resources needed to maintain it
In short, it’s incredibly powerful, but not lightweight.
Ideal for
Adobe Analytics is a good fit for:
Large enterprises with high-traffic digital properties
Teams that need to unify data from multiple sources and channels
Organizations with in-house analysts or external support
Companies already using Adobe Experience Cloud products
If your team needs full control over analytics across a sprawling digital ecosystem and has the resources to handle it, Adobe Analytics is hard to beat.
Pricing
Adobe does not publish pricing publicly, but here’s what we know:
Enterprise contracts typically start in the six-figure range
Pricing depends on traffic volume, number of properties, and integrations
Usually bundled with other Adobe tools (like Adobe Target, Campaign, etc.)
Most companies using Adobe Analytics have already reached enterprise scale and have the budget and internal resources to get full value from the platform.
Choosing the Right Product Analytics Tool
There’s no one-size-fits-all when it comes to product analytics — and that’s a good thing. The best tool for your team depends on what you're trying to uncover, how technical your setup is, and what kind of decisions you're trying to drive.
The most important thing: pick the tool that will actually be used. The one your team feels confident exploring, sharing, and acting on. A tool that fits your product culture, not just your budget.
So take your time. Try a few. Talk to your engineers, your designers, your data team. And when you find the one that helps your team move faster, build smarter, and learn more, that’s your tool.
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Updated: August 13, 2025
