Use this article to discover the metrics and attributes you can use to build Explore queries based on your usage of Zendesk Guide. These datasets are also used for the Guide pre-built dashboards (see Overview of the Zendesk Guide dashboard).
For more information about how to create queries with Explore, see Creating queries.
In this article:
Answer Bot dataset
This section contains the following topics:
Answer Bot dataset schema
Use this diagram to help you understand the elements of the Answer Bot dataset and their relationships.
Answer Bot metrics
This section lists and defines all metrics available in the Answer Bot dataset.
| Metric | Definition | Explore formula |
|---|---|---|
| Attempts | The answers that Answer Bot gave. | [Answer ID] |
| Answers | The answers that have been used as answers to questions. | IF ([Answer status - Unsorted]="Offered" OR [Answer status - Unsorted]="Clicked" OR [Answer status - Unsorted]="Resolved") THEN [Answer ID] ENDIF |
| Unsuccessful attempts | The answers that have not been offered to any questions. | IF ([Answer status - Unsorted]="Unoffered" ) THEN [Answer ID] ENDIF |
| Clicks | Counts successful Answer Bot 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 Answer Bot answers that resolved the end user’s request. | IF ([Answer status - Unsorted]="Resolved") THEN [Answer ID] ENDIF |
| Indirect resolutions | The number of Answer Bot answers that indirectly resolved the end user’s request.
In some situations, articles suggested by Answer Bot 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 Answer Bot offered suggestions from the total number of enquiries it attempted to answer. | D_COUNT(Offered answers)/D_COUNT(Attempted answers) |
| % Click-through rate | The percentage of answers clicked by end users from the total answers offered by Answer Bot. | D_COUNT(Clicked answers)/D_COUNT(Offered answers) |
| % Resolution rate | The percentage of enquiries resolved by Answer Bot from the total enquiries where it offered suggestions. | COUNT(Resolutions)/D_COUNT(Offered answers) |
| Suggested articles | Count of the suggestions made by Answer Bot. | [Suggestion ID] |
| Clicked articles |
The number of Answer Bot 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 from Answer Bot. | IF ([Suggestion resolved]="true" ) THEN [Suggestion ID] ENDIF |
| Rejected articles | The number of Answer Bot 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 Answer Bot suggestions that have been clicked by an end-user. | COUNT(Clicked suggestions)/COUNT(Suggestions) |
| % Rejection rate | The percentage of Answer Bot suggestions that have been marked as unhelpful by end users. | COUNT(Rejected articles)/COUNT(Suggested articles) |
| Answered tickets | Count of tickets where an Answer Bot response was generated, a suggestion was clicked, and this resulted in the ticket being solved. | 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 an Answer Bot response was not given. | IF ([Answer status - Unsorted]="Unoffered" ) THEN [Answer ticket ID] ENDIF |
| Answer clicked tickets | Count of tickets where an Answer Bot response was generated, which 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 with Answer Bot, 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 an Answer Bot 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 Resolved using an Answer Bot 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 Answer Bot 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 from Answer Bot suggestions compared to the total solved ticket volume where an Answer Bot response was given. | D_COUNT(Solved tickets)/D_COUNT(Answered tickets) |
| % Ticket non-reopened resolution rate | The rate of ticket resolutions provided by Answer Bot suggestions in comparison to total tickets where an Answer Bot answer was generated. | D_COUNT(Non-reopened solved tickets)/D_COUNT(Answered tickets) |
| % Ticket unassisted resolution rate | The rate of ticket resolutions that have not been re-opened provided by Answer Bot suggestions in comparison to total tickets where an Answer Bot 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 in Answer Bot, and this suggestion being clicked. | (Click time (min)) |
| Resolution time (min) | The duration in minutes between a suggestion being generated in Answer Bot, and this suggestion solving the ticket. | (Resolution time (min)) |
| Click time (hrs) | The duration in hours between a suggestion being generated in Answer Bot, and this suggestion being clicked. | VALUE(Click time (min))/60 |
| Resolution time (hrs) | The duration in hours between a suggestion being generated in Answer Bot, 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) |
Answer Bot attributes
This section lists and defines all attributes available in the Answer Bot dataset. You can use this diagram to help you understand the meaning of some of the attributes in the list:
| Attribute | Definition |
|---|---|
| Answer status | The status of a suggestion provided by Answer Bot. The status is set depending on the end-user's response. Values include Unoffered, Offered, Clicked or Resolved. |
| Answer channel | The channel on which Answer Bot interacted with the end user. Values include Email, Web Widget, Web form, API, SDK, Slack, and Agent. |
| Answer brand | The brand of ticket corresponding to the brand of the knowledge base from which Answer Bot generated suggestions for an answer. |
| Answer enquiry | The end user’s question for which Answer Bot looked for suggestions. The attribute values are limited to the first 255 characters. |
| Answer ID | The ID of the notification with suggestions sent by Answer Bot. |
| 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 Answer Bot response was triggered. |
| Suggested article clicked | The event of the suggestion generated by Answer Bot 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 by Answer Bot which led to the ticket being resolved. Values are True and False. |
| Suggested article rejected | The article suggestion generated by Answer Bot being marked as unhelpful by an end-user. Values are True and False. |
| Suggestion ID | The ID of the knowledge base article suggestion sent by Answer Bot. |
| Suggested article language | The language of the knowledge base article suggestion sent by Answer Bot. |
| Suggested article locale | The locale of the knowledge base article suggestion sent by Answer Bot. 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. |
| 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 by Answer Bot. |
| User role | The role of the user who was assisted by Answer Bot. |
| User ID | The ID of the user who was assisted by Answer Bot. |
| User email | The email address of the user who was assisted by Answer Bot. |
| User locale | The locale of the user who was assisted by Answer Bot. |
| User status | The Zendesk status of the user who was assisted by Answer Bot. Values are Active, Suspended or Deleted. |
| User tags | A list of tags associated with the user who was assisted by Answer Bot. |
| User time zone | The time zone of the user who was assisted by Answer Bot. |
| 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. |
| Time – Bot answer created | Includes several attributes that refer to the time when an answer was generated by Answer Bot containing relevant knowledge base articles. |
| Time - Bot answer last event | Includes several attributes that refer to the last answer notification from Answer Bot. |
| Time - Bot suggestion last event | Includes several attributes that refer to the last time Answer Bot triggered a suggestion. |
| Time – Bot suggestion clicked | Includes several attributes that refer the time a suggested article was clicked from an answer generated by Answer Bot. |
| Time – Bot suggestion resolved | Includes several attributes that refer to the time a suggested article was clicked from an answer generated by Answer Bot, 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 last updated | Includes several attributes that return the time when an article was last updated. |
Knowledge Capture dataset
The Knowledge Capture dataset contains metrics and attributes that relate to the Guide Knowledge Capture app. This section list all the available elements for the Knowledge Capture dataset. Use this dataset to help you understand the efficiency of selecting articles to deflect support tickets.
This section contains the following topics:
Knowledge Capture dataset schema
Use this diagram to help you understand the elements of the Knowledge Capture dataset and their relationships.
Knowledge Capture metrics
This section lists and defines all metrics available in the Knowledge Capture dataset.
| Metric | Definition | Explore formula |
|---|---|---|
| Knowledge Capture events | Knowledge base article updates made using the Knowledge Capture app. | [Knowledge Capture event ID] |
| Linked articles | Count of the number of articles linked using the Knowledge Capture app in a ticket. | IF ([Knowledge Capture type]="Linked") THEN [Knowledge Capture event ID] ENDIF |
| Flagged articles | Counts the number of articles flagged for update using the Knowledge Capture app in a ticket. | IF ([Knowledge Capture type]="Flagged") THEN [Knowledge Capture event ID] ENDIF |
| Created articles | Counts the number of articles created using the Knowledge Capture app in a ticket. | IF ([Knowledge Capture type]="Created") THEN [Knowledge Capture event ID] ENDIF |
| Resolution articles | Count of articles linked through the Knowledge Capture app that were marked as helpful by end users and resolved their request. | IF ([Knowledge Capture type]="Solved") THEN [Knowledge Capture event ID] ENDIF |
| % Resolution rate | The percentage of resolution articles against articles offered to end users via the Knowledge Capture app. | COUNT(Resolution articles)/COUNT(Linked articles) |
| Knowledge Capture tickets | Tickets where any update using the Knowledge Capture app took place. | [Knowledge Capture ticket ID] |
| Linked article tickets | Counts tickets where a knowledge base article was linked using the Knowledge Capture app. |
IF ([Knowledge Capture type]="Linked") THEN [Knowledge Capture ticket ID] ENDIF |
| Flagged article tickets | Counts tickets where a knowledge base article was flagged for update using the Knowledge Capture app. | IF ([Knowledge Capture type]="Flagged") THEN [Knowledge Capture ticket ID] ENDIF |
| Created article tickets | Counts the number of tickets where an article was created using the Knowledge Capture app. | IF ([Knowledge Capture type]="Created") THEN [Knowledge Capture ticket ID] ENDIF |
| Resolution article tickets | Count of tickets that were resolved by end users through articles linked via the Knowledge Capture app. | IF ([Knowledge Capture type]="Solved") THEN [Knowledge Capture ticket ID] ENDIF |
| % Agent engagement rate | The percentage of total tickets on which the Knowledge Capture app was used. | D_COUNT(Knowledge Capture tickets)/DCOUNT_VALUES([Ticket ID]) |
| % Article linking rate | The percentage of tickets where an article was linked using Knowledge Capture app to all tickets where a Knowledge Capture event took place. | D_COUNT(Linked article tickets)/D_COUNT(Knowledge Capture tickets) |
| % Ticket resolution rate | The percentage of tickets that were resolved by end users against tickets on which articles were linked via the Knowledge Capture app. | D_COUNT(Resolution article tickets)/D_COUNT(Linked article tickets) |
| Linked articles - Ticket average | The average number of articles linked using the Knowledge Capture app to all tickets where a Knowledge Capture event took place. | D_COUNT(Linked article tickets)/DCOUNT_VALUES([Ticket ID]) |
Knowledge Capture attributes
This section lists and defines all attributes available in the Knowledge Capture dataset.
| Attribute | Definition |
|---|---|
| Knowledge Capture type | The type of event performed by the Knowledge Capture app. Possible values are Created, Flagged, and Linked. |
| Knowledge Capture ticket ID | The ID of the ticket that was updated using the Knowledge Capture app. |
| Knowledge Capture event ID | The ID of the knowledge base article that was updated using the Knowledge Capture app. |
| Knowledge Capture brand | The brand of the knowledge base where the Knowledge Capture app was used. |
| Knowledge Capture language | The language of the knowledge base where the Knowledge Capture app was used. |
| Knowledge Capture locale | The locale of the knowledge base where the Knowledge Capture app was used. |
| 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 given to the ticket. |
| Ticket subject | The subject of ticket. |
| Ticket tags | The tags associated with a ticket. |
| Ticket type | The ticket type: Question, Incident, Problem, or Task. |
| 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. |
| 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 |
| Article translation URL | The URL of the knowledge base article. |
| Article author | The name of the user who originally created a knowledge base article. |
| User name | The name of the user associated with the article. |
| User role | The role of the user associated with the article. |
| User ID | The ID of the user associated with the article. |
| User email | The email address of the user associated with the article. |
| User locale | The locale of the user associated with the article. |
| User status | The Zendesk status of the user associated with the article. |
| User tags | A list of tags associated with the user for the article. |
| User time zone | The time zone of the user associated with the article. |
| Time – Knowledge capture event | Includes several attributes that return the time and date when an update using the Knowledge Capture app was registered. |
| 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 last updated | Includes several attributes that return the time when an article was last updated. |
| Ticket Status – Unsorted | The status of the ticket. |
| Ticket Priority – Unsorted | The ticket’s priority. |
| Ticket Type - Unsorted | The ticket type. |
24 Comments
Will visitor data from Guide/Help Center/Web widget/SDK, including search be available in Explore?
When I need to report on things like
I currently need to use a combination of Custom reporting in Insights, Zendesk native reporting and Google Analytics and put it all together in a spreadsheet.
Hi Jacob,
Thanks for your feedback! We are working on expanding our Guide content in 2019 by adding additional datasets. One of the key themes revolves around content consumption. I cannot share any specifics at this time, but I have noted your feedback. Once these new datasets are available, you should be informed via email.
Sounds good, thank you Hannah!
I second this request. This is a huge void for our analytics/metrics. Knowing how our customers are using our Help Center is half the battle.
Can you please give an ETA for when in 2019 these metrics will be available?
Please advise an ETA on this :-(
I am currently using the Zendesk Insights tab data for the content consumption dataset currently not available in Explore.
Is there an update on the availability of this dataset?
Hi Stephanie,
Thanks for reaching out! Can you clarify what you mean by content consumption dataset? I'm not seeing this listed in our Insight's metrics reference, so we'd like to make sure that we know what you're looking for before we check with our Explore team.
Best,
Any ETA on when we will get metrics for Guide in Explore? The current "Knowledge Capture" dataset is the only dataset and shows zero metrics on how customers are getting to and using our Help Center -it only shows what articles are being linked in Support tickets. This doesn't help us understand if those linked tickets are being read, and if they are helping with case deflection, etc. Having to use Google Analytics to try and piece this together is not sufficient.
Hi Judd,
Thank you for reaching out.
We fully understand the need to better understand how your Knowledge Base and Community contribute to your customer experience. We'll be kicking-off a research project in H2 to refine the vision, and we should be able to share more information re. the timeline then,
Kind regards
Vincent
H there,
Is there an update on when general reporting for Guide will be available to use in Explore?
We're particularly keen to see this since the standard Help Centre reporting metrics in Zendesk aren't working correctly, are giving incorrect numbers and cannot be relied upon for key reports to Stakeholders and partners.
I've raised this point with Support and our Account Manager who have suggested I use this article to add further weight to getting this issue fixed.
Thanks
Anneka
Hi Anneka, thanks for following up. We do appreciate the criticality of helping you understand how your Help Center is being consumed - covering both Knowledge Base and Community. Key areas include:
- enabling you to measure the impact of the content you are creating on the end-user experience
- enabling you to understand the end-user journey
- enabling you to identify what areas need more work
- enabling you to know who your top contributors are
We are still planning an in-depth research project in H2. We'll then be able to share more information on scope & timeline.
Many thanks for your continued patience,
Kind regards
Vincent
Hi Vincent,
Congratulations for Explore, it really improved reporting and is a great tool to use on a regular basis.
I am taking the opportunity to add a couple of use cases to be considered regarding Guide as a data set :
- % of users that visited the help center and created a ticket
- % of downvotes on articles
- Searches that lead to no click on any articles
Kind regards,
Louis
Hi Louis -
I encourage you to post your feedback to the Explore Product Feedback topic in the community, so that other users can up vote and add their comments as well.
Hey,
I want to measure "new vs known" where "known" is tickets linked to a pre-existing article (i.e not where a new article was created).
Which metric should I use?
Hey Andy,
You should be able to use the Linked Articles or the Linked article tickets metric to pull the information you're looking for.
Let me know if you have any other questions for me!
Now that we are well into Q1 2020, do we have an ETA for metrics in Explore for Guide on how customers are using our Help Center? When can we expect these metrics to be added for Guide in Explore?
Hey Judd,
No updates to share at this time as far as I know. I'll contact our Explore PM's and let them know about this post so they can provide any updates when available.
Cheers!
Hi, I'm trying to follow your article to add a couple of metrics to understand the level of engagement of our agents in creating and editing ZD Guide FAQs/Articles. Sounds like a good best practice you put forward, so how do I actually build that in ZD Explore? Thanks for your advice!
Hey EJ,
If you're looking to create queries with some available Guide data, you'll want to take a look at our Creating queries article which I've linked for you. The article you're commenting on now will show the available metrics/attributes you can use within the Guide Dataset.
I can't assist with creating reports from scratch but the above should point you in the right direction to get started.
Hope this helps!
Hi, are there any plans to add % Article flagging rate to this list? We use % Article linking rate very often and it would be very helpful to have a similar metric for flagged articles. Thanks!
Hello Andrey Bobrovskiy,
We have no announcements on the feature request currently. I would recommend sharing this with our developers in our product feedback forums so it can be considered for a future update.
Best regards.
+1 for Guide statistics on Zendesk explorer. We would like to be able to pull a list of ZD articles order by their ratings and views. I hope this feature will be available soon..
Hi all,
While viewing our AB metrics, I am a bit confused about the difference between:
Attempts, Answers, and Suggestions
Looking at my metrics in Explore, I see that we have a large amount of "Attempts" and "Answers" so that makes our suggestion rate high, but our overall resolution rate is low (5% across our brands)
I'm trying to understand why our RR is low and how we can improve it. I think it has to do with our generic AB bounce back email and thus low engagement with the articles suggested in there.
Any help/guidance would be greatly appreciated!
Hey all,
I'm curious as to how I would track solved tickets with no engagement (no links, creates, etc.). I considered doing a custom metric against total solved tickets - tickets with link, but I can't seem to get the former in the Guide attributes.
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