5 best product analytics tools for 2024

A product analytics tool is a strategic asset that enables businesses to optimize their products, enhance user experiences, and stay competitive in dynamic markets. It forms the foundation for data-driven decision-making and continuous improvement in the product experience.

The task of choosing the right product analytics tool can be challenging. The market is saturated with options, and the tools are similarly matched in terms of their capabilities. The true differentiation comes down to a tool’s ability to address your specific business use cases and fit into your technology stack.

If you are looking for a product analytics tool, here are 5 that should make it on your list in 2024.

Product analytics tools fall into two categories:

1. Fully vertically-integrated SaaS applications
2. Warehouse-native product analytics platforms

Amplitude, Mixpanel, and Heap are examples of fully vertically-integrated SaaS applications. These tools enable companies to capture and manage data and perform analytics. These events can include user interactions, system events, clicks, logins, purchases, etc. They can work with data warehouses, but only as a way to move data in and out of their SaaS application. They cannot compute directly on the data warehouse.

Warehouse-native product analytics platforms work directly on top of data warehouses, enabling them to go beyond basic product insights and delve into deep customer and behavioral analysis. They emerged to solve many of the challenges posed by the fully vertically-integrated SaaS applications.

Some key differences between these two:

• Warehouse-native product analytics tools do not require hours of coding in SQL to answer your next question.
• Fully vertically-integrated SaaS applications typically have an event-based pricing model, which can get very expensive.
• Fully vertically-integrated SaaS applications require point-to-point integrations, leading to data duplication and inconsistent insights.

While the evaluation criteria you prioritize depend on your business use case, as a general rule of thumb, these 5 things are important for any reliable product analytics tool.

Ease of use: To start, look for a clean UI, clear onboarding steps, and supportive guides for troubleshooting. Equally important is the product's usability for teams. Seek collaboration features such as report sharing and user permissions within the platform.

Ecosystem: Take stock of the business systems that contain data about interactions customers have with you and your product. With fully vertically-integrated SaaS applications, you will need to look for all the point-to-point, version-specific integrations. With warehouse-native product analytics tools, these headaches go away.

Scalability and performance: Assess the scalability of the platform to handle your current and future data volumes. Consider factors such as data processing speed, storage capacity, and the ability to scale as your business grows.

Data governance: Data governance is a set of internal policies and standards that monitor how data is gathered, stored, processed, and disposed of. You can evaluate if a product analytics tool has data governance by:

1. Checking data quality management features
2. Assessing data lineage and metadata handling
3. Verifying data access controls
4. Ensuring audit trails and logging
5. Evaluating governance policy support

Security and compliance: Check if the platform adheres to industry-standard security practices and compliance regulations.

NetSpring is purpose-built for product and growth teams to self-serve funnel, path, cohort, retention, and exploratory analysis across any product or customer business data in the data warehouse.

Key product features: Product and Customer Analytics (pivot seamlessly, slice and dice), Self-service capabilities (template library), Flexible modeling (model across all tables), Business-impactful metrics, Consistent insights, Data governance and integrity.

Pros:

• Low, predictable pricing (starts at $49/month)
• Single source of truth
• Assured data governance
• Reduced TCO

Cons:

• Business teams need buy-in from data teams
• Additional vendor agreement required for instrumentation
• Small learning curve for UI

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Amplitude is a fully vertically-integrated SaaS application and one of the earliest in the space.

Key product features: Behavioral Analytics, User Path and Funnel Analysis, Cohort Analysis, A/B Testing (Experiment feature), Collaboration and Workflow, Customer Data Platform (CDP).

Pros:

• Intuitive UI
• Comprehensive behavioral analytics
• Customized event tracking
• Anomaly detection
• Direct integrations

Cons:

• Data duplication required
• No support for ad hoc visual data exploration outside Amplitude
• Significant dev bandwidth for setup
• Event-based pricing becomes expensive

Mixpanel is also a fully vertically-integrated SaaS application. It stands out from competitors by prioritizing ease of use.

Key product features: Event Tracking and Analysis, Funnel Analysis, User Segmentation and Retention, A/B Testing, Notifications and Messaging.

Pros:

• Intuitive UI
• Mobile analytics focus
• Flexible event tracking
• Extensive template library
• Major tool integrations

Cons:

• Compromised data integrity due to duplication
• No ad hoc visual exploration
• High dev bandwidth for setup
• Scalability costs

FullStory now offers some basic product analytics capabilities, but is best known for session replay and its digital experience analytics platform.

Key product features: Session Playback, Click Maps and Heatmaps, Error Tracking and Reporting, Searchable User Sessions, Conversion Analytics, Frustration Signals.

Pros:

• Quick start
• Intuitive dashboard
• Web and mobile analytics
• Collaboration features
• API library

Cons:

• Limited analytics feature set
• Privacy concerns
• Limited integrations
• Expensive session-based pricing

Heap is another fully vertically-integrated SaaS application that helps businesses track and analyze user interactions.

Key Product Features: Auto Event Tracking (Autocapture), Retroactive Analysis, Funnel Analysis and Segmentation, Effort Analysis, Session Replay.

Pros:

• Event Visualizer (point-and-click)
• Web and mobile support
• Activation integrations

Cons:

• Limited template library
• Data duplication for business context
• Dependent on Data/BI teams for SQL
• Session-based pricing costs

Due to their architecture, fully-vertically integrated SaaS applications will always lack the data access, depth of analytics, customization, and scalability needed by modern data-driven businesses.

Companies are investing in a centralized data strategy to tackle such challenges head-on. If your company already has a data warehouse or is investing in one, a warehouse-native product analytics tool is the ideal choice.

In order to evaluate product analytics tools effectively, consider the following:

1. Ease of use
2. Ecosystem
3. Scalability and performance
4. Data governance
5. Security and compliance