Key metric summary visualization
- Topics:
- Visualizations
CREATED FOR:
- Beginner
- User
Learn about the key metric summary visualization in Analysis Workspace, which lets you see how an important metric is trending within a single timeframe. It also lets you compare metric performance across two timeframes.

Transcript
Hi, this is Taylor Baker, product manager for Adobe Analytics. Today I’m excited to reveal a new visualization, the key metric summary. The key metric summary visualization lets you see how an important metric is trending within a single timeframe. It also lets users compare metric performance across two timeframes. It provides the benefits of multiple visualizations combined into one and those three visualizations that we’re combining into one are line, summary change and summary number, three already very popular visualizations within Adobe Analytics. Let’s jump in. First, we access the key metrics summary visualization through the visualization tab in the left rail or through the blank panel visualization selector, whichever is easiest for you. Next, we drag the key metrics summary from the left rail into the blank panel at the right. Here, we can see the visualization builder where we select multiple components, some optional. Let’s start with the required components, first, metrics. Metrics are the key metric you’d like to explore either a default metric in your instance or a calculated metric that you’ve created previously. Second, the primary date range, the main date you like to understand in your exploratory analysis with this visualization. But jumping into the optional metrics, the comparison date range is the date range you’d like to compare to the primary date range. Next, the segment, the segment that you’d like to apply to filter your analysis further. So let’s try to understand these metrics in the context of some use cases. The first use case is an analyst trying to understand how visits looked this month compared to last month. Next, say you’re a marketer exploring how lead generation for a specific lead type has changed from this month to the same month last year.
Or let’s say you’re an executive wanting to understand how new bookings changed from this quarter to last quarter.
Let’s go back to the first example use case I shared, an analyst trying to understand how visits looked this month compared to last month. I’ll select visits from the metric dropdown. Then I’ll select this month for the primary date range. Then I’ll select last month for the comparison date range.
And finally, I’ll leave segment blank for now and come back to edit that later. Here we see our result. The 28.2% decrease here is our summary change and indicates that the total number of visits from this month so far since we haven’t finished the month yet is 28% lower than the total number of visits for last month. The 319,000 number is the total number of visits for our primary date range, which in this case is this month. And our spark lines here show visit data for this month in blue and last month in gray. As you can see, you can hover over the primary or comparison spark lines and see data for that specific day. One of the biggest advantages of this visualization is the amount of flexibility we offer users in terms of how they want to present their data. First, the edit state. I mentioned earlier we would come back to choosing a segment. Let’s do that now. If we click on the pencil icon in the top left, you have access to the builder again and can switch or edit any component. Let’s filter this data for mobile web hits.
Done, here we can see the summary change and summary numbers have changed as well as the trends on the spark lines. We can also see that the segment has been applied in the legend where it shows us that we’re looking at visits data filtered for mobile web hits. In addition to the edit state, which offers a lot of flexibility in quickly digging into the visualization, there are a lot more settings that we built in based on user feedback. First is emphasize number value. So again, a lot of our users requested flexibility in terms of how they report out on their data, how their executives or senior leaders are wanting to see their data and one is what kind of data to emphasize. So here, instead of emphasizing the summary change, we’re emphasizing the number value.
Hiding or showing the legend cleans up our data visually and gives users some flexibility in terms of how large the visualization is and how much context they’re giving new users when they’re sharing the visualization.
Hiding and showing the spark lines, again, offers more flexibility in terms of just emphasizing the summary change and the summary number and you’ll notice when we hide the spark lines that the legend adjusts and is no longer visually referencing spark lines that are not displayed on the visualization. If you want some flexibility in terms of showing or hiding the comparison spark line, if you go into the settings, you can uncheck the box next to show comparison and you’ll notice that the comparison spark line has been removed from the visualization, emphasizing the primary data, but still showing the difference between the comparison data and the primary data, and still showing the summary number of the primary date range. One of the most requested features from users was show raw difference which is a setting that allows users to show instead of the summary number, the difference between the total number for the primary date range and the total number for the comparison date range which in this case is 125,000. If we want to abbreviate that value, we have that flexibility in the settings. And here, as we can see, that rounds that number to instead of 125,541, 126,000.
And after abbreviate value, one more option here for you is showing the max and min on the spark lines. If we go into the settings, we can click show in max and min on spark lines, and then we can see dots for the maximum and dots for the minimum on both the primary spark line and the comparison spark line. And here we can see within the tool tip, it shows that that point is a maximum for the primary spark line or over here a minimum on the spark line. Thank you so much for your time today in learning more about our new key metrics summary visualization. We’re really excited to see our users start to engage with this tool and to explore insights and make more informed decisions. Please be sure to share any feedback as you explore the tool and thank you so much for your time today. -
For more information, please visit the documentation
More help on this topic
Analytics
- Analytics tutorials
- Introduction to Analytics
- What is analytics
- What Can Adobe Analytics Do For Me?
- How Adobe Analysis Workspace Can Change Your Business
- It’s More Than Data. It’s Customer Intelligence
- Adobe Sensei and Adobe Analytics
- Customer Use Case - ServiceNow
- Customer Use Case - Accent Group
- Customer Use Case - The Home Depot
- Summit 2019 Super Session - Travel and Hospitality
- Summit 2019 Super Session - Retail
- Summit 2019 Super Session - High Tech
- Strategy & thought leadership
- Transitioning from other platforms
- Analytics Basics
- Customizing the UI
- Getting Help
- Analysis Workspace
- Analysis Workspace Basics
- Analysis Workspace quick intro
- Analysis Workspace overview
- Navigate the new landing page
- Start your analysis with a pre-built report
- Building a Workspace project from scratch
- Create and manage custom templates in Analysis Workspace
- Understanding how data gets into your Analysis Workspace project
- Foundational metrics in Adobe Analytics
- Component management in Analysis Workspace
- Selecting a report suite in Analysis Workspace
- View Analysis Workspace performance metrics
- Create bot reports
- Tips and Tricks
- Navigating Workspace Projects
- Data Dictionary in Analysis Workspace
- Starting your first project
- Training tutorial template
- Use folders in Analysis Workspace
- Copy and insert panels and visualizations
- Create a table of contents
- Right-click for Workspace efficiency
- Keyboard shortcuts
- Annotations
- View density
- Use filters
- Use multi-select drop-down filters
- Real-time reports
- Using Panels
- Using Tables, Visualizations, and Panels in Analysis Workspace
- Quick Insights Panel in Analysis Workspace
- Using the Attribution IQ Panel
- Media Concurrent Viewers Panel in Analysis Workspace
- Media Playback Time Spent Panel
- Using Drop-down Filters
- Using Panels to Organize your Analysis Workspace Projects
- Choose segments for a panel
- Multiple Report Suites in Analysis Workspace
- Next/Previous and Page Summary Workspace Panels & Reports
- Understanding attribution panel and lookback windows
- Building Freeform Tables
- Understand your data–freeform tables
- Use the left rail to build freeform tables
- Easy drag and drop to blank projects
- Work with dimensions in a freeform table
- Work with metrics in a freeform table
- Row and column settings in freeform tables
- Freeform table totals
- Use the freeform table builder
- Right-click for workspace efficiency
- Reorder static rows
- Use Attribution IQ in freeform tables
- Cross-sell analysis
- Freeform table filters
- Time-parting dimensions
- Visualizations
- Visualization types and overview
- Visualization use cases
- Data visualization playbook
- Getting data into visualizations
- Using component drop-downs in Workspace
- Area and area stacked visualizations
- Bar and bar stacked visualizations
- Bullet graph visualization
- Donut visualization
- Histogram visualization
- Unlocking insights with histograms
- Line visualization
- Combo charts
- Adding trend lines to line visualizations
- Map visualization
- Summary number and summary change visualizations
- Key metric summary visualization
- Text visualization
- More than words - Using text visualizations and descriptions
- Scatterplot visualization
- Treemap visualization
- Venn diagram visualization
- Use the cumulative average function to apply metric smoothing
- Flexible layouts
- Changing the scale/axis on visualizations
- Dimension-graph live linking
- Set the granularity for visualizations
- Link inside or outside of your project
- Customize visualization legends
- 100% stacked visualizations
- Table and visualization data source settings
- Build a time-parting heatmap
- Analyzing Customer Journeys
- Applying Segments
- Apply segments to your Analysis Workspace project
- Apply ad hoc segments
- Use different Attribution IQ models with segments
- Choose segments for a panel
- Use segments as Dimensions in Analysis Workspace
- Use segments to limit data in Analysis Workspace
- Quick segments in Analysis Workspace
- Building Customer Journey Segments
- Building Customer Journey Segments - Part 2
- Metrics
- Dimensions
- Calendar and Date Ranges
- Curate and Share Projects
- Attribution IQ
- Using Cross-tab Analysis to Explore Basic Marketing Attribution
- Adding side-by-side comparisons of Attribution IQ Models
- Attribution IQ in Calculated Metrics
- Using Attribution IQ in Freeform Tables
- Using the Attribution IQ Panel
- Using different Attribution IQ models with segments
- Algorithmic Model in Attribution IQ
- Custom Look-back Windows in Attribution IQ
- Cohort Analysis
- Cohort Analysis in Analysis Workspace
- Understand your data–Cohort Tables
- Overview of Cohort Tables
- Cohort Table Settings
- Churn Analysis with Cohort Tables
- Cohort Analysis Using Any Dimension
- Latency Analysis with Cohort Tables
- Calculate Rolling Retention in Cohort Tables
- Use Cohort Analysis to Understand Customer Behavior
- Voice Analytics
- How to Manage and Track Your Voice Assistant App Data
- Understand Differences Across Voice-Enabled Devices
- Finding Opportunities To Increase Engagement for Voice Apps
- Reducing Error Rates and Improving Success Rates in Your Voice App
- Understand User Behavior on Voice Assistants
- Understanding the User’s Voice Journey
- Analysis Workspace Basics
- Administration
- Key Admin Skills
- Creating an empowered community
- Simplify and spend less time training users
- Getting the Right People on Your Analytics Team
- Gaining a seat at the table
- Telling impactful stories with data
- Translating Adobe Analytics technical language in a non-technical way
- Working cross-functionally
- Are you asking the right questions?
- Admin Tips and Best Practices
- Download the implementation playbook
- Audit your data dictionary
- Create standardized naming conventions
- Create standardized code templates
- Create basic videos and training
- Create an internal Adobe Analytics site
- Use a global report suite
- Create a news & announcements project
- Drive success with executive summary dashboards
- Create Operational Dashboards
- Company Settings
- User Management
- Manage Report Suites
- How to Configure General Account Settings
- Customize Calendar Settings
- Configure Paid Search Detection
- Set up marketing channels
- Create marketing channel processing rules
- Manipulating incoming data with Processing Rules
- Configuring Traffic Variables (props)
- Configure traffic classifications
- Configure hierarchy variables
- Configuring Variables in the Admin Console
- Configure conversion classifications
- Configuring List Variables
- Configure Finding Methods
- Set Internal URL Filters
- Configuring Zip and Postal Code Settings
- Enable the Timestamp Optional setting
- Configure bot rules in Analytics
- Data Governance and GDPR
- Traffic Management
- Logs
- Key Admin Skills
- Implementation
- Implementation Basics
- Experience Platform Tags
- Implement Experience Cloud solutions in websites using Tags
- Basic configuration of the Analytics extension
- Configure library management in the Analytics extension
- Configure general settings in the Analytics extension
- Configure global variable settings in the Analytics extension
- Use custom code in the Analytics extension
- Use a data layer to set variables
- Use doPlugins and implementation plug-ins
- Configure easy download link tracking
- Configure easy exit link tracking
- Prepare Tags for your Analytics implementation
- Create data elements for the Analytics implementation
- Create a global page load rule
- Validate the global page load rule
- Create rules for special pages
- Create rules for success events
- Publish Tags libraries to stage and production
- Using JavaScript
- Components
- Segmentation
- Segment builder overview
- Finding and creating segments
- Rolling date ranges in segments
- Segment comparison in Analysis Workspace
- Segment containers
- Segment management and sharing
- Applying segments in Analysis Workspace
- Using segments as dimensions
- Using segments to limit data
- Differences between the segment builder and quick segments
- Sequential segmentation
- Before/After sequences in sequential segmentation
- Segmentation on distinct dimension counts
- Dimension models in segmentation
- Use ‘equals any of’ in segmentation
- Analytics Insider Webinar - Customer Segmentation Strategies
- Now just wait a segment… Using segmentation to discover new insights
- Calculated Metrics
- Calculated metric builder overview
- Calculated metrics - implementation-less metrics
- Calculated metrics - segmented metrics
- Calculated metrics - functions
- Approximate count distinct function in calculated metrics
- Quick calculated metrics in Analysis Workspace
- Manage your calculated metrics
- Attribution IQ in calculated metrics
- Use dimensions in calculated metrics
- Take your data analysis to the next level with calculated metrics
- Classifications
- Virtual Report Suites
- Activity Map
- Segmentation
- Additional Tools
- Exporting
- From the UI
- Data Warehouse
- Data Feeds
- Report Builder
- Upgrade and reschedule workbooks
- Add Segments to Multiple Requests at Once in Report Builder
- Anomaly Detection in Report Builder
- Edit Metrics across Requests
- Using Report Builder to learn the Adobe Analytics API
- Get started with Report Builder
- Schedule a Report Builder request
- Use Report Builder advanced delivery options for Power BI
- Integrations
- Experience Cloud
- Audience Manager
- Target
- Adobe Advertising DSP
- Configuring Advertising Analytics
- Implementing tracking templates into search engines
- Introduction to the Adobe Advertising DSP integration
- Create a Pre-launch campaign analysis
- Report on Advertising DSP marketing channels
- Create Analytics site journey profiles
- Create Analytics segments for activation and reporting
- Create Advertising DSP alerts with Adobe Analytics
- Create Analytics custom metrics with Advertising DSP data
- Create Advertising DSP site entry reports
- Create Advertising DSP dashboards
- Ad Hoc Analytics
- Power BI
- Magento
- Data Science
- Vertical-Specific
- Media Analytics
- Mobile App Analytics
- APIs
- Analysis Use Cases