diff --git a/config/_default/menus/main.en.yaml b/config/_default/menus/main.en.yaml index b9c33c6566545..46bc65e6e993f 100644 --- a/config/_default/menus/main.en.yaml +++ b/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 diff --git a/content/en/product_analytics/_index.md b/content/en/product_analytics/_index.md index 138a7c8b419b3..e165ed648d426 100644 --- a/content/en/product_analytics/_index.md +++ b/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.
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.

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.

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]. +
+ ## 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 + diff --git a/content/en/product_analytics/charts/_index.md b/content/en/product_analytics/charts/_index.md index 2dbb7720d35ed..8c0af17fce51b 100644 --- a/content/en/product_analytics/charts/_index.md +++ b/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 + + diff --git a/content/en/product_analytics/charts/analytics_explorer/_index.md b/content/en/product_analytics/charts/analytics_explorer/_index.md index bebfb42245db8..81024f0d47ecf 100644 --- a/content/en/product_analytics/charts/analytics_explorer/_index.md +++ b/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/ \ No newline at end of file +[3]: /product_analytics/charts/analytics_explorer/group \ No newline at end of file diff --git a/content/en/product_analytics/charts/analytics_explorer/events.md b/content/en/product_analytics/charts/analytics_explorer/events.md index 047482bfdb0b0..d7ed7c50d21a7 100644 --- a/content/en/product_analytics/charts/analytics_explorer/events.md +++ b/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. diff --git a/content/en/product_analytics/charts/analytics_explorer/group.md b/content/en/product_analytics/charts/analytics_explorer/group.md index 0faf400e07ab5..654c26e5cad3b 100644 --- a/content/en/product_analytics/charts/analytics_explorer/group.md +++ b/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. diff --git a/content/en/product_analytics/charts/analytics_explorer/visualize.md b/content/en/product_analytics/charts/analytics_explorer/visualize.md index a29ac279ee2b8..8ddd36b67390a 100644 --- a/content/en/product_analytics/charts/analytics_explorer/visualize.md +++ b/content/en/product_analytics/charts/analytics_explorer/visualize.md @@ -91,7 +91,7 @@ By default, events in the list visualization are organized by timestamp, with th ## Related events -For all visualizations besides the [funnel](#funnels), select a section of the graph or click on the graph to either zoom in or see a list of events that correspond to your selection. +For all visualizations besides the [funnel][2], select a section of the graph or click on the graph to either zoom in or see a list of events that correspond to your selection. {{< img src="product_analytics/analytics/visualize/analytics-related-events.png" alt="Related events link available when you click on the graph" width="90%" >}} @@ -103,4 +103,5 @@ For the remaining visualization options, click on the graph and click **View eve {{< partial name="whats-next/whats-next.html" >}} -[1]: /product_analytics/analytics_explorer/ \ No newline at end of file +[1]: https://app.datadoghq.com/product-analytics/explorer +[2]: /product_analytics/charts/funnel_analysis \ No newline at end of file diff --git a/content/en/product_analytics/charts/funnel_analysis.md b/content/en/product_analytics/charts/funnel_analysis.md index ddfe84e05ae71..877065b360f09 100644 --- a/content/en/product_analytics/charts/funnel_analysis.md +++ b/content/en/product_analytics/charts/funnel_analysis.md @@ -28,17 +28,17 @@ Funnel analysis helps you track conversion rates across key workflows to identif ## Build a funnel -To build a funnel, navigate to [**Digital Experience > Product Analytics > Journeys**][1] and click **Funnel**. +To build a funnel, navigate to [**Product Analytics > Charts**][1] and click **Funnel**. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-overview.png" alt="Navigate to the Funnel Analysis tab within Product Analytics" style="width:100%;" >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_overview.png" alt="Navigate to the Funnel Analysis tab within Product Analytics" style="width:100%;" >}} -From this page, choose your starting view or action and click on the plus icon to build additional steps. You can also use drag and drop functionality to move steps around. +From this page, choose your starting view or action and click on `+ Step` to build additional steps. You can also use drag and drop functionality to move steps around. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-start-view-action.mp4" alt="Filtering network map with search" video=true >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_video1.mp4" alt="Filtering network map with search" video=true >}} If you have a starting point in mind, but aren't sure what your users did next, the funnel step editor automatically loads the top most common **views** and **actions** that users typically see and take next. This allows you to build funnels quicker knowing the paths your users are taking in sequence. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-build-next-steps.png" alt="The funnel step editor automatically loads the top most common views and actions that users typically see and take next." style="width:50%;" >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_dropoffs.png" alt="The funnel step editor automatically loads the top most common views and actions that users typically see and take next." style="width:50%;" >}} **Note**: Any action or view that happens between two steps in a funnel does not impact the step-by-step or overall conversion rate. As long as step 1 and step 2 happen in the right order in a given session at least once, it counts as a single converted session. @@ -48,11 +48,11 @@ When constructing your funnel, you can filter globally or on a step. - **Global filters** are applied to the entire funnel. - {{< img src="product_analytics/journeys/funnel_analysis/funnels-global-filters.png" alt="Use attributes to filter information globally when constructing your funnel" style="width:50%;" >}} + {{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_filter_by-2.png" alt="Use attributes to filter information globally when constructing your funnel" style="width:50%;" >}} - **Filtering on a step** provides insight on how the step changes based on a particular constraint on that step. For example, you may want to see how a specific device, operating system, geolocation, or user impacts conversion between steps. - {{< img src="product_analytics/journeys/funnel_analysis/funnels-step-filters.png" alt="Use attributes to filter information between steps when constructing your funnel" style="width:50%;" >}} + {{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_filter_by_step.png" alt="Use attributes to filter information between steps when constructing your funnel" style="width:50%;" >}} ### Combining events @@ -83,7 +83,7 @@ You can measure conversion by the following attributes: You can measure these attributes **across all steps** or between **specific steps**. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-across-steps.png" alt="Measure attributes across all steps or specific steps." style="width:60%;" >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_conversion.png" alt="Measure attributes across all steps or specific steps." style="width:60%;" >}} Use the **filter** selector to filter by various criteria that you define. @@ -91,7 +91,7 @@ Next, click a datapoint to **investigate the specific attributes** that might ha ## Changing the visualization -{{< img src="product_analytics/journeys/funnel_analysis/funnel-timeseries.mp4" alt="Click the visualization dropdown to select a different view" video=true >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_change_viz.mp4" alt="Click the visualization dropdown to select a different view" video=true >}} After you've defined the step events and conversion measurement, you can switch to a different visualization to better understand user conversions for your app. @@ -100,19 +100,19 @@ Seeing the conversion as a timeseries can be helpful in understanding conversion You can select the time period for graphing the conversion and view conversions in percentages or in absolute count. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-timeseries.png" alt="View conversion data as a timeseries." style="width:80%;" >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_timeseries.png" alt="View conversion data as a timeseries." style="width:80%;" >}} ### Query value Query values display the current value of the given usage metric. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-query-value.png" alt="View conversion data as a query value." style="width:80%;" >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_query_value.png" alt="View conversion data as a query value." style="width:80%;" >}} ### Top list Visualize the top values from a facet based on your chosen measure. -{{< img src="product_analytics/journeys/funnel_analysis/funnels-top-list.png" alt="View conversion data as a top list." style="width:80%;" >}} +{{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_toplist.png" alt="View conversion data as a top list." style="width:80%;" >}} ## Share a funnel @@ -122,19 +122,16 @@ You can share the entire visualization or individual widgets. - Share the entire visualization to Notebooks and dashboards: - {{< img src="product_analytics/journeys/funnel_analysis/funnels-share-visualization.png" alt="Share the entire visualization by clicking Export" style="width:90%;" >}} + {{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_share_funnel.png" alt="Share the entire visualization by clicking Export" style="width:90%;" >}} - Share individual widgets from a dashboard: - {{< img src="product_analytics/journeys/funnel_analysis/funnels-share.png" alt="Share a widget by clicking the export icon in the upper-right of the widget" style="width:90%;" >}} + {{< img src="product_analytics/journeys/funnel_analysis/pana_funnel_share_dashboard.png" alt="Share a widget by clicking the export icon in the upper-right of the widget" style="width:90%;" >}} ## Further reading {{< partial name="whats-next/whats-next.html" >}} [1]: https://app.datadoghq.com/product-analytics/user-journey/funnel -[2]: /real_user_monitoring/browser/data_collected/#default-attributes -[3]: /real_user_monitoring/browser/data_collected/#session-metrics -[4]: /real_user_monitoring/session_replay -[5]: /dashboards/ +[5]: /product_analytics/dashboards/ [6]: /notebooks/ \ No newline at end of file diff --git a/content/en/product_analytics/charts/pathways.md b/content/en/product_analytics/charts/pathways.md index c552e81697049..a377af4adc76d 100644 --- a/content/en/product_analytics/charts/pathways.md +++ b/content/en/product_analytics/charts/pathways.md @@ -1,5 +1,5 @@ --- -title: Pathways +title: Pathways Diagrams aliases: - /real_user_monitoring/product_analytics/sankey - /product_analytics/sankey @@ -16,21 +16,21 @@ further_reading: ## Overview -You can use Pathway diagrams to visualize all user journeys across your application to analyze the critical path. +Pathways diagrams allow you to visualize all user journeys across your application to analyze the critical path. -{{< img src="/product_analytics/journeys/pathways/pathways-overview.png" alt="The default Pathways diagram for an app" style="width:90%;" >}} +{{< img src="/product_analytics/journeys/pathways/ga_pathway_diagrams_page.png" alt="The default Pathways diagram for an app" style="width:90%;" >}} Each node represents a view the user visited. The thickness of each node represents the count of user sessions on that page. A page with fewer visitors has a thinner node in the diagram. If a user visits the same page multiple times during their session, that page is only counted once. -Actions are not supported in the Pathways diagram. +Action events are not supported in the Pathways diagram. ## Build a Pathways diagram ### View the default diagram -1. Navigate to [**Product Analytics > User Journeys**][1]. +1. Navigate to [**Product Analytics > Charts**][1]. 2. Click **Pathways** if it's not already selected. This displays the default visualization that represents the most popular user journeys in your application. ### Start or end the diagram at a given view @@ -41,7 +41,7 @@ You can use the left menu to customize this diagram and display: The example below displays the four steps that users in the United States take after visiting `/department/lighting`: -{{< img src="/product_analytics/journeys/pathways/customized-pathways.png" alt="A customized Pathways diagram for an app" style="width:90%;" >}} +{{< img src="/product_analytics/journeys/pathways/pana_pathway_page_img2.png" alt="A customized Pathways diagram for an app" style="width:90%;" >}} ### Graph all views containing a given phrase @@ -49,27 +49,27 @@ Pathways diagrams support [Datadog wildcards][2], allowing you to build a diagra To match multiple routes, type a wildcard instead of choosing a single view name. The example below displays the five steps that users take after visiting any view matching `/department/*`: -{{< img src="/product_analytics/journeys/pathways/pathways-wildcard.png" alt="A Pathways diagram that uses a wildcard to match several routes" style="width:90%;" >}} +{{< img src="/product_analytics/journeys/pathways/pana_pathway_page_img3.png" alt="A Pathways diagram that uses a wildcard to match several routes" style="width:90%;" >}} -## Analyze a Pathways diagram +## Analyze a pathways diagram You can hover over a diagram node to view the number of sessions that included visits to that view. Click a node for a list of analysis options, such as viewing a sample [Session Replay][3] or building a Pathways diagram that starts with that view. -{{< img src="/product_analytics/journeys/pathways/pathways-node.png" alt="The actions menu of a Pathways diagram node" style="width:90%;" >}} +{{< img src="/product_analytics/journeys/pathways/pana_pathway_page_img4.png" alt="The actions menu of a Pathways diagram node" style="width:90%;" >}} ### Convert the diagram to a funnel 1. From the Pathways diagram page, click the **Build Funnel** button. 2. In the Pathways diagram, click the nodes of the views you want to include in the funnel. -3. Click **Create Funnel from Selection**. +3. Click **Create Funnel From Selection**. -{{< img src="/product_analytics/journeys/pathways/pathways-build-funnel.png" alt="A Pathway to funnel conversion in process" style="width:90%;" >}} +{{< img src="/product_analytics/journeys/pathways/pana_pathway_page_img5.png" alt="A Pathway to funnel conversion in process" style="width:90%;" >}} ## Further reading {{< partial name="whats-next/whats-next.html" >}} -[1]: https://app.datadoghq.com/product-analytics/user-journey +[1]: https://app.datadoghq.com/product-analytics/user-journey/pathways [2]: /real_user_monitoring/explorer/search_syntax/#wildcards -[3]: /real_user_monitoring/session_replay/ +[3]: /product_analytics/session_replay/ diff --git a/content/en/product_analytics/charts/user_retention.md b/content/en/product_analytics/charts/user_retention.md index cdac6300df410..f19d57c5fefdc 100644 --- a/content/en/product_analytics/charts/user_retention.md +++ b/content/en/product_analytics/charts/user_retention.md @@ -12,11 +12,26 @@ further_reading: ## Overview Retention Analysis allows you to measure how often users are successfully returning to a page or action. By tracking user retention over time, you can gain insights into overall user satisfaction. -User retention is measured within a given cohort of users that you define. A cohort is a group of users who participate in an initial event, such as clicking a link. A user in the cohort is considered retained if they subsequently complete a return event, such as clicking the same link again or clicking a **Proceed to Payment** button. Only views and actions can act as events. +User retention is measured within a given cohort of users that you define. A cohort is a group of users who participate in an initial event, such as clicking a link. A user in the cohort is considered retained if they subsequently complete a return event, such as clicking the same link again or clicking a **Proceed to Payment** button. -The retention graph displays the percentage of users who completed the return event each week. +Only views and actions can act as events. + +The retention graph displays the percentage of users who completed the return event each day during the past week. + +{{< img src="product_analytics/retention/pana_retention_overview-2.png" alt="Example Retention Analysis graph" style="width:100%;" >}} + +
+Note: The retention chart displays grey when partial data is available for a given time period or cohort. This is because the time period is not finished and Datadog cannot yet accurately compute the retention rate. +
+ + +You can further scope the retention measure based on when the return event occurs to identify the users who have completely churned from a product or feature. + +- `Return on or after`: the user has to complete the "Return event" on or after the period to be counted as retained. + +- `Return on`: the user has to do the "Return event" on the period to be counted as retained. +It's useful to understand the likelihood of a user to come back after a given period. -{{< img src="real_user_monitoring/retention_analysis/example-retention-analysis-graph.png" alt="Example Retention Analysis graph" style="width:100%;" >}} ## Prerequisites @@ -24,32 +39,39 @@ In order for User Retention data to populate, you must set the `usr.id` attribut ## Build a graph -To build a retention graph, navigate to **[Digital Experience > Product Analytics > Retention Analysis][1]**, which takes you to the **User Retention** page, then follow the steps below. +To build a retention graph, navigate to **[Product Analytics > Charts][1]**, click the **Retention** tab, then follow the steps below. -### 1. Define the initial event -1. Select the view or action to act as the initial event for defining a group of users. -2. Optionally, add filters such as the device used or the country of origin. - - If your initial event is a view, you can add any [view facets][2] or context facets. - - If your initial event is an action, you can add any [action facets][3] or context facets. +### 1. Define the starting and return events +1. Select the view or action to act as the starting event for defining a group of users.
+2. Select the view or action to act as the return event. -### 2. Optionally, define the return event -The return event defaults to a repeat of the original event. To use a different return event: +### 2. Define the the measures +1. Select `Retention rate` to see the data in percentages, or `Unique users` to see the absolute number of users. +2. Scope the retention measure `Return on or after` or `Return on` based on when the return event occurs. +3. Choose the timeframe (day, week or month) which define the rows in your diagram, then scope to the appropriate duration for your columns. For example, in the `Measure by` section, you can select `Each day` and have the duration of this measure be for the past week. + +{{< img src="product_analytics/retention/pana_retention_timeframes.png" alt="Example Retention Analysis graph" style="width:100%;" >}} + + + +### 3. Define the users +Optionally, select a specific [segment][6] to measure the retention of its users. This defaults to All users. + +### 4. Add filters +Optionally, add any desired filter criteria, such as the user's country, device type, or operating system. -1. Change **Repeated the original event** to **Experienced a different event**. -2. Select the view or action to act as the return event. -3. Optionally, add any desired filter criteria, such as the user's operating system. ## Analyze the graph For insights on user retention week over week, read each row of the graph horizontally from left to right. You can click on an individual diagram cell to view a list of users, and export the list as a CSV: -{{< img src="real_user_monitoring/retention_analysis/retention-analysis-graph-details-panel.png" alt="Details panel for a diagram cell" style="width:90%;" >}} +{{< img src="product_analytics/retention/pana_retention_export.png" alt="Details panel for a diagram cell" style="width:90%;" >}} The graph displays slightly different information depending on whether the initial and return events match. -### Matching events -If the events match: +### Matching events +If the starting and returning events match: - **Week 0** is always 100%, since it represents all of the users who completed the initial event. - The other cells compare the viewers in a given week to **Week 0**, displaying the percentage of the cohort who completed the event in that week. @@ -60,7 +82,7 @@ Reading the **Dec 04 2023** row of the above graph from left to right: - 92% of the people who completed the event in **Week 0** came back and completed it again in **Week 2**. ### Differing events -If the events differ: +If the starting and returning events differ: - **Week 0** represents users who completed both the initial and return events. - After **Week 0**, each cell displays the percentage of the **Users** column who completed the return event in that week. @@ -79,3 +101,4 @@ Reading the **Dec 04 2023** row of the above graph from left to right: [3]: /real_user_monitoring/browser/data_collected/#action-timing-metrics [4]: /real_user_monitoring/browser/advanced_configuration#user-session [5]: /help +[6]: https://app.datadoghq.com/product-analytics/segments diff --git a/content/en/product_analytics/dashboards.md b/content/en/product_analytics/dashboards.md index e69de29bb2d1d..64cb045017e99 100644 --- a/content/en/product_analytics/dashboards.md +++ b/content/en/product_analytics/dashboards.md @@ -0,0 +1,65 @@ +--- +title: Dashboards +description: Visualize your data to gain insight +further_reading: +- link: "/product_analytics/" + tag: "Documentation" + text: "Product Analytics" +--- + +## Overview + +The key to getting started with dashboards is knowing what kind of questions you ask yourself regularly. What are common issues your customers face? When a problem occurs, what questions help you find a solution? + +Creating a good dashboard is about bringing the answers to these questions to the surface. Also, it is important not to cram all of those thoughts into the same dashboard. Creating separate dashboards to pinpoint different issues can help you quickly find your answers. + +This guide gets you started on a path to creating dashboards. These basic dashboards enable team discussion and speed up issue resolution. + +## Create a dashboard + +To create a dashboard, click **+New Dashboard** on the [Dashboard List][1] page. + +{{< img src="product_analytics/dashboard/pana_dashboard_overview.png" alt="Adding a new dashboard" style="width:70%;">}} + + +Enter a dashboard name and choose a layout option. + +{{< img src="dashboards/create-dashboard.png" alt="Adding a new dashboard" style="width:70%;">}} + +Dashboards +: A grid-based layout, which can include a variety of objects such as images, graphs, and logs. They are commonly used as status boards or storytelling views which update in real time, and can represent fixed points in the past. They have a maximum width of 12 grid squares and also work well for debugging. + +Timeboards +: Automatic layouts that represent a single point in time—either fixed or real-time—across the entire dashboard. They are commonly used for troubleshooting, correlation, and general data exploration. + +Screenboards +: Dashboards with free-form layouts which can include a variety of objects such as images, graphs, and logs. They are commonly used as status boards or storytelling views that update in real time or represent fixed points in the past. + +## Refresh rate + +The refresh rate of a private dashboard depends on the time frame you are viewing. The shorter the time frame is, the more frequently the data is refreshed. Publicly shared dashboards refresh every thirty seconds, regardless of the selected time frame. + +| Time frame | Refresh rate | +|--------------|--------------| +| 1 minute | 10 seconds | +| 2 minutes | 10 seconds | +| 5 minutes | 10 seconds | +| 10 minutes | 10 seconds | +| 30 minutes | 20 seconds | +| 1 hour | 20 seconds | +| 3 hours | 1 minute | +| 4 hours | 1 minute | +| 1 day | 3 minutes | +| 2 days | 10 minutes | +| 1 week | 1 hour | +| 1 month | 1 hour | +| 3 months | 1 hour | +| 6 months | 1 hour | +| 1 year | 1 hour | + + + +## Further reading +{{< partial name="whats-next/whats-next.html" >}} + +[1]: https://app.datadoghq.com/product-analytics/dashboard/list \ No newline at end of file diff --git a/content/en/product_analytics/guide/rum_and_product_analytics.md b/content/en/product_analytics/guide/rum_and_product_analytics.md index 2c5806e62208b..534ee20b18bb6 100644 --- a/content/en/product_analytics/guide/rum_and_product_analytics.md +++ b/content/en/product_analytics/guide/rum_and_product_analytics.md @@ -84,5 +84,4 @@ See the full feature comparison table below. {{< partial name="whats-next/whats-next.html" >}} [1]: https://www.datadoghq.com/pricing/?product=real-user-monitoring#products -[2]: /product_analytics/journeys/#conversion [3]: https://app.datadoghq.com/rum/list? \ No newline at end of file diff --git a/content/en/product_analytics/segmentation/_index.md b/content/en/product_analytics/segmentation/_index.md index f59ae45620723..1204fd699bb25 100644 --- a/content/en/product_analytics/segmentation/_index.md +++ b/content/en/product_analytics/segmentation/_index.md @@ -21,7 +21,7 @@ The segments page includes a list of all of the segments you have created. You c The [User Profiles][3] page allows you to track and analyze the behavioral patterns of key users. You can scope down to specific users' behavioral data to help inform your decisions on product optimization and feature adoption. -{{< img src="product_analytics/segmentation/user_profiles_pana.png" alt="A view of the User profiles page." >}} +{{< img src="product_analytics/segmentation/userprofiles_pana-ga.png" alt="A view of the User profiles page." >}}

Example: See users who dropped before buying

diff --git a/content/en/product_analytics/session_replay/_index.md b/content/en/product_analytics/session_replay/_index.md index c797bde69db09..2ca0e8aac38bd 100644 --- a/content/en/product_analytics/session_replay/_index.md +++ b/content/en/product_analytics/session_replay/_index.md @@ -1,5 +1,5 @@ --- -title: Session Replay +title: Replaying User Activity description: Learn about how to capture and visually replay your users' web browsing or mobile app experience with Session Replay. aliases: - /real_user_monitoring/guide/session-replay-getting-started/ @@ -57,9 +57,9 @@ You can create a playlist of Session Replays to organize them by any patterns yo [1]: https://github.com/DataDog/browser-sdk [2]: https://www.rrweb.io/ -[3]: /real_user_monitoring/session_replay/browser/ -[4]: /real_user_monitoring/session_replay/mobile/ +[3]: /product_analytics/session_replay/browser/ +[4]: /product_analytics/session_replay/mobile/ [5]: https://docs.datadoghq.com/notebooks/ [6]: https://docs.datadoghq.com/account_management/audit_trail/ [7]: https://app.datadoghq.com/rum/replay/playlists/my-watch-history -[8]: /real_user_monitoring/session_replay/playlists \ No newline at end of file +[8]: /product_analytics/session_replay/playlists \ No newline at end of file diff --git a/content/en/product_analytics/session_replay/heatmaps.md b/content/en/product_analytics/session_replay/heatmaps.md index 075635d77b454..ce18002d12841 100644 --- a/content/en/product_analytics/session_replay/heatmaps.md +++ b/content/en/product_analytics/session_replay/heatmaps.md @@ -11,7 +11,7 @@ further_reading: tag: 'Blog' text: 'Visualize user interactions with your pages by using Scrollmaps in Datadog Heatmaps' --- - +## Overview {{< img src="real_user_monitoring/session_replay/heatmaps/heatmaps-landing.png" alt="An overview of the heatmap functionality." style="width:100%;">}} A heatmap (or heat map) is a visualization of your user's interactions overlaid on Session Replay data. Product Analytics has three different types of heatmaps: diff --git a/content/en/product_analytics/session_replay/mobile/_index.md b/content/en/product_analytics/session_replay/mobile/_index.md index c9baf7ca06839..ea793d2ad514e 100644 --- a/content/en/product_analytics/session_replay/mobile/_index.md +++ b/content/en/product_analytics/session_replay/mobile/_index.md @@ -8,4 +8,35 @@ further_reading: text: Session Replay --- -{{< include-markdown "real_user_monitoring/session_replay/mobile" >}} \ No newline at end of file +## Overview + +Mobile Session Replay expands visibility into your mobile applications by visually replaying each user interaction, such as taps, swipes, and scrolls. It is available for native apps on both Android and iOS. Visually replaying user interactions on your applications makes it easier to reproduce crashes and errors, as well as understand the user journey for making UI improvements. + +{{< img src="real_user_monitoring/session_replay/mobile/mobile_replay.mp4" alt="An example of a Mobile Session Replay recording" video="true" style="width:60%;">}} + +## Setup + +Learn how to [Setup and Configure Mobile Session Replay][1]. + +## Privacy options + +See [Privacy Options][2]. + +## How Mobile Session Replay impacts app performance + +See [How Mobile Session Replay Impacts App Performance][3]. + +## Troubleshooting + +Learn how to [Troubleshoot Mobile Session Replay][4]. + +
For Session Replay, Datadog supports RUM for native iOS and Android mobile apps, but it is not supported for smart TVs or wearables.
+ +## Further reading + +{{< partial name="whats-next/whats-next.html" >}} + +[1]: /product_analytics/session_replay/mobile/setup_and_configuration +[2]: /product_analytics/session_replay/mobile/privacy_options +[3]: /product_analytics/session_replay/mobile/app_performance +[4]: /product_analytics/session_replay/mobile/troubleshooting diff --git a/static/images/product_analytics/analytics/group/pana_group_by_action.png b/static/images/product_analytics/analytics/group/pana_group_by_action.png new file mode 100644 index 0000000000000..f23c454951df3 Binary files /dev/null and b/static/images/product_analytics/analytics/group/pana_group_by_action.png differ diff --git a/static/images/product_analytics/analytics/group/pana_group_by_loading_time.png b/static/images/product_analytics/analytics/group/pana_group_by_loading_time.png new file mode 100644 index 0000000000000..22315c00b95c4 Binary files /dev/null and b/static/images/product_analytics/analytics/group/pana_group_by_loading_time.png differ diff --git a/static/images/product_analytics/analytics/group/pana_group_distribution.png b/static/images/product_analytics/analytics/group/pana_group_distribution.png new file mode 100644 index 0000000000000..8dfac9049aa3b Binary files /dev/null and b/static/images/product_analytics/analytics/group/pana_group_distribution.png differ diff --git a/static/images/product_analytics/analytics/group/pana_group_search_bar.png b/static/images/product_analytics/analytics/group/pana_group_search_bar.png new file mode 100644 index 0000000000000..07f7f4dc2649b Binary files /dev/null and b/static/images/product_analytics/analytics/group/pana_group_search_bar.png differ diff --git a/static/images/product_analytics/analytics/pana_analytics_group_by.png b/static/images/product_analytics/analytics/pana_analytics_group_by.png new file mode 100644 index 0000000000000..64872b2adc2a7 Binary files /dev/null and b/static/images/product_analytics/analytics/pana_analytics_group_by.png differ diff --git a/static/images/product_analytics/analytics/pana_analytics_time_imterval.png b/static/images/product_analytics/analytics/pana_analytics_time_imterval.png new file mode 100644 index 0000000000000..7b2cc96af3dca Binary files /dev/null and b/static/images/product_analytics/analytics/pana_analytics_time_imterval.png differ diff --git a/static/images/product_analytics/dashboard/pana_dashboard_overview.png b/static/images/product_analytics/dashboard/pana_dashboard_overview.png new file mode 100644 index 0000000000000..6c96b2356d201 Binary files /dev/null and b/static/images/product_analytics/dashboard/pana_dashboard_overview.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_change_viz.mp4 b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_change_viz.mp4 new file mode 100644 index 0000000000000..d3724206a3cca Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_change_viz.mp4 differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_conversion.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_conversion.png new file mode 100644 index 0000000000000..dee2d4e69c112 Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_conversion.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_dropoffs.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_dropoffs.png new file mode 100644 index 0000000000000..b754bb6e0dffd Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_dropoffs.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_filter_by-2.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_filter_by-2.png new file mode 100644 index 0000000000000..773c406203abb Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_filter_by-2.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_filter_by_step.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_filter_by_step.png new file mode 100644 index 0000000000000..194c67345b91d Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_filter_by_step.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_overview.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_overview.png new file mode 100644 index 0000000000000..3cfca9921c944 Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_overview.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_query_value.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_query_value.png new file mode 100644 index 0000000000000..84978640bba7a Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_query_value.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_share_dashboard.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_share_dashboard.png new file mode 100644 index 0000000000000..a096db53a773b Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_share_dashboard.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_share_funnel.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_share_funnel.png new file mode 100644 index 0000000000000..8cb87a09b08b7 Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_share_funnel.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_timeseries.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_timeseries.png new file mode 100644 index 0000000000000..5be884067b097 Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_timeseries.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_toplist.png b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_toplist.png new file mode 100644 index 0000000000000..b4049d253fda1 Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_toplist.png differ diff --git a/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_video1.mp4 b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_video1.mp4 new file mode 100644 index 0000000000000..bc9d425332928 Binary files /dev/null and b/static/images/product_analytics/journeys/funnel_analysis/pana_funnel_video1.mp4 differ diff --git a/static/images/product_analytics/journeys/pathways/ga_pathway_diagrams_page.png b/static/images/product_analytics/journeys/pathways/ga_pathway_diagrams_page.png new file mode 100644 index 0000000000000..eb2a041cab143 Binary files /dev/null and b/static/images/product_analytics/journeys/pathways/ga_pathway_diagrams_page.png differ diff --git a/static/images/product_analytics/journeys/pathways/pana_pathway_page_img2.png b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img2.png new file mode 100644 index 0000000000000..1619a810b200f Binary files /dev/null and b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img2.png differ diff --git a/static/images/product_analytics/journeys/pathways/pana_pathway_page_img3.png b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img3.png new file mode 100644 index 0000000000000..6d119f4f99065 Binary files /dev/null and b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img3.png differ diff --git a/static/images/product_analytics/journeys/pathways/pana_pathway_page_img4.png b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img4.png new file mode 100644 index 0000000000000..44620e7fabc8f Binary files /dev/null and b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img4.png differ diff --git a/static/images/product_analytics/journeys/pathways/pana_pathway_page_img5.png b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img5.png new file mode 100644 index 0000000000000..3381a0ee79bda Binary files /dev/null and b/static/images/product_analytics/journeys/pathways/pana_pathway_page_img5.png differ diff --git a/static/images/product_analytics/overview_analytic_ga.png b/static/images/product_analytics/overview_analytic_ga.png new file mode 100644 index 0000000000000..358ee60fa1b5d Binary files /dev/null and b/static/images/product_analytics/overview_analytic_ga.png differ diff --git a/static/images/product_analytics/overview_funnel_ga.png b/static/images/product_analytics/overview_funnel_ga.png new file mode 100644 index 0000000000000..fc105515b886d Binary files /dev/null and b/static/images/product_analytics/overview_funnel_ga.png differ diff --git a/static/images/product_analytics/overview_pathways_ga.png b/static/images/product_analytics/overview_pathways_ga.png new file mode 100644 index 0000000000000..47f84e6b10a9b Binary files /dev/null and b/static/images/product_analytics/overview_pathways_ga.png differ diff --git a/static/images/product_analytics/overview_retention_ga.png b/static/images/product_analytics/overview_retention_ga.png new file mode 100644 index 0000000000000..93411465d2dde Binary files /dev/null and b/static/images/product_analytics/overview_retention_ga.png differ diff --git a/static/images/product_analytics/pana_charts_video.mp4 b/static/images/product_analytics/pana_charts_video.mp4 new file mode 100644 index 0000000000000..72a7952e738c0 Binary files /dev/null and b/static/images/product_analytics/pana_charts_video.mp4 differ diff --git a/static/images/product_analytics/pana_home_page.png b/static/images/product_analytics/pana_home_page.png new file mode 100644 index 0000000000000..04628afac44d3 Binary files /dev/null and b/static/images/product_analytics/pana_home_page.png differ diff --git a/static/images/product_analytics/pana_session_replay_page.png b/static/images/product_analytics/pana_session_replay_page.png new file mode 100644 index 0000000000000..7512ae5d2a41a Binary files /dev/null and b/static/images/product_analytics/pana_session_replay_page.png differ diff --git a/static/images/product_analytics/retention/pana_retention_export.png b/static/images/product_analytics/retention/pana_retention_export.png new file mode 100644 index 0000000000000..959f867dac0f5 Binary files /dev/null and b/static/images/product_analytics/retention/pana_retention_export.png differ diff --git a/static/images/product_analytics/retention/pana_retention_overview-2.png b/static/images/product_analytics/retention/pana_retention_overview-2.png new file mode 100644 index 0000000000000..bede3f559b617 Binary files /dev/null and b/static/images/product_analytics/retention/pana_retention_overview-2.png differ diff --git a/static/images/product_analytics/retention/pana_retention_timeframes.png b/static/images/product_analytics/retention/pana_retention_timeframes.png new file mode 100644 index 0000000000000..4adf5be4c4402 Binary files /dev/null and b/static/images/product_analytics/retention/pana_retention_timeframes.png differ diff --git a/static/images/product_analytics/segmentation/userprofiles_pana-ga.png b/static/images/product_analytics/segmentation/userprofiles_pana-ga.png new file mode 100644 index 0000000000000..ed3c3638df0ce Binary files /dev/null and b/static/images/product_analytics/segmentation/userprofiles_pana-ga.png differ