PANA REDO 2 -

config/_default/menus/main.en.yaml

@@ -8020,6 +8020,11 @@ menu:
       parent: pa_session_replay
       identifier: pa_heatmaps
       weight: 301
+    - name: Playlists
+      url: product_analytics/session_replay/playlists
+      parent: pa_session_replay
+      identifier: pa_playlists
+      weight: 302
     - name: Mobile
       url: product_analytics/session_replay/mobile
       parent: pa_session_replay
@@ -8069,17 +8074,17 @@ menu:
       url: product_analytics/segmentation/
       parent: product_analytics
       identifier: pa_segmentation
-      weight: 4
+      weight: 6
     - name: Guides
       url: product_analytics/guide/
       parent: product_analytics
       identifier: pa_guides
-      weight: 5
+      weight: 7
     - name: Troubleshooting
       url: product_analytics/troubleshooting/
       parent: product_analytics
       identifier: pa_troubleshooting
-      weight: 6
+      weight: 8
     - name: Account Management
       url: account_management/
       pre: cog-2

content/en/product_analytics/_index.md

@@ -19,10 +19,10 @@ further_reading:
 
 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
+- [Understand product adoption](#understand-product-adoption)
+- [Track conversion rates and their evolution over time](#track-conversion-rates-and-their-evolution-over-time)
+- [Track key user behavior patterns](#track-key-user-behavior-patterns)
+- [Visualize the most and least interacted with buttons on a given page](#visualize-the-most-and-least-interacted-with-buttons-on-a-given-page)
 
 ## Getting started
 
@@ -34,44 +34,75 @@ To start using Product Analytics, enable it for each application where you want
 
 {{< img src="product_analytics/enable-product-analytics.png" alt="Enable Product Analytics from the Application Management page.">}}
 
-By default, Product Analytics data is retained for 15 months. Learn more about [Privacy at Datadog][1].
+By default, Product Analytics data is retained for 15 months. Learn more about [Datadog's data retention periods][1].
 
-## Measure user retention
+## Navigating the Product Analytics UI
+Each Product Analytics feature provides context into your users' journeys. This section describes the context each feature can provide for your individual use case.
 
-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][2] to measure how a group of users engage with specific features over time to understand where drop-offs occur.
+### Understand product adoption
+The [Home][3] page gives you a bird's-eye view of your users' activity and a pulse into your product's adoption. This is where you most often land when accessing Product Analytics.
 
-{{< img src="real_user_monitoring/retention_analysis/differing-events-retention-graph.png" alt="Retention graph for differing events" style="width:90%;" >}}
+{{< img src="/product_analytics/pana_home_page.png" alt="Understand end-to-end conversions with Funnel Analysis.">}}
 
-## Map user journeys
+By default, this page displays the `active users`, `page views` and `average time spent by user` charts, but you have the ability to add additional charts or a dashboard. You can navigate to anywhere in Product Analytics from the home page. 
 
-[User journeys][3] 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.
+### Track conversion rates and their evolution over time
+The Product Analytics charts help you visualize your users' journey as they use your product.
 
-{{< img src="/product_analytics/journeys/pa-funnel-1.png" alt="Understand end-to-end conversions with Funnel Analysis.">}}
+{{< img src="/product_analytics/pana_charts_video.mp4" alt="visualize your users' journey with charts." video="true">}}
 
-See different visualizations of the user experience when interacting with your application:
+Each chart type provides a different view into the user's journey:
 
-- **[Funnel][4]**: Measure the **conversion rate** and **time to convert** from end-to-end of a given workflow. 
-- **[Pathways][5]**: Explore aggregated workflows in a single visualization to aid in answering questions about user journeys. In addition, track conversion rates over time and compare them against specific attributes that might have affected conversion rates, such as browser type or geography.
+[Pathways][5]
+: you can visualize all user journeys across your application to analyze the critical path.
 
-## Create user segments
+[Funnel][4]
+: track conversion rates across key workflows to identify and address any bottlenecks in end-to-end user journeys. <br> For example, you can see if customers drop off at a certain point due to poor website performance or measure how adding new steps to a workflow impacts drop off rate.
 
-Segments are users grouped by specific characteristics or behaviors. [Segmentation][6] in Datadog allows you to analyze and understand specific groups or segments of your user base.
+[Retention][2]
+:  measure how often users are successfully returning to a page or action to gain insights into overall user satisfaction.
 
-## Visualize user interactions with heatmaps
+[Analytics][13]
+: contains views data aggregation for understanding how your product is being used.
 
-[Heatmaps][7] 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.
 
-{{< img src="real_user_monitoring/heatmaps/heatmap_v2.png" alt="An overview of the heatmap functionality." style="width:100%;">}}
+### Track key user behavior patterns
+You may want to better understand a specific group of users. This could be for the purpose of improving their user experience, or nudge them to buy the content in their cart. Regardless of the purpose, you can use the [Users & Segment][6] section to group your users based on a desired characteristic.
+
+{{< img src="/product_analytics/segmentation/userprofiles_pana-ga.png" alt="See individual profiles of users and create a segment from these profiles.">}}
+
+You can see the individual profiles of user, and create a segment, or a specified grouping, from these profiles to fit the behavior you would like to observe. For example, you can create a segment on users who have items in their carts but have not yet checked out to send an email nudging them to make a puchase. 
+
+
+### Visualize the most and least interacted with buttons on a given page
+Suppose you want to make changes to your application interface but want to first understand how users navigate in the page. Is there a specific path they take more than others? Can you make user actions and flows smoother? The following features can help you capture and replay your users' browsing experience to inform your product change decisions. 
+
+{{< img src="/product_analytics/pana_session_replay_page.png" alt="Capture and replay your users' browsing experience to inform your product design decisions.">}}
+
+[Session replay][11] 
+: Expands your user experience monitoring by allowing you to capture and visually replay the web browsing or mobile app experience of your users. <br><br>This is beneficial for _error identification_, _reproduction_, and _resolution_, and provides insights into your application’s usage patterns and design pitfalls
+
+[Heatmaps][10]
+:  This is a visualization of your user’s interactions overlaid on Session Replay data. Product Analytics has three different types of heatmaps: Click maps, Top elements, Scroll maps. <br><br> Use heatmaps to review complex data at a glance, gaining insights around optimizing your user experience.
+
+[Playlist][12]
+: You can create a playlist of Session Replays to organize them by any patterns you notice. Learn more about [Session Replay Playlists][12].
+<br>
+
 
 ## Further reading
 {{< partial name="whats-next/whats-next.html" >}}
 
-[1]: https://www.datadoghq.com/privacy/
-[2]: /product_analytics/user_retention
-[3]: /product_analytics/journeys
-[4]: /product_analytics/journeys/funnel_analysis
-[5]: /product_analytics/journeys/pathways
+[1]: /data_security/data_retention_periods/
+[2]: /product_analytics/charts/user_retention
+[3]: https://app.datadoghq.com/product-analytics
+[4]: /product_analytics/charts/funnel_analysis
+[5]: /product_analytics/charts/pathways
 [6]: /product_analytics/segmentation/
-[7]: /product_analytics/heatmaps
 [8]: https://app.datadoghq.com/rum/
 [9]: https://app.datadoghq.com/rum/list
+[10]: /product_analytics/session_replay/heatmaps
+[11]: /product_analytics/session_replay/
+[12]: /product_analytics/session_replay/playlists
+[13]: /product_analytics/charts/analytics_explorer
+

content/en/product_analytics/charts/_index.md

@@ -1,8 +1,6 @@
 ---
-title: Journeys
-aliases:
-- /product_analytics/journeys
-description: Journeys help you understand the path your users follow as they discover your product, service, or brand.
+title: Visualizing with charts
+description: The various Charts help you understand the path your users follow as they discover your product, service, or brand.
 further_reading:
 - link: "/product_analytics/"
   tag: "Documentation"
@@ -11,22 +9,44 @@ further_reading:
 
 ## Overview
 
-Journeys help you track user journeys from end-to-end to discover the different ways users navigate through your application. You can extract the data to design your app in a way that users actually use it - not how you think they use it.
+Use the various charts to visualize your users' journeys from end-to-end to discover the different ways users navigate your application. You can extract the data to identify frictions in the user journey, measure the success of UI changes and inform your application design decisions. 
 
-## Pathways
+## Deciding which chart to use
 
-{{< img src="/product_analytics/journeys/pa-pathways-1.png" alt="Use Pathways to visualize all user journeys across your application to analyze the critical path">}}
 
-[Pathway diagrams][1] allow you to visualize all user journeys across your application to identify the most important contributions to a flow.
+### Pathways diagram
 
-## Funnel analysis
+{{< img src="/product_analytics/overview_pathways_ga.png" alt="Use Pathways to visualize all user journeys across your application to analyze the critical path">}}
 
-{{< img src="/product_analytics/journeys/pa-funnel-1.png" alt="Understand end-to-end conversions with Funnel Analysis.">}}
+The [Pathways diagram][3] allows you to visualize all user journeys across your application to identify the most important contributions to a flow.
+
+
+### Funnel analysis
+
+{{< img src="/product_analytics/overview_funnel_ga.png" alt="Understand end-to-end conversions with Funnel Analysis.">}}
+
+With [funnel analysis][2], you can understand the end-to-end conversion of a single essential workflow. You can view details in the side panel to understand why conversation rates are what they are.
+For example, you can determine if there was there a performance issue that caused user drop-off. Are customers experiencing an error that occurred in a recent release? Watch a Session Replay of a user who converted or dropped off to see exactly what happened.
+
+### Retention Analysis
+
+{{< img src="/product_analytics/overview_retention_ga.png" alt="Understand end-to-end conversions with Funnel Analysis.">}}
+
+With [retention analysis][4] you can measure how often users are successfully returning to a page or to an action. This measure offers insight into overall user satisfaction with your application. 
+
+### Analytic Explorer
+
+{{< img src="/product_analytics/overview_analytic_ga.png" alt="Understand end-to-end conversions with Funnel Analysis.">}}
+
+The [Analytics Explorer][1] contains views data aggregation to help you understand how your product is being used. You can create a widget in a dashboard out of that visualization and dive deeper into subsets of the events list depending on the interactions that the visualization enables. 
 
-With [funnel analysis][1], you can understand the end-to-end conversion of a single key workflow. You can get a detailed drilldown in the sidepanel to understand why conversation rates are what they are. For example, was there a performance issue that caused user dropoff? Are they experiencing an error that occurred in a recent release? Watch a Session Replay of a user who converted or dropped off to see exactly what happened.
 
 ## Further reading
 {{< partial name="whats-next/whats-next.html" >}}
 
-[1]: /product_analytics/journeys/pathways
-[2]: /product_analytics/journeys/funnel_analysis
+[1]: /product_analytics/charts/analytics_explorer/
+[2]: /product_analytics/charts/funnel_analysis
+[3]: /product_analytics/charts/pathways
+[4]: /product_analytics/charts/user_retention
+
+

content/en/product_analytics/charts/analytics_explorer/_index.md

@@ -21,7 +21,7 @@ further_reading:
 
 ## Overview
 
-The Analytics Explorer contains views data aggregation for understanding how your product is being used. You can control:
+The [Analytics Explorer][1] page contains views data aggregation for understanding how your product is being used. You can control:
 
 * The event type (Sessions, Views, or Actions) to see views by.
 * The query that filters the set of views to analyze.
@@ -33,6 +33,15 @@ With Analytics visualizations, you can:
 * Create a widget in a dashboard out of that visualization.
 * Dive deeper into subsets of the events list depending on the interactions that the visualization enables.
 
+## Using the analytics chart
+{{< whatsnext desc="Follow these links here to learn how to use the analytics search syntax, view events, and vizualise, group, and export views. " >}}
+    {{< nextlink href="product_analytics/charts/analytics_explorer/search_syntax" >}}Search syntax{{< /nextlink >}}
+    {{< nextlink href="product_analytics/charts/analytics_explorer/events" >}} Events {{< /nextlink >}}
+    {{< nextlink href="product_analytics/charts/analytics_explorer/visualize" >}}Visualize{{< /nextlink >}}
+    {{< nextlink href="product_analytics/charts/analytics_explorer/group" >}}Groups{{< /nextlink >}}
+    {{< nextlink href="product_analytics/charts/analytics_explorer/export" >}}Export{{< /nextlink >}}
+{{< /whatsnext >}}
+
 ## Build a query
 
 In [Analytics][1], customize your display by adding facets and measures to your search query. 
@@ -45,18 +54,18 @@ In [Analytics][1], customize your display by adding facets and measures to your
 
    {{< img src="product_analytics/analytics/measure_selection.png" alt="Choose a measure to graph the unique count." style="width:50%;">}}
 
-4. Choose a field to [group][3] the measure by.
+3. Choose a field to [group][3] the measure by.
 
-   {{< img src="product_analytics/analytics/group_breakdown.png" alt="Group the measure by specific fields." style="width:50%;">}}
+   {{< img src="product_analytics/analytics/pana_analytics_group_by.png" alt="Group the measure by specific fields." style="width:50%;">}}
 
-5. Choose the time interval for your graph. Changing the global timeframe changes the list of available timestep values.
+4. Choose the time interval for your graph. Changing the global timeframe changes the list of available timestep values.
 
-   {{< img src="product_analytics/analytics/time_interval.png" alt="Choose a time interval for your graph." style="width:50%;">}}
+   {{< img src="product_analytics/analytics/pana_analytics_time_imterval.png" alt="Choose a time interval for your graph." style="width:50%;">}}
 
 ## Further Reading
 
 {{< partial name="whats-next/whats-next.html" >}}
 
-[1]: https://app.datadoghq.com/rum/analytics
+[1]: https://app.datadoghq.com/product-analytics/explorer
 [2]: /real_user_monitoring/guide/understanding-the-rum-event-hierarchy/
-[3]: /product_analytics/analytics_explorer/group/
+[3]: /product_analytics/charts/analytics_explorer/group

content/en/product_analytics/charts/analytics_explorer/events.md

@@ -14,7 +14,7 @@ The Product Analytics Explorer displays individual events in a side panel format
 
 {{< img src="real_user_monitoring/explorer/events/performance_side_panel.png" alt="Application performance graph and Core Web Vitals in the Performance tab" width="80%" >}}
 
-General context information is provided at the top. Scroll to the waterfall to see the actual content of the event. 
+General context information is provided at the top. Scroll to the waterfall to see the content of the event. 
 
 Context about your users and their applications, including the OS, country, code version, and more, is captured when the event is generated. Context also refers to the event itself, which includes information specific to the event type. For example, the event side panel shows the view path while the **Errors** side panel shows the error message.
 

content/en/product_analytics/charts/analytics_explorer/group.md

@@ -1,7 +1,5 @@
 ---
 title: Group Product Analytics Events
-aliases:
-- /product_analytics/analytics_explorer/group
 further_reading:
 - link: "/real_user_monitoring/explorer/search/"
   tag: "Documentation"
@@ -12,7 +10,7 @@ further_reading:
 
 Product Analytics events are valuable both individually and collectively. The search query contains information to aggregate a subset of events.
 
-{{< img src="product_analytics/analytics/group/group-overview.png" alt="Group into fields section of the Search query" style="width:100%;" >}}
+{{< img src="product_analytics/analytics/group/pana_group_search_bar.png" alt="Group into fields section of the Search query" style="width:100%;" >}}
 
 Your selection of fields to group, aggregate, and measure your events are preserved as you switch between visualization types.
 
@@ -22,15 +20,15 @@ All Product Analytics events that match your filter query are aggregated into gr
 
 - Count of events per group
 
-  {{< img src="product_analytics/analytics/group/group_count_of_events.png" alt="Group by count of events" style="width:90%;" >}}
+  {{< img src="product_analytics/analytics/group/pana_group_by_action.png" alt="Group by count of events" style="width:90%;" >}}
 
 - Unique count of coded values for a facet per group
 
-  {{< img src="product_analytics/analytics/group/count-of-coded-values.png" alt="Group by unique count of coded values" style="width:90%;" >}}
+  {{< img src="product_analytics/analytics/group/pana_group_by_loading_time.png" alt="Group by unique count of coded values" style="width:90%;" >}}
 
 - Statistical operations (such as minimum, maximum, average, and percentiles) on a facet's numerical values per group
 
-  {{< img src="product_analytics/analytics/group/group-statistical-operations.png" alt="Group into fields using statistical operations" style="width:90%;" >}}
+  {{< img src="product_analytics/analytics/group/pana_group_distribution.png" alt="Group into fields using statistical operations" style="width:90%;" >}}
 
 Individual events with multiple values for a single facet belong to that number of aggregates. For example, an event with the `country:france` and `browser:chrome` attributes are counted once in the `country:france` aggregate and once in the `browser:chrome` aggregate.