Metrics and attributes for Zendesk AI agents (legacy)


Use this article to discover the metrics and attributes you can use to build Explore reports based on your usage of Zendesk bots. These datasets are also used for the Answer Bot prebuilt dashboards (seeOverview of the Answer Bot dashboard).


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Zendesk has renamed our bot capabilities. Answer Bot is now AI
agents, Flow Builder is bot builder, and Article Recommendations are
autoreplies with articles. The Explore dashboard
described in this article uses legacy names.

Use this article to discover the metrics and attributes you can use to build Explore
reports based on your usage of Zendesk bots. These datasets are also used for the Answer
Bot prebuilt dashboards (see

Overview of the Answer Bot dashboard

).
For more information about how to create reports with Explore, see
Creating reports.
This article contains the following topics:

Article Recommendations
dataset
Flow Builder dataset




Article Recommendations dataset

This section contains the following topics:

Article Recommendations
dataset schema
Article Recommendations
metrics
Article Recommendations
attributes




Article Recommendations schema

Use this diagram to help you understand the elements of the Article
Recommendations dataset and their relationships.




Article Recommendations metrics

This section lists and defines all metrics available in the Article
Recommendations dataset.


Note:
Article Recommendations metrics aren’t fully
supported for the messaging channel. Supported metrics include answers and
attempts, but not clicks and resolutions.




Table 1. Article Recommendations metrics







Metric
Definition
Explore formula




Attempts
All instances in tickets and chats where Article
Recommendations was available to recommend articles, regardless
of whether the bot identified relevant articles to
suggest.
[Answer ID]


Answers
Instances in tickets and chats where the bot identified
articles relevant to a customer’s query and suggested them to
the customer.
IF ([Answer status - Unsorted]="Offered" OR [Answer status -
Unsorted]="Clicked" OR [Answer status - Unsorted]="Resolved")
THEN [Answer ID] ENDIF


Unsuccessful attempts
Instances in tickets and chats where the bot could not
identify any articles relevant to a customer’s query and did not
make a suggestion to the customer.
IF ([Answer status - Unsorted]="Unoffered" ) THEN [Answer ID]
ENDIF


Clicks
Counts successful attempts where at least one generated
suggestion was clicked.
IF ([Answer status - Unsorted]="Clicked" OR [Answer status -
Unsorted]="Resolved") THEN [Answer ID] ENDIF


Resolutions
Count of recommended articles that resolved the end user’s
request.
IF ([Answer status - Unsorted]="Resolved") THEN [Answer ID]
ENDIF


Indirect resolutions
The number of recommended articles that indirectly resolved
the end user’s request.
In some situations, suggested articles
don’t resolve the customer’s enquiry directly but instead
point them in the right direction in the help center to find
the answer to their question. These resolutions are known as
indirect resolutions. Indirect resolutions are
reflected in
Resolutions,
Indirect resolutions
and
Answer status
fields.

D_COUNT(Resolutions)-COUNT(Resolution articles)


% Suggestion rate
The percentage of enquiries where the bot offered suggestions from the total number of
enquiries it attempted to answer.
D_COUNT(Offered answers)/D_COUNT(Attempted answers)


% Resolution rate
The percentage of enquiries resolved from the total enquiries
where it offered suggestions.
COUNT(Resolutions)/D_COUNT(Offered answers)


Suggested articles
Count of the suggestions offered.
[Suggestion ID]


Clicked articles

The number of suggestions that have been clicked by a
user.

IF ([Suggestion clicked]="true" ) THEN [Suggestion ID]
ENDIF


Resolution articles
Count of solved tickets solved through a suggestion.
IF ([Suggestion resolved]="true" ) THEN [Suggestion ID]
ENDIF


Rejected articles
The number of suggestions that have been marked as unhelpful
by end users.

IF ([Suggested article rejected]=TRUE) THEN [Suggestion ID]
ENDIF



% Article click-through rate
The percentage of suggestions that have been clicked by an
end user.
COUNT(Clicked suggestions)/COUNT(Suggestions)


% Rejection rate
The percentage of suggestions that have been marked as
unhelpful by end users.
COUNT(Rejected articles)/COUNT(Suggested articles)


Answered tickets
Count of tickets where articles were recommended, a suggestion was clicked, or the end user
marked the article recommendation as resolving their
issue.
IF ([Answer status - Unsorted]="Offered" OR [Answer status -
Unsorted]="Clicked" OR [Answer status - Unsorted]="Resolved" )
THEN [Answer ticket ID] ENDIF


Unanswered tickets
Count of tickets where a suggestion was not given.
IF ([Answer status - Unsorted]="Unoffered" ) THEN [Answer
ticket ID] ENDIF


Answer clicked tickets
Count of tickets where a suggestion was generated that
resulted in the ticket being resolved.
IF ([Answer Status - Unsorted]="Clicked" OR [Answer status -
Unsorted]="Resolved" ) THEN [Answer ticket ID] ENDIF


Solved tickets

Count of tickets with a status of
Solved.

IF ([Answer status - Unsorted]="Resolved") THEN [Answer
ticket ID] ENDIF


Non-reopened solved tickets
Count of tickets with a status of
Solved, that have
not been re-opened.
IF ([Answer status - Unsorted]="Resolved" AND
VALUE(Reopens)<1) THEN [Answer ticket ID] ENDIF


Reopened solved tickets
Count of tickets that were set to a status of
Solved
and were subsequently re-opened.
IF ([Answer status - Unsorted]="Resolved" AND
VALUE(Reopens)>0) THEN [Answer ticket ID] ENDIF


Agent unassisted solved tickets
Count of tickets with no Assignee set, and with a status of
Solved
through a suggestion.
IF ([Answer status - Unsorted]="Resolved" AND VALUE(Agent
replies)<1) THEN [Answer ticket ID] ENDIF


Agent assisted solved tickets
Count of tickets that are assigned to an agent, where the
agent has replied, and the ticket status is
Resolve
using
a suggestion.
IF ([Answer status - Unsorted]="Resolved" AND VALUE(Agent
replies)>0) THEN [Answer ticket ID] ENDIF


% Ticket usage rate
The rate of tickets that were assisted by suggestions in
comparison to total number of tickets.
DCOUNT_VALUES([Answer ticket ID])/DCOUNT_VALUES([Ticket
ID])


% Ticket resolution rate
The percentage of tickets resolved by suggestions compared to
the total solved ticket volume where a response was
given.
D_COUNT(Solved tickets)/D_COUNT(Answered tickets)


% Ticket non-reopened resolution rate
The rate of ticket resolutions that have not been re-opened
provided by suggestions in comparison to total tickets where an
answer was generated.
D_COUNT(Non-reopened solved tickets)/D_COUNT(Answered
tickets)


% Ticket unassisted resolution rate
The rate of ticket resolutions provided by suggestions in
comparison to total tickets where an answer was generated.
D_COUNT(Agent unassisted solved tickets)/D_COUNT(Answered
tickets)


Click time (min)
The duration in minutes between a suggestion being generated
and this suggestion being clicked.
(Click time (min))


Resolution time (min)
The duration in minutes between a suggestion being generated
and this suggestion solving the ticket.
(Resolution time (min))


Click time (hrs)
The duration in hours between a suggestion being generated
and this suggestion being clicked.
VALUE(Click time (min))/60


Resolution time (hrs)
The duration in hours between a suggestion being generated
and this suggestion solving the ticket.
VALUE(Resolution time (min))/60


Agent replies
Counts the total number of agent replies to a ticket.
(Agent replies)


Reopens
The number of times a ticket status changed from
Solved
to
Open.
(Reopens)







Article Recommendations attributes

This section lists and defines all attributes available in the Article
Recommendations dataset. You can use this diagram to help you understand the
meaning of some of the attributes in the list:



Table 2. Article Recommendations attributes






Attribute
Definition




Answer status
The status of a suggestion provided. The status is set
depending on the end user's response. Values include
Unoffered,
Offered,
Clicked
or
Resolved.


Answer channel
The channel on which a suggestion was offered to an end user
or agent. Values include:


Agents
(when an agent uses the Knowledge Capture
app or the knowledge section of the context panel from
within a ticket)

Conversation Bots
(on messaging channels
including Web Widget, mobile SDKs, and social messaging
apps)
API
Email

SDK
(Classic mobile SDKs only)
Slack
Web form

Web Widget
(Classic only)




Answer brand
The brand of ticket corresponding to the brand of the
knowledge base where a suggestion for an answer was
generated.


Answer enquiry
The end user’s question for which suggestions were offered. The attribute values are limited
to the first 255 characters. This attribute does not include
the Generate a reply and Don't answer based on articles bot
response options. To report on these, use the Content text
attribute in the Flow Builder dataset.



Answer ID
The ID of the notification with suggestions sent.


Answer resolution article ID
The ID of the knowledge base article which resolved the end
user’s enquiry.


Answer ticket ID
The ID of the ticket from which the response was
triggered.


Suggested article clicked
The event of the suggestion generated being clicked by an
end user. Values are
True
and
False.


Suggested article resolved
The event of the suggested article being clicked from the
answer generated that led to the ticket being resolved. Values
are
True
and
False.


Suggested article rejected
The article suggestion generated being marked as unhelpful by
an end user. Values are
True
and
False.


Suggestion ID
The ID of the knowledge base article suggestion sent.


Suggested article language
The language of the knowledge base article suggestion
sent.


Suggested article locale
The locale of the knowledge base article suggestion sent.
Values include
EN-US,
EN-GB,
DE,
FR,
RU.


Article ID
The ID of the knowledge base article.


Article ID and locale
The ID and locale of the knowledge base article.


Article translation title
The title of the knowledge base article in a specific
language.


Article translation URL
The URL of the knowledge base article.


Article author
The name of the user who originally created a knowledge base
article.


Ticket ID
The ID number of the ticket.


Ticket status
The current status of the ticket.


Ticket group
The name of the group where the ticket was assigned.


Ticket assignee
The name of the user to who the ticket is assigned.


Ticket brand
The brand of the ticket.


Ticket channel
The channel a ticket was created from.
For more information
about the ticket channels Explore collects, see
Understanding ticket
channels in Explore.



Ticket form
Ticket form used on the ticket.


Ticket organization
The name of the organization associated with the
ticket.


Ticket priority
The ticket’s priority.


Ticket problem ID
The ID of the associated problem ticket.


Ticket requester
The name of the user that requested the ticket.


Ticket satisfaction rating
The satisfaction rating of the ticket,
Good
or
Bad.


Ticket subject
The subject of ticket.


Ticket tags
The tags associated with a ticket.
For information about
filtering reports using tags, see
Reporting on ticket tags
using filters.



Ticket type
The ticket type.


Sharing agreement inbound
Affiliated instances of Zendesk Support and companies who
share tickets with the current instance of Zendesk
Support.


Sharing agreement outbound
Affiliated Zendesk accounts and companies tickets are shared
with.


User name
The name of the user who was assisted.


User role
The role of the user who was assisted.


User ID
The ID of the user who was assisted.


User email
The email address of the user who was assisted.


User locale
The locale of the user who was assisted.


User status
The Zendesk status of the user who was assisted. Values are
Active,
Suspended or
Deleted.


User tags
A list of tags associated with the user who was
assisted.
For information about filtering
reports using tags, see
Reporting on ticket tags
using filters.



User time zone
The time zone of the user who was assisted.


User organization name
The organization name of the user.


User organization ID
The organization ID of the user.


User organization domains
The domain name of the organization of the user, for example,
zendesk.com.


User organization status
The system status of the organization of the user, either
active or deleted.


User organization tags
The tags associated with the organization of the user.
For
information about filtering reports using tags, see
Reporting on ticket tags
using filters.



Intent
(Requires
intelligent
triage
)

A prediction of what the ticket is about. To see the possible values, open the Taxonomy tab of the
Intent settings page to see the AI Intents list under
the Taxonomy values heading.


Intent confidence
(Requires
intelligent
triage
)

The likelihood that the intent prediction is correct.
Possible values are
High,
Medium, and
Low.


Language
(Requires
intelligent
triage
)

A prediction of what language the ticket is written in. To see the possible values, open the Taxonomy tab
of the settings page.


Language confidence
(Requires
intelligent
triage
)

The likelihood that the language prediction is correct.
Possible values are
High,
Medium, and
Low.


Sentiment
(Requires
intelligent
triage
)

A prediction of how the customer feels about their request.
Possible values are
Very Positive,
Positive,
Neutral,
Negative, and
Very
Negative.


Sentiment confidence
(Requires
intelligent
triage
)

The likelihood that the sentiment prediction is correct.
Possible values are
High,
Medium, and
Low.


Time – Answer Bot answer created
Includes several
Answer created
attributes that refer
to the time when an answer was generated containing relevant
knowledge base articles.


Time – Answer Bot answer last event
Includes several
Answer event
attributes that refer to
the last answer notification.


Time – Answer Bot suggested article last event
Includes several
Suggested article event
attributes
that refer to the last time a suggestion was triggered.


Time – Answer Bot suggested article clicked
Includes several
Suggested article clicked
attributes
that refer the time a suggested article was clicked from an
answer.


Time – Answer Bot suggested article resolved
Includes several
Suggested article resolved
attributes
that refer to the time a suggested article was clicked from an
answer, which led to ticket being resolved.


Time – Ticket created
Includes several attributes that return the time
and date when tickets were created.


Time – Ticket solved
Includes several attributes that return the time
and date when tickets were solved.


Time – Ticket last updated
Includes several attributes that return the time
and date when tickets were last updated.


Time – Article created
Includes several attributes that return the time
when an article was created.


Time – Article updated
Includes several attributes that return the time
when an article was last updated.








Flow Builder dataset

This section contains the following topics:

Flow Builder
metrics
Flow Builder
attributes




Flow Builder metrics

This section lists and defines all metrics available in the Flow Builder
dataset.



Table 3. Flow Builder metrics







Metric
Definition
Explore formula




Total users
The number of unique users who received a message from
the bot. A user does not have to engage with the bot
(sending a message or clicking a quick reply) to be included
in this count.
[Sunshine Conversations app user ID]


Engaged with bot
The number of unique users who have sent a message to the
bot or responded to a prompt.
IF ([Activity event type] =
"user_input_received") THEN [Sunshine Conversations app user
ID] ELSE NULL ENDIF


Transferred to agent
The number of unique users who have successfully
completed the transfer step from the bot to an agent. A
Support ticket is created for each successful
transfer.
IF ([Activity event type] =
"agent_transfer_completed") THEN [Sunshine Conversations app
user ID] ELSE NULL ENDIF


% total users who engaged with bot
The percentage of total users who have sent a message to
the bot or responded to a prompt.
D_COUNT(Engaged with bot) / D_COUNT(Total
users)


% engaged users transferred to agent
The percentage of engaged users who have successfully
completed the transfer step from the bot to an
agent.
D_COUNT(Transferred to agent) / D_COUNT(Engaged
with bot)


User input count
The total number of user inputs (messages of any type)
received by the bot.
[Content text]


Total users in previous 30 days
The total number of users in the period from 62 days to
32 days before today.



Total users in last 30 days
The total number of users in the period from 31 days ago
to yesterday.



Engaged users in previous 30 days
Users who engaged with the bot in the period from 62 days
to 32 days before today.



Engaged users in last 30 days
Users who engaged with the bot in the period from 31 days
ago to yesterday.



Transferred users in previous 30 days
Users who were transferred from the bot to an agent in
the period from 62 days to 32 days before today.



Transferred users in last 30 days
Users who were transferred from the bot to an agent in
the period from 31 days ago to yesterday.



Containment rate
The proportion of engaged users whose
conversation was
not
transferred from the bot to an
agent. The inverse of
% transferred to agent.




Resolution feedback prompts


The number of times the bot asked for feedback
via an “Ask if question resolved” step.
Note:
This metric and the following
metrics are counted based on each instance of the event
and not aggregated per user. So if a user went through
the same flow and replied to a feedback prompt more than
once, this metric counts each instance of a prompt being
sent or a feedback reply interaction.




Resolution feedback replies
The number of feedback prompt replies received
by the bot.



% resolution feedback replies
The proportion of times the bot received a
reply after sending a feedback prompt. This is the count of
replies of any type divided by the count of prompts
sent.



Resolved feedback replies
The number of
resolved
feedback prompt
replies received by the bot (for example, “Yes, problem
solved”).



% resolved
The proportion of total replies that were
resolved
replies. This is the count of resolved
replies divided by the count of total replies.



Unresolved feedback replies
The number of
unresolved
feedback prompt
replies received by the bot (for example, “No, I still need
help”).



% unresolved
The proportion of total replies that were
unresolved
replies. This is the count of
unresolved replies divided by the count of total
replies.









Flow Builder attributes

This section lists and defines all attributes available in the Flow Builder
dataset.



Table 4. Flow Builder attributes






Attribute
Definition




Brand ID
The ID of the brand associated with the bot the
user engaged with.


Brand name
The name of the brand associated with the Flow
Builder flow the user engaged with.


Sunshine Conversations app user ID
The unique identifier of the user participating
in a messaging conversation.


Activity event type
The event type recorded as a result of certain bot
conversation interactions. Values include: Conversation
started (journey_started), Engaged with bot
(user_input_received), Transferred to agent
(agent_transfer_completed), (resolution_prompt_sent),
(subflow_switched), and (user_feedback_received).
Events
are recorded only for published answers. If answers are
removed, unpublished, or renamed, historical data isn’t
affected.



Channel
The Zendesk channel where the interaction took place. In
Sunshine Conversations terminology, a “channel” is referred
to as “source.type”.


Time - Activity occurred
Includes several attributes that return the
time and date when an activity (Conversation started,
Engaged with bot, or Transferred to agent) happened.


Language
The standard name for a language (for example, Simplified
Chinese).


Language code
The shorthand code for a language (for example,
zh-CN).


User input type
The type of user input received by the bot. Possible
values include
Option selected,
Message sent,
Form sent, and
Unknown.


Content type
This is effectively the same as user input type. User
input type is the human friendly name, while content type is
the raw value used by the system.


Content text
The text of the message sent to the bot. This includes
only messages sent as a result of selecting a quick reply
option (the
Option selected value in the
User
input type attribute). Free text entered by end
users is returned as blank values.


Answer ID
The ID of the answer.


Answer name
The name of the answer. This is referred to as
“intent” when creating an answer in bot builder.


Answer type

The type of answer. Possible answer types
are:


answer


initial
(For the greeting
standard response, if enabled)


fallback
(For the fallback
standard response)


unknown
(For legacy and
unexpected values)





Option is resolution feedback
Indicates whether the type of option selected
was a resolution feedback reply, as opposed to a standard
option. Possible values are
true
or
false. An
attribute of the
user_input_receivedevent.


Resolution feedback reply
Indicates how the user replied to the
resolution feedback prompt (when the bot asks for feedback
via an “Ask if question resolved” step). Possible values are
Resolved
or
Unresolved. An attribute of
the
user_feedback_receivedevent.








