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In this article


Maximize chat operation efficiency by utilizing's chat analytics to identify areas for improvement and optimize performance.

Explore the basis of Analytics


Filter through specific metrics such as period, manager, follower, and tags. In addition, if you press the magnifying glass button you can get quick access to the chats which make up that dataset. Here are the available filtering options:

  • Assignee and Follower: You can filter and view managers who are participating in the chat as either assignee or follower.

  • Team: You can filter and view the team responsible for the chat.

  • Chat goal: You can filter and view whether or not the chat goal has been achieved.

  • Chat tag: You can filter and view the tags assigned to the chat.

  • Integration: You can filter and view chats received through external messengers, phone calls, and emails.


You can look over the response time for every incoming inquiry, you can further inspect the data by setting filter conditions.

Next to each statistic category, you can see the rate of change(ROC). It shows the change in the statistic relative to the preceding time period. If there is no data in the preceding period, then the ROC is set as -.

E.g.) If you are filtering your statistics for the month of April (01/04→ 30/04) then the ROC statistic will show you the change from the statistic for the 30-day period of March (01/03→30/03)

Understanding the graphs

  1. First response time (WaitingTime / OperationWaitingTime)

    • This is the statistic that measures the period of time from the user’s first message until the operator’s response.

    • This metric is still measured if the operator sent the first message. In such a case, it measures the customer’s first message and the manager's follow-up message. In other words, it measures the time from a customer’s first message until the operator’s response after such a message

      • Equation: FirstRepliedAtAfterOpen - OpendedAt

      • OperationWaitingTime = FirstRepliedAtAfterOpen (Operation time) - OpendedAt (Operation time)

    • Example)

      • The Customer sends their first message at 1:03, and after the chat is opened the operator responds with their first message at 1:10. Therefore, the First response time for this chat is 7 minutes

      • The Customer sends their first message at 9:22, but then sends a second message at 9:25 and the operator responds at 9:30. Therefore the first response time is 8 minutes (30-22)

      • The Operator sends a message at first to the chat room at 11:00, but the customer doesn't respond until 11:30. Then at 11:32, the operator responds back. So, in this case, the first response time is 2 minutes.

  2. Average Reply time (AvgReplyTime / OperationAvgReplyTime)

    • This metric measures the average reply time for chats for your team. It will measure the time between your customers' first response, and your manager’s last message, and then normalize it over the entire length of the chat room. In layman’s terms, it is the average response.

      • Equation: AvgReplyTime = TotalReplyTime / ReplyCount

      • OperationAvgReplyTime = OperationTotalReplyTime / OperationReplyCount

  1. Resolution Time (ResolutionTime / OperationResolutionTime)

    • Measure the time from opening a chat until the time close the same chat.

      • ResolutionTime = ClosedAt - OpenedAt

      • OperationResolutionTime = ClosedAt (During Business Hours)- OpenedAt (During Business Hours)

  2. One-stop Closing Rate

    • One-Stop Closing Rate is a metric used to measure how many chats only have one operator assigned as a manager.

    • Even if the person in charge of the chat switches from A→B→A it is still considered one-stop closing because the same operator opened and closed the chat.

All of these statistics, except for first response time, use data from closed chat only. First response time uses Opened, snoozed, and closed chats as data.

View Options

  • Summary statistics: Median | Average

  • Time: All | Operating Hours only

  • Graph View: Timeseries | Distribution

Operating hours gives you the ability to look at a breakdown of your statistics but only for your operating hours, being able to increase in-hour efficiency.

  • Operating hours are set hours in the day when your customer service is actively seeking inquiries. As such, the operating hour's statistic allows you to parse the data only occurring when your team is present.

    • Example) If you have your office hours set from 9am - 12pm, and 1pm - 6pm:

      • If a new chat comes in at 10am and a manager responds at 11am → this interaction will count towards your analytics.

      • If a new chat comes in a t 11am but a manager responds at 12:30pm → this will not count towards the operating hours statistic.

      • If a new chat comes in at 8am but a manager responds at 10am → This interaction will likewise not count towards operating hours statistics.

      • If a chat comes in at 11am but a manager responds at 3pm → This counts towards the operating hour's statistics.

      • Finally, if a chat comes in at 3pm but ends at 11am the next day → Does not count toward statistics.

  • If your operating hours are changed while checking statistics, the operating hours will be applied to the data and the analytics may change depending on the operating hour's change.

    • Example) Let’s consider the case of operating hours for the month of June were 9am - 6pm for the first ten days of the month, then for the remaining twenty days changed to 10am - 5pm.

      • On June 9th, a new user chat is opened at 9:30am and on the same day a manager responds at 5:30pm → Counts toward operating hours statistics.

      • On June 12th, a new user chat is opened at 9:30am and a manager responds at 5:30pm → It will not count towards statistics because the operating hours changed.


Inflow is a metric measuring the total number of new chats, closed or opened chats, visitors, tags, pages, and other important filter metrics.

  1. Check the total number of visitors and consultations within a given period

    • Visitors

      • This metric is the total number of Unique Visitors (UV) who visited the homepage or app who also opened your Channel lounge.

      • If the same customer visits multiple times a day then they will only count as one UV.

      • Except for Page Visitors, inquiries received from external messaging inquiries (Instagram) are also counted as one visitor.

    • Chats

      • This shows the total number of chats in a given period.

      • If a customer starts a conversation again in a closed chatroom, the conversation will be counted as a new chat with a different start date.

      • If the same customer opens multiple chatrooms each chatroom counts as a separate chat.

  2. Check the distribution of opened/closed chats that occurred over a set period of time and date

    • Opened

      • Sum of all new chats during the predetermined period of time

    • Closed

      • Sum of all closed chats during the predetermined set of time

The number of chats is also color-coded, with the darkness of the color shade implying a large number of chats.

  1. Parse your chat inflow by tags, pages, and route

    • Chat Tags

      • Under the Chat Tags statistic, you can measure which tags are inquiring and opening chats and their ratio compared to other tags.

      • You can also break down certain tags into their subtags (such as if you had a “US” tag and then multiple subtags of “northeast, southeast, midwest, south, west, and northwest” for each region).

      • Chats without any tags also are included in this statistic.

    • Page

      • You can check from which pages on your website do chats come. For example, if someone opens the chat on the homepage it will count towards a homepage chat. Even if a customer moves to a different page and reopens their chat window, it will still count towards the original page.

      • There is no page information provided if the chat is opened via:

        • Support bot that is attached to a marketing campaign

        • External messengers(Instagram, Line, etc.)

    • Routes

      • During the set period, this statistic breaks down from which method chats come. For example, it breaks it down into support bots, marketing campaigns, and external messengers.

      • If multiple campaigns, support bots, or on-time marketing paths are running concurrently, they will be aggregated into general categories of “support bot, campaign, or one time message.

      • If an operator first starts a chat by opening a new user chat, or through a plug-in link, it will be shown as “other”.

    • Trend

      • This shows the trends of each category over a selected period of time.


Performance is a leaderboard for your team. It allocates a score to each operator based on a number of factors such as the number of chats assigned, One-Stop Closing Rate, First Response Time, and Resolution Time. Moreover, you can check the processing status of all the assigned chats to an operator (opened, snoozed, closed).

  • Operator Leaderboard

    • The leaderboard is a calculated score of multiple operator-specific variables. The leaderboard score is based on how efficiently each operator handled all of their chats, such as first response time, one-stop closing rate, and resolution time. As the number of assigned chats goes up, the more that operator’s score has weight on the leaderboard.

    • The leaderboard shows operators who have had at least one chat during the selected time period.

  • Chat Status

    • You can also parse the data into business hours, and also summary statistics such as average score and median score.

    • The graph shows the number of new chats over the selected time period (horizontal axis) whereas the vertical axis shows the number of chats. Color represents the status of the chats.

    • If all open chats are closed the day previous, and there are no new chats incoming, then the graph will show zero for your current day.

    • You can monitor the trends and status of your chats, and you can make sure that no chats are left to fall between the cracks. (Learn more about chat status)