Add Product use case

docs.json

@@ -37,6 +37,7 @@
                   "getting-started-guide/learn-about-axiom",
                   "getting-started-guide/event-data",
                   "getting-started-guide/observability",
+                  "getting-started-guide/product-analytics",
                   "getting-started-guide/feature-states",
                   "getting-started-guide/glossary"
                 ]

getting-started-guide/event-data.mdx

@@ -19,7 +19,6 @@ Each event is simply a structured record—composed of key-value pairs—that ca
 Event data, understood as the atomic unit of digital activity, is the lifeblood of modern businesses. Leveraging the power of event data is essential in the following areas, among others:
 
 - [Observability](/getting-started-guide/observability)
-- Security
-- Product analytics
-- Business intelligence
-- AI and machine learning
+- AI
+- [Product analytics](/getting-started-guide/product-analytics)
+- Business intelligence

getting-started-guide/learn-about-axiom.mdx

@@ -20,6 +20,13 @@ Learn about the fundamentals of timestamped event data in Axiom
 Learn about how Axiom helps you leverage timestamped event data for observability purposes
 </Card>
 
+<Card
+  title="Axiom for product analytics"
+  href="/getting-started-guide/product-analytics"
+>
+Learn about how Axiom helps you leverage timestamped event data for product analytics purposes
+</Card>
+
 <Card
   title="Glossary"
   href="/getting-started-guide/glossary"

getting-started-guide/observability.mdx

@@ -4,7 +4,7 @@
 sidebarTitle: Observability
 ---
 
 Axiom helps you leverage the power of timestamped event data. A common use case of event data is observability (o11y) in the field of software engineering. Observability is the ability to explain what is happening inside a software system by observing it from the outside. It allows you to understand the behavior of systems based on their outputs such as telemetry data, which is a type of event data.
 
 Software engineers most often work with timestamped event data in the form of logs or metrics. However, Axiom believes that event data reflects a much broader 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).
 
@@ -54,4 +54,4 @@
 - Axiom doesn’t support pre-aggregated metrics such as scrape samples.
 - Axiom isn’t optimized for high-dimensional metric time series with a very large number of metric/label combinations.
 
-Support for these types of metrics data is coming soon in the first half of 2025.
+Support for these types of metrics data is coming soon. If you’re interested, [contact Axiom](https://axiom.co/contact).

getting-started-guide/product-analytics.mdx

@@ -0,0 +1,120 @@
+---
+title: "Axiom for product analytics"
+description: "This page explains how Axiom helps you leverage timestamped event data for product analytics purposes."
+sidebarTitle: Product analytics
+---
+
+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).
+
+This page explains how you can leverage the power of event data for the product analytics use case.
+
+In product analytics, the ability to harness and interpret data effectively can determine the success of a product. Axiom allows product analytics to leverage the power of timestamped event data and easily read every single event. This unique capability enables organizations to gain actionable insights, optimize user experiences, and drive product innovation.
+
+## Why event data matters in product analytics
+
+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:
+
+- **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.
+
+## Key features of Axiom for product analytics
+
+The following key features make Axiom perfect for product analytics:
+
+- **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. For example:
+
+    - Track whether feature flags are toggling as expected.
+    - Watch for broken signup flows or onboarding drop-offs immediately after a deploy.
+    - Monitor if newly launched features are generating engagement.
+
+- **Unified data platform:** Axiom eliminates data silos by integrating event data from diverse sources into a single, cohesive platform. Axiom stores system telemetry alongside product analytics data. This eliminates the traditional separation between “user behavior” tools and “engineering” tools, and this convergence unlocks powerful debugging and insight scenarios:
+
+    - Correlate frontend feature usage with backend latency.
+    - View conversion funnel stages alongside HTTP error logs.
+    - Link user drop-off to infrastructure anomalies.
+
+- **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.
+
+## Standard patterns for product data: Segment compatibility
+
+Axiom supports event ingestion via widely adopted patterns such as the [Segment specification](https://segment.com/docs/connections/spec/):
+
+- **`identify`** associates events with known users.
+- **`track`** records user interactions like button clicks or page views.
+- **`group`** associates users with organizations or accounts.
+
+Axiom is compatible with these conventions used by popular tools like Mixpanel, Amplitude, June, and RudderStack.
+
+This approach gives product teams a familiar and low-friction way to onboard their analytics events, and the foundation for querying user behavior via APL (Axiom Processing Language).
+
+For example, the APL query below filters tracked events by name:
+
+```kusto
+['segment-frontend-prod']
+| where event == "Button Clicked"
+| summarize count() by userId, bin(_time, 1h)
+```
+
+## Enhance product analytics with Axiom
+
+Axiom helps you make the most of your event data in the following product analytics use cases, among others:
+
+- **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.
+
+## Use cases: from funnels to retention
+
+Here are some ways product teams use Axiom:
+
+### Feature adoption tracking
+
+Measure which users are engaging with newly released features.
+
+```kusto
+['segment-frontend-prod']
+| where event == "Feature Used" and properties.featureName == "AI Chat"
+| summarize count() by userId, bin(_time, 1h)
+```
+
+### Retention and churn analysis
+
+Analyze returning users over time:
+
+```kusto
+['segment-frontend-prod']
+| where event == "Logged In"
+| summarize sessions = count(), users = dcount(userId) by bin(_time, 1w)
+```
+
+### Funnel diagnostics
+
+Trace where users drop off between signup, onboarding, and first value.
+
+```kusto
+['segment-frontend-prod']
+| where event in ("Signed Up", "Completed Onboarding", "Created Project")
+| project userId, event, _time
+| sort by userId, _time
+```
+
+### A/B test measurement
+
+Compare experiment cohorts based on downstream engagement:
+
+```kusto
+['segment-frontend-prod']
+| where properties.experimentGroup == "variant_a"
+| where event == "Clicked Upgrade"
+| summarize conversions = dcount(userId)
+```
+
+## Why choose Axiom for product analytics
+
+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.
+
+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.