Face/Off charts are great for benchmarking data across filters, companies, end users and assets. They give you a way to compare how segments perform over time at a granular level, like "average daily usage per subscription tier" or "time-to-value between industries".
So powerful - it’s basically like having a BI tool inside your customer platform!
When would you use Face/Off charts?
Face/Off charts are unique in that they combine metric data with qualitative categories, commonly via filters, allowing you to break down portfolio/filter metrics over time.
This means you could easily show:
"Average number of tickets per industry" in a Support team review meeting
"Product usage by ARR segments" in a Management Report
"Asset performance" in a Custom Company Profile, which now allows you to compare multiple Assets within the same company
"Compare the Top 5 customers within our SaaS segment with the rest of the SaaS segment, in terms of product usage" (going neatly hand-in-hand with our Top/Bottom list filters!)
Etc... The sky is the limit!
Face/Off Line vs. Bar chart
The Face/Off chart comes in two forms:
Face/Off Time Series Line, allowing you to visualise metrics as individual lines over time
Face/Off Stacked Time Series Bar, letting you present the data as stacked bars for each period
The main difference between them is the design, but we recommend using each in slightly different scenarios. The Face/Off Line is best suited for segment benchmarking, while the Face/Off Stacked Bar is best suited for evaluating segment contributions to the total.
Let's have a closer look at how they compare and when we recommend using which.
Face/Off Time Series Line
The Face/Off Time Series Line is similar to a “standard” Time Series Line. They both visualise metric data over time (different from Cohort Lines which visualise field data).
The key difference is what multiple lines correspond to in each of the charts:
What are typical use cases? Just like Time Series Lines, they are ideal for analysing how metric data changes over time, but with the added dimension of comparing segments.
For example:
Number of tickets each week - Top 20% of Companies by ARR, vs. bottom 20% of Companies by ARR
Number of chats each quarter - EMEA vs. France vs. UK vs. Belgium etc.
Average Health Score each month - High-touch vs. low-touch vs. all Companies
Face/Off Stacked Time Series Bar
The Face/Off Stacked Bar is comparable with the standard Stacked Time Series Bar chart, as both visualise metric data over time.
How to configure a Face/Off Chart
The setup for Face/Off charts is identical, whether you use the Bar or Line style - although we use a line to demonstrate!
This is probably one of the most complex charts to set up in Planhat.
The main elements are:
Choose a model - e.g. Company
Choose an associated metric (system or calculated metrics) - e.g. email
Choose whose data to include in the chart - your options are:
“All” - all records of your selected model, e.g. all Companies
“Filter” - select an existing filter you created on the Data Module. e.g. Enterprise customers.
“Company” (or other data models, dependent on the model you have selected) - you can choose one specific record to follow over time, such as Company X. This can be useful for using one particular record as a benchmark to compare other ones to.
Choose how to consider multiple values (e.g. for multiple Companies) within the time period. You want to pick the same operation for all your series, for a fair comparison. Options are:
Sum - For the Face/Off stacked bar, the bar segments will be totalled together, so “sum” is typically the most appropriate
Average (all) - Can be used for Face/Off Line charts as the lines are independent of each other
Average (values) - Can be used for Face/Off Line charts as the lines are independent of each other
Choose how to define your bar segments or lines - e.g. list fields such as “Country” work well. Optionally, if you have a lot of segments, you can sort them and limit the number shown.
Choose how to consider values over time. This affects the increments on the x-axis. Options are: this is the same as you have seen in other time-series charts - choose a time period and operation, e.g. “week (sum)”
Simple daily values (plotting days on the x-axis)
Sum of daily values across a period (week, month, quarter, year etc.)
Average of daily values across a period (week, month, quarter, year etc.)
You can also change the timespan (number of bars) and apply an offset if you like, as you have seen in other time-series bars\
Let's see this in action for a couple of examples:
Basic example: Do the largest or smallest customers produce the most tickets?
In the video below, we use Face/Off chart to understand if our biggest or smallest customers produce the most tickets. This is also a great combinatory use case of Face/Off with the Top/Bottom list filters!
An advanced example: these top 20%, how do CSMs feel about them?
After seeing that the Top 20% largest customers produce the most tickets, you might want to check out how usage and CSM score correlates in this top 20% segment. This utilises some deeper parameters in the Face/Off chart which you can access by pressing the "Show more" arrow under any series.