Time Series Explorer

Customer Interactions over time, with powerful DIY capabilities

As we developed the Workspace Analytics capabilities, our customers also highlighted the need for flexibility in visualising interactions with customers on Slack. There are very very limited tools that provide customer intelligence on Slack, and none in the market have DIY capabilities.

This led to the creation of the Time Series explorer.

Use Case

Top accounts with SLA Breaches in a time period

In order to setup this time series representation, we will set the Show parameter to SLA Breached. This will give us the universe of all SLA Breaches across the workspace. Now, we can add Channel Name as a pivot using Compare By, in order to see the top channels with SLA breaches. Lastly, Date Range will host the From and To dates required for our analysis. The condition will look like below.

Top Account Tiers with Support Tickets in a time period

To see the tickets created by Account Tier, you can setup the Show to Tickets, Compare by to Account Tier and Date Range according to your requirements. Below is a representation of what this visual could look like.


Show (Subject Area that you want to visualise)

The ability to visualise Conversations, Requests, SLAs Breached as well as Tickets across customer channels.

Compare By (Group the Subject Area)

The pivots that allow you to group the relevant subject area basis CSM, Account Health/Account Tier, Channel Name, Users and more.

Date Range (Time period of interest)

Simply select the start date and end date in order to get a view of the customer engagement during this time period.

Filters (Additional criteria to identify specific insights)

Additional filtering criteria to ensure that your time series is reflective of the current use case that you are evaluating. You also get the ability to view the tabularised dataset below, and export to CSV for additional intelligence.

Attribute Descriptions

  • Total Shared Channels: The total Customer channels on your workspace where Thena is added.
  • Total Requests: The customer requests detected by Thena as actionable. These could include support requests, account requests, and even generic questions.
  • Total Tickets: The support tickets created with the relevant tool. The tool here could be Hubspot Tickets, Intercom, Freshdesk, Zendesk, Salesforce Cases or more.
  • Ticket Closure Time: This is the time taken to close a ticket. If you have a SLA for customer request resolution, or an internal Support SLA metric for resolution, then this becomes a key metric to track.
  • First Response SLA Breach: Setup the First Response SLA to be reminded whenever there is a lack of response to a customer message. You can also configure the First Response SLA to include working hours, holidays, count reactions as responses and more.
  • First Response Time Taken: This is the time taken to respond to a customer message. If you have a SLA for customer message response time, or an internal Support SLA metric for first response, then this becomes a key metric to track.
  • Channel/Account: In mapping your CRM Account to your customer channel, Thena now allows you to get broader perspective across your customer communication. This attribute is key to analysing customer engagement patterns.
  • CSM: With our CRM integration, you can pivot the relevant insights basis your CSMs. If your CRM data is not upto mark, you can also update the CSM manually. Using this pivot, a lot of intelligence can be provided straight to the CSM on their account, engagement pattern, opportunities and best practises.
  • Messages: Total number of customer messages are highlighted in this attribute.
  • ARR: What is the ARR of this account? This is pulled from the CRM integration.
  • NPS: What is the NPS for this account? This is pulled from the CRM integration.
  • Account Health: What is the account health for this account? This is pulled from the CRM integration.
  • Account Tier: What is the account tier for this account? This is pulled from the CRM integration