Product Analytics

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Overview

Product Analytics helps you gain insight into user behavior and make data-driven decisions. It can help solve the following types of use cases in your application:

Understand product adoption
Track conversion rates and their evolution over time
Track key user behavior patterns
Visualize the most and least interacted with buttons on a given page

By default, Product Analytics data is retained for 15 months. Learn more about Privacy at Datadog.

Measure user retention

User retention is a metric for measuring the percentage of active users who continue to use your product, app, or service over a set period of time. Use Retention Analysis to measure how a group of users engage with specific features over time to understand where drop-offs occur.

Map user journeys

User journeys allow you to measure and report on the impact of every feature change - from backend bottlenecks to user frustrations - so that they can be appropriately optimized. Identify the ideal path for feature adoption and user conversion.

Understand end-to-end conversions with Funnel Analysis

See different visualizations of the user experience when interacting with your application:

Pathways: Explore aggregated workflows in a single visualization to aid in answering questions about user journeys.
Funnel: Measure the conversion rate end-to-end of a given workflow.
Conversion: Track conversion rates over time and compare it against specific attributes that may have affected conversion rates, such as browser type or geography.

Create user segments

Segments are users grouped by specific characteristics or behaviors. Segmentation in Datadog allows you to analyze and understand specific groups or segments of your user base.

Visualize user interactions with heatmaps

Heatmaps visualize the most interacted with elements on a page to see where hot spots of activity are, along with analyzing scroll depth to see how far users scrolled down a given page. You can view every swipe, scroll, and click with a pixel-perfect reproduction of exactly what users went through on both browser and mobile applications to identify high-or low-performing content.