5 alternatives to Heap for holistic product analytics

Heap emerged as a pioneering product analytics tool aimed at helping businesses understand how users interact with their digital products and services,

By offering automated, self-service product instrumentation and analytics, Heap empowered teams to analyze user behavior, identify pain points, and optimize the product experience.

But today’s product-led-growth-focused companies want flexible insights into the full customer journey across multiple touchpoints, channels, and interactions, both within and outside the product.

First-generation product analytics tools like Heap can’t natively provide this 360 perspective.

This leads to complex, expensive workarounds or fragmented insights and missed opportunities for data-driven growth. That’s why many future-focused companies are seeking more holistic, modern alternatives.

In this article, we’ll show you what to look for in a Heap alternative and talk you through five top Heap competitors so you can make an informed decision.

What to look for in a Heap alternative

Let’s start with some important context on the rapidly evolving analytics landscape and what to keep in mind when evaluating Heap alternatives.

Why consider alternatives to Heap?

Data-driven, product-led companies understand the need for a holistic, flexible approach to analytics that will give them insights on the full customer journey, so they can identify blockers and spot opportunities for growth.

Heap's automated event tracking makes it easy to analyze every movement in your user interface. However, its siloed product-instrumentation approach and lack of exploratory capabilities means organizations end up with underpowered, fragmented analytics. Workarounds involve ETL and reverse-ETL tools and duplicated instrumentation data, leading to operational inefficiencies, technical debt, and increased costs.

Here are the main reasons future-focused organizations should consider alternatives:

1. Lack of cross-functional visibility

Heap's data model is centered around tracking user interactions within the product, with limited capabilities to incorporate data from external sources or integrate with other tools.

Since it’s not optimized to work off modern data architectures like data warehouses and data lakes, it limits companies looking to leverage single-source-of-truth, warehouse data to understand the customer journey across multiple touchpoints.

2. No single source of truth for full customer journey analyses

Workarounds to integrate Heap’s product instrumentation data with business data generally involve labor-intensive ETL or reverse-ETL pipelines, data duplication, and SQL-querying in business intelligence tools like Looker. As well as creating complexities and delays, this can mean organizations end up with inconsistent data as well as data governance issues.

3. Limited flexibility and customization

While Heap offers easy-to-use report templates, it’s challenging to create custom reports or views. There is limited data exploration and ad hoc analysis possible, meaning teams can’t quickly test hypotheses or uncover unexpected insights to derive actionable knowledge from their data. Dashboards are also limited, with no comparative view of product experiments and A/B tests.

4. High total cost of ownership (TCO)

Heap’s automated data capture features mean you end up collecting and storing high volumes of potentially irrelevant data, and the pricing model is built around session volumes rather than insights. This means it’s tricky to control trade-offs between cost and performance based on requirements. The need for additional ETL or reverse-ETL pipelines to explore data in BI tools like Looker also pushes up costs and complexity.

5 top Heap alternatives for product-led growth

The ideal Heap alternative for your organization will depend on your specific business needs, available resources, and existing tech stack.

When evaluating each different tool, you’ll want to consider:

• Ease of use — ensuring the software has an intuitive interface and a minimal learning curve for both technical and non-technical teams.
• Flexible analytics capabilities — such as whether it’s possible to do ad-hoc analytics, advanced data exploration, custom visualizations, and tailored reporting.
• Scalability and cost-effectiveness — checking that the pricing model aligns with your growth projections and data volume requirements.
• Integration with your business tools and data stack — including whether it works directly off your composable CDP warehouse or requires point-to-point integrations with different business systems.
• Data governance, security, and compliance — ensuring that the tool adheres to all relevant regulations and considering whether a need for data duplication would compromise data integrity.

To simplify your decision process, we’ve put together a comprehensive overview of 5 leading Heap alternatives, with an overview of features and a breakdown of benefits, limitations, and pricing.

1. Optimizely Warehouse-Native Analytics

Optimizely Warehouse-Native Analytics is a next-generation, warehouse-native product and customer journey analytics platform designed for modern data architectures. It enables rich self-service analytics across various data sources, including product usage data, marketing campaigns, sales interactions, and customer support engagements. Optimizely Warehouse-Native Analytics is a powerful Heap alternative for businesses seeking a comprehensive, reliable, and cost-effective view of the customer journey across all touchpoints.

Key features

• Leverages your existing data warehouse as a single source of truth across all touchpoints
• Advanced cohort, funnel, multi-actor, and behavioral analytics
• Wide range of self-service report templates
• Powerful self-service ad-hoc data exploration capabilities
• Flexible data modeling across all tables in your data warehouse
• No data duplication needed to merge multiple product and business event streams

Benefits Of Optimizely Warehouse-Native Analytics as a Heap alternative

• Like Heap, Optimizely Warehouse-Native Analytics provides advanced cohort, funnels, retention, and predictive analytics, plus a wide range of easy-to-use templates.
• As a warehouse-native platform, Optimizely Warehouse-Native Analytics goes beyond product usage insights to natively integrate warehouse data from all user/customer touchpoints.
• Unlike Heap, Optimizely Warehouse-Native Analytics enables self-service ad-hoc analysis, custom visualizations, and tailored reporting, empowering teams to get the answers they need without costly data transformations and engineering support.
• Optimizely Warehouse-Native Analytics avoids Heap's event-based pricing challenges with a seat-based model that scales seamlessly even as you grow.
• By removing the need for data duplication and ETL or reverse-ETL pipelines, Optimizely Warehouse-Native Analytics ensures a single, consistent source of truth — and protects data security and governance.

Limitations Of Optimizely Warehouse-Native Analytics as a Heap alternative

• Requires an existing data warehouse infrastructure, so it’s not suitable for businesses without a centralized, modern data stack including a composable CDP.
• There’s a small learning curve for users new to the platform to get the most from its flexible modeling capabilities.

Pricing

Optimizely Warehouse-Native Analytics offers custom pricing, exactly gitting your need

Best for

Optimizely Warehouse-Native Analytics is ideal for data-driven organizations with a modern data stack.

It’s particularly well-suited for companies looking to empower teams to access advanced, ad hoc analytics and gain 360° insights on the full customer journey. Optimizely Warehouse-Native Analytics's flexible modeling, warehouse-first approach makes it a strong choice for organizations seeking to drive product-led growth.

2. Amplitude

Like Heap, Amplitude is a first-generation product analytics tool that enables businesses to understand user behavior on both web and mobile products. However, Amplitude has more granular customizations for setting up and tracking user events.

Key features

• Extensive behavioral analytics and event tracking
• User path and funnel analysis
• Cohort analysis and user segmentation
• A/B testing and product experimentation analytics
• Visualizations and customizable dashboards
• New segment testing

Benefits of Amplitude as a Heap alternative

• Each user interaction event can be customized according to your specific use cases and tracked across different journeys and stages, providing more flexibility and granularity than Heap’s automated approach.
• Amplitude's AI/ML-assisted behavior clustering allows users to build cohorts without predefined rules, based on similarities in event behavior.
• Runs data reliability checks and sends alerts when anomalies are detected in the data to quickly resolve data management issues.
• Many users find Amplitude’s UI (after setup) easier to navigate.
• Due to the demand for warehouse-native analytics, Amplitude will offer Snowflake-native options in 2024 (with limited capabilities).

Limitations of Amplitude as a Heap alternative

• While Heap automatically captures all product interactions with no code needed, Amplitude requires setup to predefine which events and behaviors you want to track.
• Though Amplitude offers some point-to-point integrations, like Heap, it’s not generally a warehouse-native solution, so bringing together product, customer, and business data still requires ETL or reverse-ETL pipelines and duplicated data.
• Doesn’t support native ad hoc data visualization and exploration.
• As with Heap’s event-based model, Amplitude's MTU-based pricing could become expensive as companies scale.
• Amplitude’s new Snowflake-native option is a backend retrofit that still involves data duplication for hybrid deployments and offers limited reports, flexible modeling, and ad hoc visualization.

Pricing

Amplitude's pricing structure consists of four tiers: a free plan, a "Plus" plan priced between $49 and $2,520 per month for up to 3,000 monthly tracked users (MTUs), and two higher-level tiers, "Growth" and "Enterprise," with pricing for these only available on request.

Best for

Amplitude is best for smaller companies that want to get started with basic product analytics for the first time, don't have mature data infrastructure, and want a simple packaged solution. It may not be the best option for companies with a modern, composable data stack, large data scale, business complexity, and looking to do more than very basic feature usage analysis.

3. Mixpanel

Like Heap and Amplitude, Mixpanel is a first-generation, vertically-integrated product analytics platform that focuses on user behavior and engagement within a product. It provides detailed insights into how users interact with mobile and web products based on instrumenting data for usage and intrinsic events.

Key features

• Granular event-tracking
• Aggregated user profiles
• Funnel and path analysis
• User segmentation
• A/B product experimentation analytics
• Direct messaging features to communicate with user segments

Benefits of Mixpanel as a Heap alternative

• Mixpanel offers an intuitive interface that prioritizes ease of use, and an extensive template library, making it easier for non-technical users to derive insights for common reports.
• Mixpanel allows users to define and analyze custom events, which requires more resources to set up but ultimately provides more flexibility than Heap's auto-capture approach.
• Unlike Heap, Mixpanel offers dashboards with views of A/B tests and product experimentation.
• Mixpanel has advanced capabilities for capturing user-level information as well as event and session data.

Limitations of Mixpanel as a Heap alternative

• Lacks Heap’s automated data capture, which means setting up events is more resource-intensive.
• Like Heap, Mixpanel requires data to be duplicated in and out of the platform to get additional business context for product analytics, which can compromise data integrity and security.
• While the most common reports are simple to use, Mixpanel doesn’t support ad hoc visual data exploration, limiting the insights it natively provides.

Pricing

Mixpanel has three separate event-based pricing plans: a free "Starter" plan (up to 20M events per month), a "Growth" plan starting at $24/month (up to 300M events per month), and a custom "Enterprise" plan with pricing only available on request.

Best for

Mixpanel is best for smaller companies that want to get started with basic product analytics for the first time, don’t have mature data infrastructure, and want a simple packaged solution. It may not be the best option for companies with a modern, composable data stack, large data scale, business complexity, and looking to do more than very basic feature usage analysis.

4. Pendo

Distinct from Heap, Pendo is a full-scale product management and adoption platform with an in-built product analytics module. It offers a range of features to help businesses understand product usage and user behavior and allows them to survey users and publish in-app guides to increase feature adoption.

Key features

• Usage analytics identifying key usage patterns and trends
• Targeted, contextual user guidance
• Gather user feedback directly within the product
• Session replays for individual users
• Product usage analytics across multiple products or portfolios
• AI tech that provides contextual advice for users based on metrics

Benefits of Pendo as a Heap alternative

• Like Heap, Pendo offers automated data capture, meaning it’s easy to set up and produces a wide range of data points to explore.
• While Pendo has features like user guidance features that help businesses onboard users and drive adoption, its product analytics stack is limited.
• Pendo enables businesses to collect voice-of-user feedback directly within the product.
• Pendo allows for product analytics across multiple portfolios, which is a plus for multi-product businesses.

Limitations of Pendo as a Heap alternative

• Pendo's automated data capture has the same limitations as solutions like Heap in terms of potential data bloat and lack of granular control.
• Product analytics aren’t its main feature; it operates on a limited set of data attributes and lacks customizability.
• It doesn’t allow you to compare in-product user paths for different user cohorts or segments.
• Pendo's pricing model is based on monthly active users (MAU), which can become expensive for businesses with a large and growing user base.

Pricing

Pendo’s MAU-based pricing has three plans: a free version (up to 500 MAUs) and a “Growth” and “Portfolio” plan, both of which have custom monthly active user limits and pricing only available on request.

Best for

Pendo is best suited for businesses looking for basic product analytics integrated with product adoption features like in-app guidance and user feedback, as part of a comprehensive product management strategy. However, companies looking for high-powered, customizable, and advanced analytics should consider other alternatives.

5. Kissmetrics

Kissmetrics is a product and marketing analytics platform that aims to offer e-commerce sites a fuller view of the customer journey and help them to improve user engagement.

Key features

• Attribution of user behavior touchpoints across multiple channels
• A/B testing and experiments for marketing campaigns and product experiences
• Flags risk of churn based on behavioral data and predictive analytics
• Targeted email automation features

Benefits of Kissmetrics as a Heap alternative

• Straightforward mapping of the user journey that’s useful for early-stage businesses and non-technical stakeholders.
• Multichannel analytics improve attribution for informed marketing and product choices. Kissmetrics offers easy integrations with a range of e-commerce tools.

Limitations of Kissmetrics as a Heap alternative

• Lacks the depth of product analytics found in Heap or other alternatives.
• Doesn’t support custom use cases, advanced data extraction, or ad hoc analyses.
• Hyper-focused on the needs of e-commerce companies.
• Like Heap, Kissmetrics primarily uses an event-based pricing model, which can become expensive as data volumes grow.

Best for

Kissmetrics is best suited for early-stage, ecommerce businesses looking to integrate basic product and user analytics with marketing metrics. However, for companies outside of this space looking for advanced, customizable analytics or ad hoc data exploration, it’s probably not the best option.

A Future-Focused Product Analytics Solution

While first-generation product analytics tools like Heap were groundbreaking when they emerged, their siloed approach and architectural limitations mean they’re not always the best choice for modern data needs.

Choosing the right product analytics tool is critical for identifying growth opportunities and removing user blocks. The ideal solution should provide powerful, flexible analytics that can give you 360 insights into the entire customer journey.

Built directly on your warehouse, Optimizely Warehouse-Native Analytics is the future-focused analytics platform designed to enable product-led growth. By leveraging your existing centralized data warehouse as a single source of truth, Optimizely Warehouse-Native Analytics avoids data duplication inconsistencies and streamlines your data governance. Optimizely Warehouse-Native Analytics’s intuitive, self-service tools empower teams to access rich behavioral insights alongside customer, marketing, sales, and support data — pivoting between pre-built report templates, ad hoc data exploration, and flexible data modeling.

Additionally, with Optimizely Warehouse-Native Analytics, you can go beyond templated reports and get deep insights into customer behavior.

Optimizely Warehouse-Native Analytics's flexible, warehouse-first approach is ushering in the next generation of customer-focused product analytics.

Experience the power of Optimizely Warehouse-Native Analytics for yourself with a no-risk free trial