7 Best Product Analytics Software in 2025: My Review

B2B business owners rely not just on audience insights, but also on the response of customers or other stakeholders who utilize their products to complete an action.

Within a B2B startup, it's the data that drives potential decisions of developers, product managers, product specialists, and sales and marketing professionals.

As part of the marketing team of a budding B2B startup, I’ve been directly involved in iterations of products based on real-time consumer insights, ROI, and user engagement. It wasn’t without struggles. Some major hurdles I experienced were teams' siloed operations, the absence of product analytics, and limited user journey visibility. 

That is why I decided to evaluate the best product analytics tools myself. These tools give you insights into how users interact with your product, exhibit positive or negative sentiment, and provide trust signals.

This list would give you a complete evaluation of the best product analytics tools in 2025, as observed by G2. These tools offer a unified view of consumer journey, product usage metrics, and real-time user experience details to optimize your digital applications.

7 best product analytics tools I strongly recommend

As the backend team of a B2B product, your future scope of developmental changes and product upgrades depends on what your customers think of you. While you might be tracking user engagement, customer feedback, or frequent events, your benefit lies in tracking real-time product ROI with advanced dashboards and analytics, which is solved with a product analytics tool.

During my analysis, I noticed a clear gap between the metrics that businesses try to track and the consumer market metrics that actually matter. You have your series of release approvals or go-to-market launches, but the core issue lies in understanding the basics: how your application really works, and whether users are truly engaging with it.

What makes a product analytics tool worth it: my opinion

According to me, the first step in choosing a product analytics tool is to maintain the status quo with your functional departments — like product, development, engineering, and sales — and put an exhaustive list of user responses or feedback that you have so far.

Analyze the raw consumer data, segment it based on demographics, and spot patterns of frequently listed complaints or negative responses that can help you improve your iteration processes. While product analytics tools provide an extensive report of real-time user interaction with the product, there are a few other things to keep in mind before investing in a compatible solution.

If you are serious about scaling your product and don't want to risk your revenue, lose customers, or make blind decisions, here are six features you absolutely must demand from any product analytics software you are considering:

• Event-based user journey tracking: I didn't consider tools that only offer basic page views for your product; rather, I prioritized the ones that track every meaningful user action, from button clicks to feature usage, across the entire customer journey. Without this feature, you won't understand which part of your application is driving engagement or drop-offs. This level of granularity allows you to move from guessing to knowing exactly what behaviours lead to conversions, so you can double down on what's working and fix what's not. 
• Cohort and segmentation analysis: If your analytics tool can't segment your cohorts into meaningful categories, like power users, churn risks, or first week drop-offs, you won't be able to scale your business. I listed the solutions that offer advanced segmentation, which lets you personalize experiences and campaigns based on real user behaviour. This helps you target the right users with the right messages at the right time, improving both retention and revenue with less marketing waste.
• Funnel visualization and drop-off analysis: You need to see where exactly your users drop off in your key funnels, whether it’s between sign-up to activation or trial to paid. A tool without this capability will leave you guessing what's killing your conversion rates. That’s why I only went for product analytics tools that offer clear and actionable funnel breakdowns. With this clarity, you can prioritize fixes that have the biggest revenue impact and turn leaks in your funnel into growth opportunities.
• Retention and stickiness reports: One-time users or churned customers would not grow your base, but retained and sticky users will. I made sure that the platform helps you measure not just who comes once, but who keeps coming back and what behaviours correlate with long-term retention. It helps you shift from acquisition to building lasting user habits, which is where sustainable growth really happens.
• Real-time insights and dashboards: I aim to highlight the importance of not taking your customer data lightly and regulating your pipeline conversions. In this sector, delayed data is wasted data. I looked for real-time dashboards that update live so you can make fast and informed decisions without waiting on engineering or weekly reports. This empowers your teams to react in the moment, turning insights into actions while they still matter, and not weeks later when the opportunity is gone.

True to the intel above, product analytics tools are also integrated with session replay software, digital analytics software, user research software, and heatmap tools to crack your buyer signals and capture that exact stage in the buying funnel that leads to potential churn or drop-off.

Out of the 40+ product analytics tools that I examined, I shortlisted the top 7 that achieved the highest G2 scores and larger reciprocation from the customer market.

The list below contains genuine reviews from the product analytics software category page. To be included in this category, a software must:

• Track user interactions with a digital product, including visits, usage, events, and interactions.
• Provide segmentation by demographics, preferences, or even device type.
• Identify behavioral patterns and funnels to understand how customers flow through the product.
• Identify pain points within a product that may lead to churn, or specific steps within the customer journey that need improvement.
• Provide dashboards and reports of visualized quantitative data.

*This data was pulled from G2 in 2025. Some reviews may have been edited for clarity.  

1. Amplitude: Best for custom event tracking and user segmentation

Amplitude is a digital analytics product that provides users with personalized insights about customer experiences and interactions across different devices. It’s designed to improve efficiency and productivity and prioritize conversions.

When I started, it really stood out to me how easy it was to get up and running. I devoted my time to learning more about the user experience, like dragging events, building funnels, segmenting cohorts, and was pretty much self-sufficient by the end of it.

Not just me, but even my marketing teammates found the UI to be extremely user-friendly. There was no SQL or backend data wrangling. Just clean, intuitive, point and click analytics.

Amplitude thrives on event-based tracking, which means every user action, whether it's clicking a button, watching a video, or abandoning a cart, will get logged as an event. What's great is how you can slice and dice this data however you want. I found the Cohorts feature especially brilliant. It lets me group users based on behaviours like "users who watched a product demo but didn't sign up" and compare their engagement patterns against other groups. 

What I also loved about Amplitude is that it offers retention analysis, which is a set of metrics that enable users to understand what makes a buyer stick around or continue their contract for the long term.

Another strong point? The dashboard and reporting system. It feels fast. I've rarely faced delays or annoying load times, even when running heavy queries on millions of events. You can build custom dashboards to track everything, from daily active users to conversion rates.

Thanks to the integration with the customer data platform (CDP), it feels like the insights never hit a dead end. You can sync your findings with tools like Braze or Mixpanel for follow-up campaigns.

But there are a few areas of improvement to consider. For starters, Amplitude's pricing scales based on your data volume. So, if your team gets trigger-happy with event tracking, you can unexpectedly go over the budget. 

Also, while the dashboards are great, they're a bit rigid. You cannot tweak chart views directly from the dashboard. You have to open each chart separately, make your changes, and then save them. It is a small hassle, but when you are trying to move fast, it feels like a speed bump.

What’s more, Amplitude heavily depends on the quality of your event tagging plan. If your implementation team doesn't define events clearly or if you have inconsistent naming conventions (and, let's face it, most of us do at some point), your data quickly becomes messy and frustrating to work with. Many times, you'll find yourself wishing for smarter ways to reorganize or rename events without having to re-engineer your entire data pipeline.

Also, Amplitude is event-focused, and sometimes, I wish it could do a better job surfacing user-centric insights — things that go beyond counts and timelines. A stronger user lens would make the tool even more holistic. 

When it comes to premium features, I explored the Amplitude Growth and Enterprise plans, and the difference is noticeable. The premium plan unlocks several new features, like Notebooks, Governance Controls, and Predictive Analytics (which uses machine learning to forecast user behaviour).

Enterprise plans go even further with custom role-based access controls, data residency options, and dedicated support. Honestly, if you are running analytics across multiple teams or regions, these premium layers are worth it. But if you are just starting out, the free plan is more than enough.

Overall, Amplitude offers an agile digital analytics platform to track product usage, user behaviour, customer retention, and churn to determine next steps of the sales funnel and push your marketing outreach to convert better.

What I dislike about Amplitude:

• Although Amplitude segments your analytics in a user-friendly way, I think it is a bit of a challenge for beginners, as it is a bit complicated. 
• I observed that Amplitude is not always intuitive about how various charts work. I often noticed users falling back on segmentation and sessions because they don't understand how the other types work.

What do G2 users dislike about Amplitude:

"The inherent complexity of the reporting capabilities may prove to be overwhelming at times, that said though, Amplitude has been making strong advancements in organizing their reporting structure and providing a more intuitive UI that allows the user to easily navigate thu pre-established reporting templates and still allow you to dig into the complex reports if you want/need to."

- Amplitude Review, Max E. S.

2. LogRocket: Best for session replays and bug tracking

LogRocket combines session replay, product analytics, and user behaviour in one dashboard to help you with a clearer view of user interactions and capitalize on winning conversions by modifying your new upgrades and releases.

What really blew me away was how effortless session replay feels within LogRocket. You can sit back and literally watch how your users navigate your website or app, click by click or scroll by scroll.

I could also see JavaScript errors in real time, inspect network requests, and view console logs right alongside user sessions. This level of developer tooling integration makes debugging less cumbersome and more useful for consumer problems.

One of my favorite features is error tracking with stack traces. When a user hits a bug, they can rewind the session to see what exactly led up to it, along with technical context. This has been a lifesaver when collaborating with my engineering team. 

LogRocket doesn't just stop at session replays either. It integrates neatly with Redux state management, which is huge if you are dealing with complex React applications like I do. Seeing state changes frame by frame in the session playback adds so much clarity when tracing issues that are otherwise impossible to reproduce.

I also appreciated the heatmaps and user flow visualizations, which helped me understand drop-off points and high engagement zones on our pages. It is satisfying to have both qualitative and quantitative data on one platform. 

LogRocket’s performance monitoring feature? A huge bonus! You get insights on page load times, slow API responses, and resource bottlenecks without needing a separate performance monitoring suite.

That said, not everything is gold. Premium features like advanced filtering, team collaboration features, and long-term data retention are hidden behind a paywall. I noticed that while the free version offers basic options, premium features also unlock advanced integrations with Jira, Slack, and Sentry, making it easier to push customer case data into various workflows. 

Another thing that gets under my skin a bit is that session recordings occasionally fail to capture certain events, especially on mobiles, on single-page applications. It is inconsistent enough to be annoying when you rely on it to catch everything.

While session replays are insightful, they do not scale well. Watching hundreds of sessions to identify trends just isn't practical without leveraging the analytics dashboards, which aren't as intuitive as I'd like them to be.

The platform can sometimes feel sluggish, especially when loading large sessions or filtering through extensive logs. Plus, I wish historical data retention were available on low-tier plans. Right now, it feels like a bit of a paywall if you want to access older session data.  

Another small gripe is the lack of offline or downloadable session data, which is super helpful for audit sessions or sharing sessions with people outside your platform.

Still, LogRocket monitors event tracking, website tracking, session replays, and other product analytics metrics to evaluate user engagement and interactions and reveal customer trends and conversion possibilities. 

What I dislike about LogRocket:

• While the session replay software makes you aware of how users interact, it takes some time to make the LogRocket sessions reliable. 
• I observed that some sessions are not captured. The platform's data can be confusing or overwhelming.

What do G2 users dislike about LogRocket:

"The main issue we have is that the data is not archiving/being accessible after a month. This does hurt us when we need to benchmark data and track issues. It would be helpful if we could access user sessions even 6 months back. I also wish there was some sort of LogRocket academy hub or training accessible to users instead of just a library of documentation, which can be dense to read through."

- LogRocket Review, Ashley K.

3. Pendo: Best for product usage insights 

Pendo provides real-time user insights and product usage metrics to deliver the best software experiences and optimize the productivity of your team and clients. With Pendo's in-app dashboard, you can drive leads, improve calling, generate surveys, and do a lot more to drive satisfaction.

The first thing that struck me about Pendo was how easy it was to get started. Setting up in-app guides and walkthroughs felt almost effortless. I didn't need to loop in engineering for every little update, which made our onboarding process much smoother. 

One of my favorite things about using Pendo is granular customer segmentation. I can filter down to a single customer account, pull their usage data, and understand exactly how they’re interacting with our product. Exporting this data is straightforward, and I love how it integrates with other tools we use across our tech stack.

Pendo’s in-app messaging capabilities deserve a shout-out. Whether it's tooltips, walkthroughs, or quick-start guides, I can push content directly into the product experience. This has been super effective for rolling out new features or helping users get unstuck without leaving the app. 

On the analytics side, Pendo gives me visibility into user behaviour that I honestly didn't think was possible without complex BI tools. I can see adoption trends, track usage patterns, and even collect user feedback, all within one platform. It makes my job easier and helps my team make smarter decisions.

However, Pendo isn't perfect. There have been times when the feedback dashboard didn't load correctly, forcing me to navigate through other menus just to find what I was looking for. And while the product delivers a ton of value, the price tag can be pretty steep, especially if you are looking to unlock its premium analytics and reporting features. 

Some of the most advanced capabilities, like API access and enterprise-level data visualizations, are gated behind high-tier plans, which might not be accessible for smaller teams.

I have also encountered a few minor bugs here and there, nothing that broke our workflows, but enough to notice. While Pendo is generally easy to use, we did face some challenges in terms of accessibility that required back-and-forth with their support team. 

But, that being said, Pendo provided customer segmentation capabilities, in-app guides for user retention, and software adoption data to improve the customer experience for your customers.

What I dislike about Pendo:

• Although Pendo can greatly improve the end-user experience based on customer responses, its export options can be limited, making it difficult to retrieve survey responses in a format suitable for detailed external analysis.
• I noticed that for some reason, the preview sometimes doesn't reflect the changes made to the storyboard.

What do G2 users dislike about Pendo:

"It takes a little bit of trial and error to use well. The knowledge base is pretty good, but as with all tools, it can be outdated."

- Pendo Review, Trina S.

4. Glassbox: Best for entry/exit page analysis and event replay

Glassbox is a customer intelligence solution which consolidates survey responses, customer feedback and location-wise data into your product analytics window. It also provides data regarding drop offs, engagement and digital interactions for businesses. 

I have been exploring Glassbox for a while, and honestly, it's been a bit of a game changer when it comes to understanding customer behaviour and user insights.

What I absolutely love about this tool is the session replay functionality. It's like having a front-row seat to every customer journey on our website. I can see exactly where users move their mouse, where they click, and even where they get stuck. This feature has been invaluable for optimizing user experience.

Another banger is the heatmaps. It allows me to visualize user engagement at scale. I can instantly spot which elements on our pages attract the most attention and which ones are being ignored. This has helped our design and product teams prioritize changes that truly matter.

What I even appreciate more is how easy it is to navigate Glassbox. Whether I am setting up filters to segment sessions by device type, customer journey stage, or geography, everything feels intuitive. The ability to search and filter sessions by user actions like “form submissions” or “error messages” has saved me hours. I no longer have to manually sift through endless data as the tool brings the most relevant sessions right to my fingertips.

I’ve used both the standard and premium plans of Glassbox, and I must say the jump to premium was well worth it. The premium tier unlocked AI-powered analytics that provided predictive insights about user drop-offs and churn risks. It also gave me access to cross-channel session stitching, allowing me to see a unified view of a customer’s journey across web and mobile apps, something that’s been crucial for our omnichannel strategy.

Of course, GlassBox does have its fair share of limitations. One of the biggest challenges I faced was the learning curve. While the tool is powerful, it can feel overwhelming at first, especially without adequate training. Many users, including myself, felt that there needs to be more structured onboarding and training resources. I had to spend quite some time experimenting before I felt confident in leveraging all the features.

I also felt that report customization needs a bit of improvement. Although the analytics are rich, creating custom reports with attached session replays felt a bit clunky. I often wish there were more flexible reporting templates or drag-and-drop functionality to simplify this process.

I’ve noticed that real-time session playback can lag, especially when dealing with high-traffic periods or sessions with a lot of data points. This sometimes disrupts the flow of my analysis, forcing me to refresh or wait for the session to load fully.

Several users also mentioned a lack of proactive alerting features. While Glassbox offers some alerts, they are not always as context-aware or actionable as one might expect. I personally would love to see more AI-driven alerts that tell me exactly what needs my immediate attention, rather than just flagging generic anomalies.

Finally, while the premium features are fantastic, they do come at a higher price point, which might not be justifiable for smaller teams or businesses just starting out. The subscription tiers could benefit from more flexible pricing or feature bundling to make the advanced capabilities accessible to a broader audience.

All in all, GlassBox is a reliable and agile product analytics tool that provides event tracking, user engagement metrics, and session replay for cross-platform devices. It’s AI-powered reporting facilities analyze the best-performing parts of your digital application and double down on what's working.

What I dislike about GlassBox:

• Even though GlassBox provides clean insights on how your product appears to users, the UI could have been a bit better and more engaging.
• I noticed that, currently, users can only look back at the last 30 days' records. It makes historical data tracking difficult.

What do G2 users dislike about GlassBox:

"Data accuracy is always the biggest topic when discussing Glassbox. I know that sessions are sampled, but sometimes questions about reliability might occur, especially when the delta between GA sessions and glassbox sessions becomes very high. Also, in the interaction maps section, sometimes the page loaded has empty slots, and it's a bit harder to understand what's behind."

- GlassBox Review, Antonio D. 

5. Fullstory: Best for visual session playback and error insights 

Fullstory is a behavioural analytics tool that product or digital marketing teams can utilize to understand their customer requirements and responses better. From real-time product optimization highlights to personalization of consumer metrics, Fullstory taps into real world customer data metrics to scale your lead generation.

What really impressed me was the session replay feature. Imagine being able to replay a user's journey from start to finish. Every tap, click, and every rage click (you know, when users furiously click something expecting it to work). Fullstory doesn't just show you the replay; it tags those rage clicks, dead clicks, and error clicks so you can fix what is broken before it costs you your conversions.

I've used the deep funnel analysis tools to track drop-offs in our checkout workflow, and being able to filter sessions by those behaviours saved us hours of guesswork.

The event tracking is next level. It captures every DOM event without needing engineering to set up manual tracking points. This means if tomorrow I want to know how many people click a random button buried deep in the site, Fullstory already has that data waiting for me.

I also love their search and segmentation capabilities. If you need to pull up all sessions where someone experienced a JavaScript error, Fullstory can do it.

If you want to build a segment of users who abandoned their carts after entering their shipping info, Fullstory provides the space for it. The search syntax can get pretty granular, and while that takes a bit of learning, once you get it, you feel unstoppable.

Now, speaking of learning, I won't say it's not something to be mindful of. There is a learning curve with the tool. When I first jumped in, I was overwhelmed by the massive amount of data available. But once you get the hang of it, it feels like unlocking cheat codes for user insights.

One thing worth mentioning is the interface. While powerful, it can feel a bit clunky at times, especially when managing notes or when trying to jump back to a specific session.  I have personally struggled with searching across multiple projects or umbrellas, as they call it, which makes multi-domain management a bit trickier than it should be. 

Honestly, I wish Fullstory had a Chrome extension that allowed users to keep a snapshot of their web usage insights and product analytics from a centralized browser..

Another thing that worries me is data retention limits. Fullstory stores data only for a certain period of time unless you pay more for extended storage. This can be frustrating when you are trying to compare user behaviour over longer cycles.

Speaking of pricing, this isn’t exactly a budget tool. Depending on the subscription tier, from the free plan to their more premium enterprise packages, you get access to different levels of session history, integration capabilities, and team collaboration features.

I’ve worked with both the Business and Enterprise tiers, and honestly, the difference in data retention and integration options (like with Salesforce, Slack, and Jira) really pays off when your team depends on cross-functional workflows.

Having said that, there are some features that I absolutely love, like privacy and compliance. It offers tools to automatically mask personal identifiable information (PII) to help stay GDPR compliant, which gives me peace of mind when dealing with sensitive customer data. 

In short, Fullstory is a reliable and agile behaviour analytics tool that helps you trace dropoffs, track events and sessions, and double down on customer satisfaction with advanced monitoring.

What I dislike about Fullstory:

• While Fullstory offers insights into every stage of the product funnel, it is a bit difficult for teams to level up beyond the introductory level.
• I observed that there seems to be a lot of complexity in arranging workflows. Teams want to see a list of all recent interactions and view them.  

What do G2 users dislike about Fullstory:

"The path of creating useful metrics is a little confusing so that if you're not sure what you're looking for at first, it's hard to tell if you're pulling in the right metrics."

- Fullstory Review, Beth D.

6. PostHog: Best for open source product analysis and funnels

PostHog is an engineering and product analytics tool that helps teams capture customer insights, build better software lifecycles, capture events, and track customer engagement via consumer analytics.

When I first started exploring PostHog, I honestly didn't expect it to be this versatile. What blew me away right off the bat was how it bundles multiple essential product operations into a single unified platform.

From product analytics to session replays to feature flags and data pipelines, it felt as if I had landed on a goldmine that didn't require stitching together a bunch of different services. The setup experience was surprisingly smooth. It can be integrated into the React application in under 10 minutes, which is a dream compared to the other analytics tools that take longer.

One feature I genuinely loved, and might sound a bit geeky, is the session replay capability. Watching real user sessions helped my team spot customer friction points almost instantly. You can cut down on churn just by seeing where the users get stuck. It's like having a direct window into user behaviour, which is priceless for a product team. I also found their screen recording feature to be equally impressive and handy.

Posthog’s detailed funnel and path analytics are worthwhile, too. You can use it extensively to track user flows in our onboarding process. The insights we got were pretty advanced, and even on the free version, it felt like PostHog offered insightful metrics, which usually are accessed with enterprise plans.

I also liked how they support self-hosting, which gives us more control over our data, something that's increasingly important in today's privacy-conscious world.

 However, there were some downsides to the platform. The dashboard, while powerful, can feel a bit overwhelming, especially for non-technical folks. I noticed my less savvy teammates struggling to figure out what metrics to track and how to set things up properly. 

The UX felt a little clunky in places, making the learning curve steeper than I'd like. For instance, when you add your Postgres database to the data pipeline, it couldn't immediately figure out how to utilize that data. It took some trial and error, and honestly, it felt as if it could have been a bit more intuitive.

I also wish there were clearer guidance on in-app verification to confirm if we had configured things correctly. Another gap I noticed was around OpenFeature support. There is a mention of open-source integration, but I couldn't find clear information on whether PostHog provides it or not.

When it comes to pricing, PostHog does a great job of scaling costs based on usage, which felt fair. However, once you start exploring premium features, like advanced user cohorts, granular access control, or higher session replay limits, you’ll likely need to move to one of their paid plans.

PostHog offers multiple tiers, but like most SaaS products, the details around what’s included at each level could be a bit clearer. I’d recommend getting in touch with their sales team if you’re considering scaling beyond the free tier.

Overall PostHog offers granular customer insights, engineering support, and event tracking to consolidate user actions into real-time product metrics and improve your adoption seamlessly.

What I dislike about PostHog:

• While PostHog offers a seamless user experience and tracks analytics easily, the documentation might be hard to follow and out of date.
• I noticed that some of the most advanced features have a bit of a learning curve, especially for people who are new to data analysis.

What do G2 users dislike about PostHog:

"It can be a bit overwhelming at first because it offers a lot of features, such as session replay and event flags. You’ll need some time to understand how everything works and what each feature does."

- PostHog Review, Muzammil K.

7. Userpilot: Best for in-app guidance and product-based messaging 

Userpilot is an all-in-one platform that provides session replays, engagement metrics, funnels, in-app surveys, and customer service to increase your product adoption. These metrics enable you to visualize your consumer workflows and build better consumer engagement and pipeline.

Userpilot positions itself as a no-code product adoption platform, and for the most part, it lives up to that promise. 

What I immediately loved was how ridiculously fast I could set up in-app experiences without involving our dev team. The flow builder is intuitive — drag and drop simple. It is easy to build personalized onboarding workflows and tool tips in minutes.

One of my favorite features is the resource center, which acts as an in-app hub where our users can self-serve information, access tutorials, or even chat with our support team, all without leaving the platform.

Userpilot also shines when it comes to behavioral analytics and user insights. The audience targeting is laser-focused. I could trigger experiences based on user attributes, behaviour, or events tracked through the native integrations with tools like Segment, MixPanel, and Amplitude.

This made our engagement campaigns feel super contextual and timely. Plus, their heatmaps and session replays gave me a crystal-clear picture of how users navigate our app, which made flow optimization almost effortless.

Now, let’s discuss the cons. Userpilot’s flow management and resource center scaling started to feel a bit clunky as the setup grew. It's easy to manage when you have a handful of experiences, but as the library expands, organizing and locating specific files becomes time-consuming.

Also, some users on my team noticed a lag between experience steps, which, although minor, can disrupt the fluidity of an onboarding journey.

As for the pricing, Userpilot isn’t exactly cheap. Once you move past their basic Starter plan, which is pretty limited in terms of feature depth and monthly active user (MAU) limits, you quickly find yourself looking at their Growth and Enterprise plans.

These plans unlock premium features like advanced segmentation, multi-language support, custom event tracking, and dedicated customer success management. While these features are powerful, the price jump feels steep, especially for smaller teams or startups.

Overall, user pilot is an essential cog in your product analytics strategy. It offers real-time engagement metrics, heatmaps, in-app service, and session replays to gauge your funnels and analyze drop-offs to improve the end user experience.

What I dislike about Userpilot:

• While Userpilot provides analytics to create great UX, some advanced features (like event-based triggers) require a bit of learning and experimentation.
• While the platform is powerful, analytics could be a bit more robust. The team would have loved deeper insights into user interactions to refine the experience.

What do G2 users dislike about Userpilot:

"It's not a dislike, but implementing a few certain functions and roles still requires dev involvement, which can be challenging if you don't have the technical skills or have devs easily available to assist you. It depends on your service/website, so this might not apply to everyone."

- Userpilot Review, Ivan S.

Best Product analytics software: Frequently asked questions (FAQs)

1. What are the best tools for product analytics?

The best product analytics tools include MixPanel, Amplitude, and Heap. They offer advanced event tracking, user journey analysis, and scalable data infrastructure.

2. Is Tableau a product analytics tool?

No, Tableau is a business intelligence (BI) and data visualization tool. While it can visualize product data, it lacks built-in event tracking, user journey mapping, and behavioural analytics that other specialized product analytics tools provide.

3. Is Google Analytics good for product analytics?

It depends. Google Analytics can be great for understanding web and app traffic patterns, user acquisition, and engagement metrics. However, when it comes to deeper product analytics, a dedicated tool like Mixpanel or Amplitude works better..

4. How do your product analytics tools handle multi-touch attribution across web, mobile, and offline channels?

Product analytics tools provide event tracking for consumers spread across different channels, identity resolution, and cross device stitching to provide accurate multi-touch attribution. These metrics are consolidated on one single dashboard which tells you about your app performance across different devices and channels.

5. Can a product analytics tool scale with enterprise-level data ingestion volumes and support real-time analytics?

Yes, our architecture is built on distributed computing with auto-scaling data pipelines. We offer real-time data processing with sub-second latency, making it ideal for enterprise-scale user activity tracking and analysis.

6. How does product analytics software ensure compliance with GDPR, CCPA, and other data privacy regulations?

Product analytics software abides by local, state, and federal laws and offers an end-to-end data security framework to align itself with GDPR, CCPA, HIPAA, and other privacy regulations. It also offers consent-level frameworks, data-regulation APIs, and region-specific data storage.

7. What integration options are available with CRM, CDP, and data warehouse systems?

Product analytics tools offer out-of-the-box integrations with leading CRMs, CDPs, and other data warehouses via REST APIs, webhook automation, and reverse ETL. This enables seamless bi-directional workflow, which powers customer data engagement.

Customer engagement = conversions 

During my analysis, I delved into the complexities of product analytics tools to learn which company segments, based on their current data pipelines, software development lifecycle, and customer behaviours, will excavate the maximum ROI out of these tools to engage and convert better.

Before deciding on the ideal product analytics tool, draw a clear roadmap of client requirements, developer bandwidth, network compatibility, and upcoming product versions or releases, which will give you a nice foreground to map your customer marketing, engagement, and conversion possibilities.

Check out my colleague's recent analysis of email marketing tools and real-time user reviews by G2 experts to help score better deals with email marketing campaigns in 2025.