Key metric summary visualization

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.

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