Selecting the right product analytics tool is critical for teams that need to iterate quickly, reduce churn, and grow adoption. In 2025, the landscape is shifting toward platforms that offer fast insights, secure architecture, and strong usability for both technical and non-technical users.
This guide compares today’s top product analytics platforms across features, reviews, and G2 satisfaction scores to help you find the best fit for your data analytics needs.
How Product Analytics is Transforming and Evolving – and Why It Matters for You
According to McKinsey, companies that effectively use product analytics outperform their peers by 85% in sales growth. This is no longer a luxury – it’s a prerequisite for having a strategic advantage over your competitors, especially for digital-native companies.
Kubit was recognized again as a Representative Vendor in the Gartner 2025 Market Guide for Product Analytics.
Gartner’s 2025 Market Guide reinforces the shift:1
- By 2028, 60% of product leaders will improve automation and product decision-making using user behavior insights obtained through product analytics—a 3x increase from 2025.
- By 2027, 90% of technology marketers will use product analytics to understand digital user behavior for acquisition, retention, and advocacy, up from just 49% in 2025.
This massive jump signals that product analytics tools are becoming foundational to how digital-first companies operate, not just analyze.
How Top Product Analytics Tools Stack Up
| Platform | Digital Analytics | Mobile App Analytics | Quality of Support | Ease of Doing Business |
| Kubit | 8.6 | 9.4 | 9.7 | 9.5 |
| Amplitude | 8.3 | 8.4 | 8.7 | 8.8 |
| Mixpanel | 8.5 | 8.7 | 8.4 | 8.8 |
| Heap | 8.3 | 8.3 | 8.7 | 8.8 |
On the G2 review platform, Kubit outperforms all other vendors in every category listed, scoring the highest in Digital Analytics, Mobile App Analytics, Quality of Support, and Ease of Doing Business, among other categories. It’s regarded as a top-rated platform for both functionality and customer satisfaction.
One G2 reviewer said: “Kubit’s customer support is second to none. Whether it’s ingesting new data, helping to build queries and reports, or talking about new feature enhancements, the Kubit team is always ready to listen. I am in Kubit at least 2-3 times a week and encourage all my product teams to do the same.”
1. Kubit – Fast, Transparent Insights without Data Duplication
Kubit is a warehouse-native platform that analyzes data directly from your cloud data warehouse—no data ingestion, no ETL headaches, and no data pipelines to manage. Teams of all technical backgrounds can run event-based queries, cohort analyses, and AI-powered natural language queries in seconds.
One Data Analyst and Kubit customer on G2 shared:
“The best part about Kubit is that it fully solves the problem of democratizing behavioral data to the rest of the organization. People with less than average analytical skills or who completely lack SQL knowledge can now edit reports themselves and find the insights they need.”
Key reasons why teams switch to Kubit:
- Restored trust in their data with full SQL-visibility
- Same-day setup – no engineering bandwidth required
- Warehouse-native model preserves one source of truth for their data
- AI-powered insights across the full customer journey
AI Is Only as Smart as Your Data
AI is revolutionizing the way teams interact with analytics. But without clean data, clear governance, and a secure foundation, even the most advanced models generate noise instead of insight. That’s why AI alone isn’t enough.
Kubit takes a fundamentally different approach. With Kubit Lumos, teams get powerful AI-driven insights, detect anomalies, and uncover insights more effectively – without added complexity. No data duplication or black boxes. This foundation ensures AI actually protects data security, improves data quality, and delivers transparent insights.
Kubit also excels at customer journey analytics, helping teams identify exactly which behaviors drive conversion, retention, or churn – without requiring multiple tools stitched together or siloing your existing data.
2. Amplitude – Widely Adopted, but Costly and Rigid
Amplitude is a familiar name in product analytics. It offers strong cohorting and retention tools and is favored by data-heavy teams. But multiple reviews highlight issues with flexibility, permissioning, and the ability to customize or interpret results without technical help.
Common complaints:
- Data discrepancies between your database and Amplitude happen pretty often. One common reason is event delays since Amplitude processes data differently, sometimes with batching or ingestion lag.” – Amplitude user feedback
- “There are no features to query the data effectively or answer questions without having to pay for a very expensive add-on.” – Reddit user
- Not warehouse-native – the data must be moved or duplicated
- One Amplitude user on Reddit said: “Our Amplitude setup is so disorganized that I can’t trust any data point, and it’s starting to significantly impact product decisions. We’ve ended up with inconsistent event names, broken user IDs that don’t unify across devices or sessions, and missing or misfired event properties that render our funnels and segmentation useless.”
- Higher cost of ownership and reliance on engineers
Amplitude’s inability to natively integrate with all data warehouses and lack of SQL access make it incompatible with many of today’s product and data teams.
3. Mixpanel – Strong Visuals, but Scaling Brings Challenges
Mixpanel offers dynamic charts and interaction tracking but comes with its own limitations around data scaling and governance.
User-reported challenges:
- “The downside of Mixpanel is the poor adoption of it at my org, and the cost of the thing” – Reddit User
- “The interface is not intuitive, making it challenging to access desired functionalities effectively.” – G2 Reviewer
- Requires strong data hygiene and protocol familiarity
- Difficult to unify with your warehouse as a source of truth. The data must be in a certain format—and ingested.
- “I find that there are discrepancies in the data […] and the events tracked by Mixpanel. I don’t really trust Mixpanel … I want to be able to see the raw data.” – Reddit user
Mixpanel’s pricing model and data governance limitations create friction for teams with growing data needs.
4. Heap – Autocapture and Customer Journey Analytics at a Cost
Heap captures every user action automatically, making it appealing for fast implementation and customer journey analytics. But data volume quickly becomes an issue.
Real user feedback:
- “Heap’s automatic event capture creates data bloat that drives up costs.” – Statsig
- “Data storage challenges. If you capture everything, you need the infrastructure (and budget) to handle that data at scale.” – Usermaven
- G2 users noted “limited features out‑of‑the‑box…requiring additional tools for complex queries”
Heap’s all-in-one capture model is valuable, but it can potentially be overwhelming and become expensive over time.
5. PostHog – Built for Devs, Harder for PMs
PostHog bundles product analytics, session replay, feature flags, A/B testing, and more into one open-source package. It’s beloved by technical users, but often too complex for product managers or marketing teams.
User concerns from G2:
- “I actually find it really difficult to get what I need from PostHog’s analytics.”
- “We also tried PostHog, much too complicated for most of our use cases.”
- “PostHog may have limitations in enterprise-level support and advanced analytics capabilities compared to more established competitors.”
PostHog also lacks built-in revenue reporting and user composition charts, adding friction and limitations for business teams.
Final Thoughts
The best product analytics tools in 2025 do more than visualize behavior. They help teams take action – quickly, securely, and at scale. Kubit stands out for its warehouse-native approach, intuitive self-service capabilities, and ability to support deep customer journey analytics with minimal setup.
Request your custom demo of Kubit to see how you can transform your idle warehouse data into complete customer journey insights – without duplication, complex ETL, black boxes, or engineering bandwidth.
- Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose ↩︎
