Filtering Table Views for Conversations Created by a Playbook
To filter a table view to target conversations created from a Playbook, you'll follow these steps:
Open any Pending or Active Conversation table
Navigate to the conversation filters on the right-hand side
Add the conversation filter Created by Playbook
Select the operator, ie, is any of, is none of...
Select one or more Playbooks from the pulldown menu, depending on the operator you've added
Creating Widgets to Report on Conversations Created by a Playbook
To create reporting widgets on conversations created from a Playbook, you'll follow these steps:
Navigate to any Dashboard you manage
Add a widget from the available options, ie, a Metric widget
Select Pending or Active conversations as the Object
Select the property you want to display in your widget, ie, count all conversations
Add a Conversation filter to your widget
Select Created by Playbook
Select the operator, ie, is any of, is none of...
Select one or more Playbooks from the pulldown menu, depending on the operator you've added
Measuring proactive vs reactive outreach
To compare how much of your outreach is proactive (started by your team or by a Playbook) against how much is reactive (started by the customer), build two formula traits rather than one. A single trait that divides proactive conversations by reactive conversations returns a ratio, not the share of each.
For the proactive percentage:
Create a formula trait with a count-all aggregation on Conversations.
Filter to conversations where Started by is any of your CSMs, or Created by Playbook is any of your Playbooks.
Divide by a count-all aggregation on all active Conversations with no filters.
Set the trait output to Percentage.
For the reactive percentage, use the same structure with the filters inverted: Started by is none of your CSMs, and not created by a Playbook.
Set the Started by filter to is any of and name each CSM. Is set matches every conversation that has a sender, not only the ones your team started.
Formula traits hold only a current value and are not stored per point in time. A widget that groups conversations by the month they were created therefore shows today's trait value for the accounts tied to those conversations, not the ratio as it stood in that month, and past points can move as accounts' values change. To track the ratio over time, add each formula trait as its own Success Metric, which caches a daily value. Two Metric widgets side by side on a dashboard show the proactive and reactive percentages together.
Two things affect the averages shown: accounts with no value for the trait are left out of the average entirely, and a conversation linked to more than one account counts once per account.