Team report

Analyze your team performance in Activity

Agent activity in Lexer Engage is recorded and stored in Lexer Activity. This tool has been designed to make reporting on your team super simple, so in this article we’re going to dive into the ways you can use each Activity report to help you find the one that best fits your reporting needs.

Volume of overall Engage Activity

  1. Customize your search
  2. Instant summary stats
  3. Explore your data in tables
  4. Export the data

The Summary report is where you’ll land when you first head into Activity, and provides the most amount of detail on the current state of all engagements in one view. As the layout and functionality is similar throughout each report in Activity, use this as a guide on getting to grips with navigating charts and tables throughout.

Volume of responses

To gain insight into the volume of customer service engagements from start to finish, head to the Cases report. If you’re looking to report on the volume of individual interactions, head into the SLA Report.

Cases combines all interactions with the same customer, and considers them all to be a single engagement. This differs from the SLA report, which looks at interactions with individual objects.

Customer wait time

How long is it taking to get back to customers? The SLA and Cases reports are the key to finding out.

At first glance, you’ll see the latest interactions, filtered by your chosen team/agent, and timeframe. Export the data from the tables at the bottom of each of these report pages to conduct your own analysis on the raw data.

Agent performance

The SLA report is a way of measuring the performance of your agents against an SLA benchmark. You can then use these benchmarks to build a report that shows when your agents responded to content, and determine whether this was an appropriate timeframe. The default Lexer SLA benchmark is 2 hours, meaning agents have two hours to begin an engagement. Contact Lexer Support ( if you’d like to update the SLA.

Understanding the SLA metric
In the Responses table on the SLA report, you’ll notice two SLA metrics: The “Agent SLA” and the “Customer SLA”. The “Agent SLA” is the handle time, from when you first take ownership, to closing - usually much shorter. The “Customer SLA” is from the time it takes the customer to publish a message, to your first response - usually longer. Both metrics measure against the 2 hour benchmark.

The ‘Responses’ table in the SLA report is one of the most informative areas of Activity, as each line in the table represents a single customer service interaction. Each interaction is accompanied by data on the agents’ response time, wait time, time sitting in the Inbox, and includes the two SLA metrics mentioned above.

Agent response time
This takes into account the first action time on a mention, and is calculated from the time the message was sent, to the last response, regardless of the agent that sent it. So it’s important to note that if one object is handled by more than one agent, this may result on a long ART, as the calculation is based on the actions per object, not the number of agents involved.

Click on each object to open up customer service interaction screen. You can use this to witness the full customer service interaction history, as well as send messages to the customers, and leave notes on objects if needed, without having to navigate back to Engage.

An export from this chart will provide you with rich details about the objects, such as customer names, dates, agent names, and topics assigned over time. This makes a really valuable chart for various types of analysis in external applications like Excel.

Team performance

The Team report is the fastest way to understand of what your team are currently working on. It provides you with tools to alternate between teams and time ranges, to learn the differences in workflow States by agents over time, so you can ensure engagements are being resolved.

  1. Your team’s current workflow status
  2. Your team’s workflow summarized
  3. Dive deeper on team details

Here you’re given chart of all messages being handled by agents across the given time range, which can be used to easily understand how much an agent has on their plate at any given time. Handy for finding any remaining, or forgotten messages - the colors of the bars represent the States of objects, as seen in the legend.

The tables at the bottom of the Team report give a deeper understanding of how your team are progressing in the selected timeframe, and how they compare against one another. The metrics show:

  • Team data: A breakdown of objects handled by each agent. This includes percentile representations of how many of these objects were being handled, how many were done so privately, whether they were within your SLA, customer wait times and agent response times.
  • Over agent SLA: A table that summarizes how many objects your agents have handled outside of the team’s SLA. This table can quickly summarize slow agent activity, or simply highlight where content may have slipped through.

Customer feedback

NPS reports are used to learn about the quality of customer service engagements. To see data on this report, NPS surveys must be submitted by agents during interactions. Find out more about setting up NPS surveys here.

Check out our guide to Lexer NPS to learn more about the metrics you see on this report.

Build benchmarks based on NPS scores from your customers

Most teams will have their own KPIs, or benchmarks set for NPS scores, though not every engagement may not be measurable, as no two meaningful engagements are identical. By promoting a healthy use of NPS surveys, and allowing time for the data to grow deeper, you’re allowing yourself a more accurate range of data to set benchmarks in.

Through Cases, you can export every customer engagement over a period of time. Included in this export are two data points - “NPS sent”, and “Case Classifications”. Combine these two data points to sort through the topics of interactions that have had NPS surveys sent to them.

Knowing this will help you keep tabs on the kind of interactions that your agents choose to send surveys to, allowing you to stay ahead of the curve on what topics may be earning your agents’ promoters.

Query your NPS data in Segment to discover more about the demographics of those that submitted them.

Keep track of agent actions

The Security report is a complete log of actions made by your agents inside Lexer’s products. Use the Security log to understand who has, or has not been performing actions; engagements that have taken place; and important edits to Workflow tools.

  1. A complete log of Agent actions in our products
  2. Filter by team, date, and time
  3. Quick search for specific entries

1. A complete log of Agent actions in our products

The Security log is a non-exportable breakdown of all actions performed by users. Every action generates a log, such as responding to an object, or applying a Classification. Actions that are logged include, but are not limited to:

Mention updated Applying Classifications
IdentityScratchPad Leaving an Identity Note
Group Updated Editing a Group setting in the Administrative side of the platform
Content Created A reply to a customer has been sent
Notification Sent Notifications on Saved Dives have been triggered
SavedFilter created/updated A new Saved Dive has been created, or has been updated
Scope created/updated A new Tier 1 filter has been created, or has been updated
Cluster updated A new Tier 2 filter has been created, or has been updated

Commonly, these items are used to work out if agents are active in the product beyond simply responding to customers. It’s also change log of Saved Dives and filters, so if you find a search has changed recently, you can find out who changed it here.

2. Filter by team, date, and time

Select a particular team or agent, date, and time frame for which you’d like to see a list of actions. This allows you to hone in on the the actions performed by teams or individuals in any given timeframe, showing complete platform transparency.

3. Quick search for specific entries

This is helpful for finding specific entries to evaluate a range of scenarios. For example, the agent involved, or time that a Saved Dive was updated, that caused an influx of new content to appear in the Engage Inbox.

September 23, 2022
Did this page help you?
Thank you! Your feedback has been received!
Oops! Something went wrong while submitting the form, for assistance please contact