Distribution of incoming messages

You responded to <b>%{count}</b> received in the last %{formatted_points} (roughly %{rate}/%{granularity}).

That's <b>%{direction} %{change}%</b> over the previous %{formatted_points}.

In the previous period you responded to <b>%{previous_count}</b>.

Here are incoming messages distributed by %{granularity}, segmented by how long users waited for a response:

Weekdays

It's also helpful to see how many messages users typically send on days and hours of the week, and how long they usually have to wait for a response.

In the punchcard chart below, <strong>circle size</strong> indicates the number of messages received and <strong>circle color</strong> indicates the how long users waited to receive a response. Areas with a <strong>blue background</strong> indicate <em>coverage</em> (times when agents are regularly responding to tickets).

Graded messages

Average grade

Average wait time

Hourly averages

Graded messages

Average grade

Average wait time

<b>Coverage:</b> You have an average of %{agent_count} agents with %{response_count} responses on %{day_and_time}.

Awaiting first response

Median open time

Host

Source: %{source}

Include 1 attachment

Include %{count} attachments

Project

Last updated

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hour

1 hour

%{count} hours

hr

1 day

1 week

%{count} weeks

1 month

%{day} at %{hour}

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1 message

%{count} messages

Graded message

Graded messages

Graded response

Graded responses

Mean response time

Average wait time

Response time distribution