Add Product use case #290
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| title: "Axiom for product analytics" | ||
| description: "This page explains how Axiom helps you leverage timestamped event data for product analytics purposes." | ||
| sidebarTitle: Product analytics | ||
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| Axiom helps you leverage the power of timestamped event data. Axiom believes that event data reflects a broad range of interactions, crossing boundaries from engineering to product management, security, and beyond. For a more general explanation of event data in Axiom, see [Events](/getting-started-guide/event-data). | ||
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| This page explains how you can leverage the power of event data for the product analytics use case. | ||
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| In product analytics, the ability to harness and interpret data effectively can determine the success of a product. Axiom offers a new approach to product analytics by leveraging the power of timestamped event data. This unique capability enables organizations to gain actionable insights, optimize user experiences, and drive product innovation. | ||
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There was a problem hiding this comment. I think it’s a stretch to call this new. Mixpanel, Amplitude and friends have been leading the charge for close to a decade. The part that feels novel to me is the ability to read every single event easily (sometimes they’ll make it easy to present aggregates, but not so easy to dive into specific underlying events), and I would expect performance wise we’d crush them at massive scale. |
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| ## Why event data matters in product analytics | ||
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| Event data captures the actions and interactions users have with a product over time. From button clicks and page views to error events and feature usage, every timestamped event tells a story about user behavior. Axiom’s platform is specifically designed to process and analyze these granular datasets, making it an indispensable tool for product teams aiming to do the following: | ||
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| - **Understand user behavior:** By tracking and analyzing event streams, Axiom provides a clear picture of how users engage with your product. | ||
| - **Identify trends and patterns:** Time-series analysis reveals emerging trends, helping teams anticipate user needs and adjust strategies proactively. | ||
| - **Optimize product features:** Pinpoint which features drive the most value and identify friction points that need improvement. | ||
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| ## Key features of Axiom for product analytics | ||
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| The following key features make Axiom perfect for product analytics: | ||
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| - **Real-time event monitoring:** Axiom’s ability to ingest and process data in real-time means you can monitor user activity as it happens. This empowers product managers to act quickly in response to anomalies or unexpected usage patterns, reducing downtime and improving user satisfaction. | ||
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There was a problem hiding this comment. What kinds of anomalies or unexpected usage patterns are usually of interest to product managers? |
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| - **Unified data platform:** Axiom eliminates data silos by integrating event data from diverse sources into a single, cohesive platform. Whether your data originates from web applications, mobile apps, or third-party tools, Axiom ensures seamless access and analysis. | ||
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There was a problem hiding this comment. Yeah great point. Could go further: What does it unlock when system / infrastructure telemetry is in the same store as product analytics? That really is unusual compared to vendors like Mixpanel and Amplitude. |
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| - **Advanced query capabilities:** With a robust query language, Axiom enables product teams to dive deep into data analysis. Perform detailed segmentation, drill down into specific user journeys, and uncover insights that would otherwise remain hidden. | ||
| - **Custom dashboards and visualizations:** Intuitive dashboards and customizable visualizations make it easy for product managers to communicate insights to stakeholders. Axiom’s visual tools enhance collaboration and decision-making. | ||
| - **Scalable infrastructure:** As your product grows, so does the volume of event data. Axiom’s architecture is built to scale effortlessly, ensuring that your analytics remain robust and reliable, even with massive datasets. | ||
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| ## Enhance product analytics with Axiom | ||
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There was a problem hiding this comment. While this section is surely relevant, unless we provide a working examples of relevant APL I’m not sure how much confidence this would give me as a product person considering Axiom |
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| Axiom helps you make the most of your event data in the following product analytics use cases, among others: | ||
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| - **Feature adoption analysis:** Understand how new features are adopted by users and identify which aspects require improvement to maximize engagement. | ||
| - **Retention and churn analysis:** Leverage event data to identify patterns in user retention and predict potential churn, enabling proactive interventions. | ||
| - **Funnel optimization:** Analyze user journeys through critical funnels, such as sign-ups or purchases, to pinpoint drop-off points and optimize conversion rates. | ||
| - **A/B testing:** Compare user interactions across different test groups to validate hypotheses and make data-driven decisions. | ||
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| ## Why choose Axiom for product analytics | ||
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| Axiom’s focus on timestamped event data makes it perfect for product analytics. By crossing boundaries from engineering to product management and security, Axiom empowers cross-functional teams to collaborate effectively. Its comprehensive feature set ensures that organizations can unlock the full potential of their data, driving smarter decisions and fostering innovation. | ||
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| In competitive markets, understanding your users is paramount. With Axiom, you gain a trusted partner in turning event data into actionable insights that propel your product to new heights. Experience the future of product analytics with Axiom and transform how you build, analyze, and optimize your product. | ||
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I think it would be a shame to publish content on product analytics and not touch on what has become something of a standard in Segment’s spec https://segment.com/docs/connections/spec/
Identify,track, andgroupcalls provide the rich foundation for event analytics, and it’s pretty common at this point for vendors to accept Segment events or services like RudderStack which follow the identical pattern because of it. Indeed, we ourselves use this in staging >segment-frontend-prodandsegment-core-prodso you can see the schema there withsegment-frontendprod | getschema.Examples:
https://docs.mixpanel.com/docs/tracking-methods/integrations/segment
https://amplitude.com/docs/data/source-catalog/segment
https://help.june.so/en/articles/5988266-segment-setup
If nothing else, it would give a fairly approachable foundation in this material to then provide sample APL that is directionally sound for product folks.
Excited about this content - I think this could be a big win!