You asked for a deep dive into Analytics—and we’re starting right here. Before we schedule a live session with our experts, we’re hosting a thread-based AMA to keep things flexible.
Analytics has been one of the most requested topics, and this format gives you the freedom to ask questions, share use cases, and learn at your own pace.
Based on your feedback and what comes up in this discussion, we’ll line up a live workshop soon.
Drop your questions, share your use cases, or simply follow along. Based on the feedback and questions from this session, we’ll tailor a live deep-dive in the near future.
This is a thread-based Coffee Chat, scheduled for June 4 - June 5 which means:
No live webinar or Zoom links.
Just drop your questions or thoughts on the event thread anytime during the scheduled days (EU & NA Friendly)
Our Product Managers will respond in real time across both days.
This is open for both CX & EX topics
Ask Us Anything:
We’ll kick things off with a few starter questions to guide the discussion—but you can post whatever is on your mind!
Which kind of reports do you find difficult to create?
Do you feel more use case specific documentation or tutorial videos will help? If yes, what use cases do you want us to create documentation or videos for?
Which is the one thing you would like to be fixed in Analytics?
Which user journeys or workflows in Analytics require a support ticket or a call with the support team?
Which is the one feature that you love about Analytics, and why?
Please add your answers by numbering them as A1, A2…
Mark your calendars and you can -
Bookmark this thread so you don’t miss out.
Post your questions early if you can’t join live.
Drop in anytime to follow the discussion or catch up later.
If you’d like to join this thread-based discussion, just drop a comment or like this post! I’ll make sure to send you a calendar invite so you can participate at your convenience during the scheduled dates. Our team of experts will be on standby to respond to your questions!
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Downside with the whole system is that no historic data is really saved.
Example: I like to know how many groups tickets has been in and if it has been moved between same group back forth more then 1 time.
It’s to follow up on routine’s, processes and documentation.
Thanks for your question, @Daniel Söderlund ! I believe you are referring to tracking any activities that are happening on the tickets, including movement of the ticket back and forth across groups. We’re aware of the request and it is under consideration for our future roadmap. In the meantime, we also encourage you to submit this idea on our community forum, as this will help increase its visibility and allow other users to vote on it, which in turn will assist us in prioritizing this request. You can log your idea here. Please be sure to select the ‘Analytics’ tag when submitting your suggestion
Hi, I'm not sure if these are the kind of questions you were expecting, or if it’s more general insight into our challenges, but maybe you can address a few points:
Tracking time of added items in tickets We'd really like to be able to measure when items are added inside a ticket (e.g. when we add a service request within an existing ticket). Currently, this item gets linked to the main ticket, and in Analytics, the report shows only the creation date of the main ticket. We'd like to see when the item was actually added.
Interactive filter limitations Sometimes in Analytics, I want to apply a filter all charts at once. Is it possible to include Custom Fields or Service Requests in the Interactive Filter?
Service request status timestamps We work with custom statuses in our company, what we are missing In analitycs is to get time of specific status in Service requests, so I would like to get timestamp of specific, custom status. Right now I have to go through API connection, because we have only created/closed/resolved in analitycs.
Incomplete data via API I don’t know if it’s question for you, but when I try to connect through API to get ticket activities not all records are stored, I have examples if required.
Scheduled export limitations The scheduled export from Analytics includes custom fields when filtering by a specific service request, which is great. However, I can't export all tickets/service requests for a specific day with those custom fields included. To do that, I need to use the API – and fetching data per ticket (especially custom fields or requested items) is very slow. We handle around 1,500 tickets daily, so keeping track of data efficiently is important to us.
We handle around 1,500 tickets daily, so keeping track of data efficiently is important to us.
Have a nice day and smooth AMA :)
Thanks for your questions @Finski ! We would really like to dig deep into this. I’ll DM to discuss more.
It would be good to be able to calculate the ratio of tickets solved to raised (tickets solved divided by tickets raised *100) shown as a percentage.
I created a custom metric for that, but the calculation is incorrect because it can’t handle the different date dimensions
Thank you @RobCrossHM for sharing this.
We’ll reach out to you directly to better understand the issue in detail, especially around how the date dimensions are impacting the custom metric calculation. This will help us explore the best way to support your use case.
Emailed Reports -- why on earth doesn’t the PDF contain the underlying data automatically and is there a way to force it to be included?
(I think I missed the time slot here… stuck in meetings again...ugh)
Hello @SW-Scott
This AMA isn’t tied to a specific time slot as it’s running across two full days. Our experts will be popping in and answering questions as they come in, so you haven’t missed a thing!
Emailed Reports -- why on earth doesn’t the PDF contain the underlying data automatically and is there a way to force it to be included?
(I think I missed the time slot here… stuck in meetings again...ugh)
@SW-Scott I believe you are referring to the schedules feature that allows you to schedule reports at a configured frequency to be delivered to the email of a set of recipients. Schedules can be created at 2 levels: report and charts.
For schedules created for reports, you only have the ‘PDF of graph data’ option in report format. Screenshot below.
However, for schedules created for charts, you have multiple options for report format, including CSV of tabular data (which is what I guess you are looking for). Screenshot below.
Hope this helps.
Hi @Amrit Mishra
So, if I have a Report with 4 Widgets, Managers want one email with the Cover Sheet then additional pages of all underlying data pertaining to each widget? They don’t want an email for each widget… The World needs fewer emails.
This is where the actual Report information that 100% of my managers need…. The bar charts and stuff are cute, but meaningless without the underlying data.
Underlying Data for Widgets
Thanks,
Scott
Some of the OOTB analytic reports seem to calculate the metrics wrong. It would be helpful to have the analytic report show how the metric is calculated...a data dictionary of sorts. Any thought to this?
@shannon.mejia We already have a data dictionary for all metrics and attributes that you can access from the Help Center. See screenshots below. However, we acknowledge that this doesn’t always answer the questions you might have related to metric calculations.
We are working on filling the gaps in the existing data dictionary where such formula, calculations, examples, etc. are missing. Additionally, we are also working on a feature to provide a summary of a chart. This summary, among other things, will tell exactly how the metric value displayed in the chart was arrived at.
Yes, the data dictionary is helpful as it is, but as you stated, it is not enough. The validity of the analytic numbers need to be explained how it is generated as some of the metrics look to be wrong if it is calculated the way I would assume.
It would be useful to have company information in Analytics.
EG - I want to show all of our companies, and how many tickets they have/average resolution time etc, but doing this on ticket data means that if a company hasn’t raised any tickets during the date range they don’t appear at all. I would need to see customers that haven’t raised any tickets as this could be a warning sign that they’re not engaging with us.
@RobCrossHM - I understand that you are trying to see companies that haven't raised any tickets within a given timeframe. This is a critical insight, as zero engagement can indeed be a warning sign.
Let me propose an approach you can use to achieve this in Freshworks Analytics.
Leveraging two group-bys
While directly displaying companies with zero tickets within a specific date range can be tricky due to how ticket-based metrics inherently work, we can achieve a similar and very useful outcome by using two group-by dimensions. This method allows you to identify trends in engagement over time, highlighting when a previously active company might have ceased engaging.
Metric: Select "Tickets" as your primary metric.
Group by 1: Group your data by "Company Name." This will list all companies that have raised at least one ticket during your selected overall time range.
Group by 2: Crucially, add a second group-by dimension for "Suitable time intervals" (e.g., "By Year," "By Quarter," or "By Month").
What this shows you:
By setting up your report this way, you'll be able to see the ticket volume for each company across different time periods. For example, in the attached screenshot: if "Acme xxx" raised 3 tickets in 2024 but no ticket in 2025 (no row in the summary table), that immediately flags them as a company that's no longer actively engaging.
Let me know if this helps you.
Regards
Hi @Amrit Mishra
So, if I have a Report with 4 Widgets, Managers want one email with the Cover Sheet then additional pages of all underlying data pertaining to each widget? They don’t want an email for each widget… The World needs fewer emails.
This is where the actual Report information that 100% of my managers need…. The bar charts and stuff are cute, but meaningless without the underlying data.
Underlying Data for Widgets
Thanks,
Scott
@SW-Scott Thanks for clarifying. We have noted this and will add it to our roadmap for future consideration. We also encourage you to submit this idea on our community forum, as this will help increase its visibility and allow other users to vote on it, which in turn will assist us in prioritizing this request. You can log your idea here. Please be sure to select the ‘Analytics’ tag when submitting your suggestion.
It would be useful to have company information in Analytics.
EG - I want to show all of our companies, and how many tickets they have/average resolution time etc, but doing this on ticket data means that if a company hasn’t raised any tickets during the date range they don’t appear at all. I would need to see customers that haven’t raised any tickets as this could be a warning sign that they’re not engaging with us.
@RobCrossHM - I understand that you are trying to see companies that haven't raised any tickets within a given timeframe. This is a critical insight, as zero engagement can indeed be a warning sign.
Let me propose an approach you can use to achieve this in Freshworks Analytics.
Leveraging two group-bys
While directly displaying companies with zero tickets within a specific date range can be tricky due to how ticket-based metrics inherently work, we can achieve a similar and very useful outcome by using two group-by dimensions. This method allows you to identify trends in engagement over time, highlighting when a previously active company might have ceased engaging.
Metric: Select "Tickets" as your primary metric.
Group by 1: Group your data by "Company Name." This will list all companies that have raised at least one ticket during your selected overall time range.
Group by 2: Crucially, add a second group-by dimension for "Suitable time intervals" (e.g., "By Year," "By Quarter," or "By Month").
What this shows you:
By setting up your report this way, you'll be able to see the ticket volume for each company across different time periods. For example, in the attached screenshot: if "Acme xxx" raised 3 tickets in 2024 but no ticket in 2025 (no row in the summary table), that immediately flags them as a company that's no longer actively engaging.
Let me know if this helps you.
Regards
That proposal still doesn’t work, if the customer hasn’t raised any tickets over the date range though, and we’re now only permitted to report on 12 month date ranges it could still leave me without a solution.
The Curated Agent Performance report has a feature that I would like to build in for some of my Team Managers but I cannot see how it is built even after copying it and examining the configuration. The Drop Down Date selection is a key example of this:
The Curated Agent Performance report has a feature that I would like to build in for some of my Team Managers but I cannot see how it is built even after copying it and examining the configuration. The Drop Down Date selection is a key example of this:
@SW-Scott please see this response by @arundhana:
If you need further clarification, please reach out to him on DM. He’ll be happy to help.
It would be useful to have company information in Analytics.
EG - I want to show all of our companies, and how many tickets they have/average resolution time etc, but doing this on ticket data means that if a company hasn’t raised any tickets during the date range they don’t appear at all. I would need to see customers that haven’t raised any tickets as this could be a warning sign that they’re not engaging with us.
@RobCrossHM - I understand that you are trying to see companies that haven't raised any tickets within a given timeframe. This is a critical insight, as zero engagement can indeed be a warning sign.
Let me propose an approach you can use to achieve this in Freshworks Analytics.
Leveraging two group-bys
While directly displaying companies with zero tickets within a specific date range can be tricky due to how ticket-based metrics inherently work, we can achieve a similar and very useful outcome by using two group-by dimensions. This method allows you to identify trends in engagement over time, highlighting when a previously active company might have ceased engaging.
Metric: Select "Tickets" as your primary metric.
Group by 1: Group your data by "Company Name." This will list all companies that have raised at least one ticket during your selected overall time range.
Group by 2: Crucially, add a second group-by dimension for "Suitable time intervals" (e.g., "By Year," "By Quarter," or "By Month").
What this shows you:
By setting up your report this way, you'll be able to see the ticket volume for each company across different time periods. For example, in the attached screenshot: if "Acme xxx" raised 3 tickets in 2024 but no ticket in 2025 (no row in the summary table), that immediately flags them as a company that's no longer actively engaging.
Let me know if this helps you.
Regards
That proposal still doesn’t work, if the customer hasn’t raised any tickets over the date range though, and we’re now only permitted to report on 12 month date ranges it could still leave me without a solution.
@RobCrossHM Acknowledge this as a workaround and not an ideal solution, but could you please elaborate a bit more on ‘… we’re now only permitted to report on 12 month date ranges...’? Are you facing issues while creating reports for a longer duration?
It would be good to be able to calculate the ratio of tickets solved to raised (tickets solved divided by tickets raised *100) shown as a percentage.
I created a custom metric for that, but the calculation is incorrect because it can’t handle the different date dimensions
Hi @RobCrossHM,
Thank you for sharing the screenshots and detailed explanation over ticket (#17958948).
From the visuals, it appears that the "Created Date" is set as the date range dimension in your custom metric setup. For consistency and accurate output, all metrics in a widget should use the same date range dimension.
Currently, in your widget:
"Tickets Created" and "Ticket Solved Ratio" are already using Created Date
"Tickets Resolved" is using the default date range of Resolved Date
To resolve this, please update the date range for Tickets Resolved to Created Date and apply the change. This should align all metrics and display the correct counts along with the Solved Ratio percentage.
(You can refer to the attached screenshots for clarity.)
Regarding your suggestion to include a "%" symbol during custom metric creation — we truly appreciate your feedback. We've noted this and added it to our roadmap for future consideration.
In the meantime, we also recommend submitting this idea via our Community Forum (here) and selecting the ‘Analytics’ tag. This will help increase its visibility, allow others to upvote, and aid our product team in prioritization.
Thanks again, and let us know if you need any further help!
It would be useful to have company information in Analytics.
EG - I want to show all of our companies, and how many tickets they have/average resolution time etc, but doing this on ticket data means that if a company hasn’t raised any tickets during the date range they don’t appear at all. I would need to see customers that haven’t raised any tickets as this could be a warning sign that they’re not engaging with us.
@RobCrossHM - I understand that you are trying to see companies that haven't raised any tickets within a given timeframe. This is a critical insight, as zero engagement can indeed be a warning sign.
Let me propose an approach you can use to achieve this in Freshworks Analytics.
Leveraging two group-bys
While directly displaying companies with zero tickets within a specific date range can be tricky due to how ticket-based metrics inherently work, we can achieve a similar and very useful outcome by using two group-by dimensions. This method allows you to identify trends in engagement over time, highlighting when a previously active company might have ceased engaging.
Metric: Select "Tickets" as your primary metric.
Group by 1: Group your data by "Company Name." This will list all companies that have raised at least one ticket during your selected overall time range.
Group by 2: Crucially, add a second group-by dimension for "Suitable time intervals" (e.g., "By Year," "By Quarter," or "By Month").
What this shows you:
By setting up your report this way, you'll be able to see the ticket volume for each company across different time periods. For example, in the attached screenshot: if "Acme xxx" raised 3 tickets in 2024 but no ticket in 2025 (no row in the summary table), that immediately flags them as a company that's no longer actively engaging.
Let me know if this helps you.
Regards
That proposal still doesn’t work, if the customer hasn’t raised any tickets over the date range though, and we’re now only permitted to report on 12 month date ranges it could still leave me without a solution.
@RobCrossHM Acknowledge this as a workaround and not an ideal solution, but could you please elaborate a bit more on ‘… we’re now only permitted to report on 12 month date ranges...’? Are you facing issues while creating reports for a longer duration?
I thought comms went out to say that the maximum duration that we could report on was 12 months - any reports with more than 12 month filters would be deleted?
It would be useful to have company information in Analytics.
EG - I want to show all of our companies, and how many tickets they have/average resolution time etc, but doing this on ticket data means that if a company hasn’t raised any tickets during the date range they don’t appear at all. I would need to see customers that haven’t raised any tickets as this could be a warning sign that they’re not engaging with us.
@RobCrossHM - I understand that you are trying to see companies that haven't raised any tickets within a given timeframe. This is a critical insight, as zero engagement can indeed be a warning sign.
Let me propose an approach you can use to achieve this in Freshworks Analytics.
Leveraging two group-bys
While directly displaying companies with zero tickets within a specific date range can be tricky due to how ticket-based metrics inherently work, we can achieve a similar and very useful outcome by using two group-by dimensions. This method allows you to identify trends in engagement over time, highlighting when a previously active company might have ceased engaging.
Metric: Select "Tickets" as your primary metric.
Group by 1: Group your data by "Company Name." This will list all companies that have raised at least one ticket during your selected overall time range.
Group by 2: Crucially, add a second group-by dimension for "Suitable time intervals" (e.g., "By Year," "By Quarter," or "By Month").
What this shows you:
By setting up your report this way, you'll be able to see the ticket volume for each company across different time periods. For example, in the attached screenshot: if "Acme xxx" raised 3 tickets in 2024 but no ticket in 2025 (no row in the summary table), that immediately flags them as a company that's no longer actively engaging.
Let me know if this helps you.
Regards
That proposal still doesn’t work, if the customer hasn’t raised any tickets over the date range though, and we’re now only permitted to report on 12 month date ranges it could still leave me without a solution.
@RobCrossHM Acknowledge this as a workaround and not an ideal solution, but could you please elaborate a bit more on ‘… we’re now only permitted to report on 12 month date ranges...’? Are you facing issues while creating reports for a longer duration?
I thought comms went out to say that the maximum duration that we could report on was 12 months - any reports with more than 12 month filters would be deleted?
@RobCrossHM That’s not the case. For Freshservice, we have a default reporting period of 2 years. For Freshdesk, currently there’s no such restriction. So you can create reports in Freshdesk for more than 12 months.
@Amrit Mishra I appreciate the ideas, but it’s still not going to solve the problem. My original post details the only true way to achieve this.
@Amrit Mishra I appreciate the ideas, but it’s still not going to solve the problem. My original post details the only true way to achieve this.
Sure @RobCrossHM. We have made a note of this requirement. We’ll consider it for our roadmap - to be able to view/group by entities that don’t contribute to the total no. of data points - to include nulls in the data set.
In the meantime, we also recommend raising this as an idea here and selecting the ‘Analytics’ sub-forum. This will help increase its visibility, allow others to upvote, and aid our product team in prioritization.
