What is Amplitude?

Amplitude is a product analytics tool designed to help teams turn raw user data into meaningful insights. It enables organizations to track user behavior, understand customer journeys, and make data-driven decisions about their products. With features like real-time analytics, user segmentation, retention analysis, and conversion tracking, Amplitude aims to provide a comprehensive view of how users interact with digital products.

While Amplitude offers valuable product analytics, there are several key reasons to consider alternatives:

1. Complex Setup and Maintenance: Implementing Amplitude requires extensive planning and manual event tagging, making it time-consuming and resource-intensive. Each new event requires a repeat of the setup process, hindering agility in responding to business needs.
2. Data Moving: Amplitude is a vertically integrated SaaS application focusing on product-related event data. Users often need to engage in time-consuming reverse ETL processes (moving data out of their data warehouse) to analyze the complete customer journey, leading to fragmented analytics and a lack of holistic insights.
3. High Costs: Amplitude’s event-based pricing can become expensive as your product scales. Companies often pay for unused events, and managing these costs can be cumbersome and strain budgets.

Alternatives to Amplitude

Below you can see 5 alternatives that can help you overcome these reasons. The alternatives are divided into 2 groups:

• Third- party applications
• Warehouse-native self-service analytics tools

Warehouse-native analytics solutions are new to the product and marketing analytics market. They work on top of your existing data infrastructure, such as a data warehouse, data lake or even on top of your operation database. Their main advantage is cost efficiency and real-time access to first party data. Their main disadvantage is that they require careful data modeling and optimization to operate fast on top of the cloud data warehouses.

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*Assuming  1M active users or visitors, 1 user generates 50 events per month, and 10 product managers.

Traditional product analytics alternative

Lets get started with the traditional data analytics solutions.

Mixpanel

With Mixpanel, you can leverage real-time analytics to gain deeper insights into user behavior, enhance engagement, and drive product growth.

• Custom Dashboards: Create multiple dashboards tailored to the metrics and events that matter most to your team, allowing for focused analysis and reporting.
• Automated Insights: Quickly generate reports and utilize industry templates to uncover user preferences and behaviors, streamlining your analysis process.
• Event Recommendations: Accelerate your setup with intelligent, automated suggestions based on your industry, helping you get started efficiently.
• Anomaly Detection: Monitor trends and identify unexpected changes in user behavior. Set alerts to catch potential issues before they escalate into larger problems.
• A/B Testing: Experiment with different ideas and optimize user experiences within the platform. Use insights from your tests to make informed decisions that enhance product performance.

These powerful tools enable you to understand your users at every stage of their journey, making Mixpanel a strong choice for your product analytics needs!

Pendo

Pendo is a powerful product analytics platform that helps businesses track user engagement and behavior within their applications. It captures comprehensive usage data through event tracking, enabling teams to identify areas for optimization and improve the overall user experience.

• Event Tracking: Monitor user interactions to understand which features are most utilized and which are underperforming.
• Paths and Funnels: Analyze user journeys and conversion rates to identify drop-off points and optimize the customer journey.
• Retention Analytics: Track cohort retention over time, allowing businesses to measure user loyalty and engagement.
• In-App Guidance: Utilize targeted messaging and onboarding flows to enhance user engagement and drive adoption.
• Integrations: Seamlessly connect with other platforms like Salesforce and Hubspot for a holistic view of customer interactions.

Pendo's combination of product analytics, in-app guidance, and feedback collection provides a comprehensive solution for enhancing user experiences.

Warehouse-native analytics alternatives

Mitzu

Mitzu.io is a warehouse-native analytics platform designed specifically for product, marketing, and revenue analytics. It streamlines data analysis, making it accessible even for teams without dedicated data resources (Companies with 0 or 1 data analyst). With Mitzu, you can automatically generate SQL queries, allowing you to focus on insights rather than coding.

• Warehouse-Native Analytics with Automatic SQL Query Generation: Mitzu provides a holistic view by merging product data with marketing and revenue insights directly from your data warehouse. It simplifies data analysis by automatically generating SQL queries based on your inputs, eliminating the need for extensive SQL knowledge.
• User Journey and Retention Analysis: Track user interactions across various touchpoints to understand their journey and improve retention strategies.
• Campaign Conversion Tracking: Measure the effectiveness of your marketing campaigns by tracking conversion rates and user engagement.
• Individual User Lookup and Cohort Analysis: Analyze user behavior by creating cohorts based on shared characteristics or actions, enabling targeted insights into product performance.
• Segmentation: Easily segment users based on specific characteristics or behaviors, allowing for targeted analysis and personalized strategies.
• Funnel Analysis: Examine user behavior sequentially to identify churn points and optimize conversion rates.

Its warehouse-native approach allows seamless integration with existing data infrastructure, potentially reducing overall analytics costs.

Netspring

NetSpring is a product and customer analytics platform that combines business intelligence's flexibility with self-service product analytics. It works directly from any cloud data warehouse.

• Self-Service: Access a rich library of product analytics reports and easily switch between reports and ad hoc visual data exploration to find answers to your questions.
• Warehouse-Native: Integrate product instrumentation with any business data in your data warehouse for comprehensive, context-rich analysis.
• SQL Option: Simplify funnel and path queries without the need for complex SQL, while still having the option to use SQL for specialized analyses.
• Product and Customer Analytics: Utilize solutions for behavioral analytics, marketing analytics, operational analytics, customer 360 views, product 360 insights, and SaaS product-led growth (PLG) strategies.

Kubit

Kubit is an analytics platform that enables companies to gain valuable customer insights without the need to move their data into silos. This warehouse-native approach reduces ownership costs, conserves engineering resources, and provides more accurate and comprehensive self-service insights.

• User Engagement: Discover which user behaviors contribute to higher lifetime value and learn effective strategies for retaining and expanding your user base.
• Feature Engagement: Identify which product features drive the most engagement and help create power users within your product.
• Conversion Analysis: Understand how users navigate key funnels in your product and pinpoint areas that may lead to drop-offs, allowing you to address these issues effectively.
• Consumption Patterns: Gain insights into which product features and content to promote and which ones to phase out.

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Conclusion

In this post, I compared two approaches to marketing: product and revenue analytics.

• Warehouse-native
• Third-party

While the warehouse-native options are clearly more recent, they might lack some complex features that the traditional analytics solution already supports. They are a great choice for teams with large datasets. Their main benefit is cost efficiency and real-time access to the cloud data warehouse. While traditional third-party analytics solutions can provide better response times during analytics, they may lack the entire picture as data must be copied first to these solutions from the company data warehouse.

I suggest choosing a 3rd-party analytics solution if you have few visitors or active users and need to maintain an active data warehouse with usage data. Choose a warehouse-native solution if you have many users or visitors that you want to analyze. Typically, this is the case for B2C freemium products or if you already maintain a cloud data warehouse, where you anyway store all your data. In this case, warehouse-native solutions will provide the best and cost efficient experience.

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