TL;DR: If you are a customer on one of GoodTime's Professional or Enterprise product packages and our available reports in the Insight tab do not provide the data you need, we are also able to deliver a raw data feed via email on a daily basis. NOTE: This data is provided as a predefined data set and it is your responsibility to conduct any necessary filtering or pivoting to arrange this data in a way that supports your unique data queries. This being said, at the following links we have provided clear explanations of what each data set contains as well as some queries you may want to conduct with the data provided.
Daily Data Feed Options:
Daily data feeds allow you to have one of the following data sets delivered to your inbox daily:
- Daily Candidate Data .csv
- Daily Interviewer Data .csv
- Daily Training Data .csv
- Daily Scheduler Data .csv
- Daily Meet Data .csv
- Daily Notes (AKA Cancel Reasons) Data .csv
Why are these e-mail Data Feeds Useful?
Should your thirst for data be greater than the Insights Tab can provide, these data feeds allow you to easily pivot or build data queries as you see fit from the raw data each provides. Additionally, these daily e-mail data feeds can be easily ingested into a data visualization tool (we recommend recommend Google Data Studio) so that you can more clearly demonstrate to to rest of the organization how kick-ass the recruiting team actually is!
NOTE: If you are a GoodTime Professional or Enterprise customer you are also able to take advantage of GoodTime's S3 bucket option which allows for the above raw data to be delivered directly to an S3 bucket that your internal Data Analytics/ Business Intelligence team would have established.
How can I obtain this data?
If you wish to receive this 'Daily Candidate Data .csv' you need to provide the following information to your Customer Success Manager or Community CSM.
- The email(s) you would like your daily data .csv email sent to,
- The time (include your time zone) at which you want to receive this daily .csv email.
NOTE: These emails will be delivered to you by the email address alerts@trevor.io
GoodTime leverages the third-party tool Trevor.io to provide our customers with deeper analytic access to their interview data. GoodTime has conducted a security review of Trevor.io and trusts it as a third-party provider to deliver customer data (including PII data) directly to customers in a manner that meets all of our own data security policies. We have internal processes in place to ensure there is no opportunity for accidental release of PII data to anyone but whom the customer identifies. For further details of GoodTime's approach to security please click here: https://www.goodtime.io/security. You can also find the security policies for Trevor.io here: https://trevor.io/security/
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Daily Candidate Data .csv
The Daily Candidate Data email provides all associated details of interview events scheduled within your GoodTime account. With this additional data you can create your own pivot tables and graphs to track your scheduling efficiency and volume in greater detail. It is also possible to ingest this .csv directly into a visualization tool and build your own dashboards. This page provides an overview of the data included in the Daily Candidate Data .csv email.
Data Sets Included:
(NOTE: this data is sorted by queue/creation_date and represents at the interview level)
- candidate - Names of each candidate (remember this is PII data)
- job - The name of the job as pulled from your ATS
- stage - The name of the scheduling stage as pulled from your ATS
- interview_status
- priority - this column reflected the internal 'priority' tag that your schedulers may assign to a candidates when scheduling them (0=None, 100=High, 200=VIP)
- event_count - the quantity of individual events a candidate is schooled to conduct as part of their listed interview.
- interviewer_count - the quantity of interviewers who are scheduled as part of the listed interview
- creator
- coordinator
- recruiter
- hiring manager
- queue/creation_date - The date and time at which a schedule task is initiated in the dashboard
- candidate_avail_received - The date and time a candidate responds with their availability
- confirmed_date - The date an interview event is scheduled into a calendar and 'confirmed'
- interview_start_date - The date an interview is scheduled to take place
- updatedAt - this will capture the last date at which the interview was updated (
- roundup_date - The date an associated internal roundup/debrief meeting is scheduled to occur
- interview_template - The name of the scheduling template used to create the listed interview
- interview_note - If your team uses the interview notes filed in a standard way you can draw contextual information here regarding why and event was rescheduled/updated/cancelled.
- interview_URL - A link to the interview within your GoodTime instance
- atsApplicationId
- jobId
- atsStageId
- atsCandidateId
- jobID + candidateID
- GT Interview ID - This is a unique reference generated by GoodTime per interview.
Some Insights that can be drawn from the Daily Candidate Data set:
Candidate Response Time: Calculating the time between 'queue/creation_date' and 'candidate_avail_received' will provide you with insight into the time it takes for each candidate to respond to your Request Availability invites.
- Pivoting candidate response time by 'job' or 'jobID' will allow you to assess if there is a variance in candidate response time based on job.
- Pivoting this data by 'coordinator', will allow you to assess if there is a variance in candidate response time based on individual coordinator.
Turnaround Time / Coordinator Efficiency: Calculating the time between 'candidate_avail_received' and 'confirmed_date' will provide an accurate measure of the 'Turnaround Time' associated with each candidate. That is, the time it takes for each candidate to be scheduled into a calendar.
- Pivoting this data by 'coordinator', will allow you to assess in detail the time it takes for each coordinator to schedule the candidate assigned to them.
Lead Time / Interviewer Efficiency: Calculating the time between 'confirmed_date' and 'interview_start_date' will provide an accurate measure of the 'Lead Time' associated with each scheduled interview. That is, the time it takes between when a candidate is scheduled into a calendar and when the candidate actually gets to meet the scheduled interviewer(s).
- pivoting this data by 'job' or 'jobID' will allow you to assess if there is a variance in the turnaround time based on job (and by extension the associated team ob business interviewers engaged). It is feasible that an engineering role may have a shorter turnaround time to a marketing role, for instance, because a greater quantity of interviewers are engaged in the interviewing process.
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Daily Interviewer Data .csv
The Daily Interviewer Data email provides all associated details of interview events scheduled within your GoodTime account. With this additional data you can create your own pivot tables and graphs to track the engagement and efficiency of your business interviewer team. It is also possible to ingest this .csv directly into a visualization tool and build your own dashboards. This page provides an overview of the data included in the Daily Interviewer Data .csv email.
Data Sets Included:
(NOTE: this data is sorted by queue/creation_date and represents at the event level)
- Name - names of each interviewer (remember this is PII data)
- Email - recruiter email address
- Tags - a collected list of all tags associated with each interviewer (if you wish to review associated tags individually you will need to split the data presented here into multiple columns)
- Job - the Job title as pulled from your ATS
- Stage - the associated stage the interviewer was scheduled to interview for
- Template - the template that was used to schedule the listed interviewer
- Event_Title
- Accepted - NOTE: this data is most relevant when aggregated by interviewer
- Covered - NOTE: this data is most relevant when aggregated by interviewer
- Declined - NOTE: this data is most relevant when aggregated by interviewer
- AvgDeclineHoursBeforeEvent - This data appears in conjunction with a 'decline' and captures how far in advance of the listed event the interviewer declined.
- GT_InterviewID - This is a unique reference generated by GoodTime per interview. Through the use of the 'GT_InterviewID' field you can also connect the data presented in your 'Daily Interview Data' .csv with other daily .csv data sets to pull additional insights.
Insights that can be drawn from the Daily Interviewer Data set:
Interview volume by Interviewer: If you wish to pull data on a specific interviewer and share back the volume of interviews they have been hosting you can pull it via filtering the data by both the 'interviewer' and the 'creation_date'.
Interviews conducted by stage: It can be valuable to assess the quantity of interviews conducted at each stage of your interviewing funnel. There will typically be progressively fewer candidates interviewing the further down the funnel they travel. If your candidate quantity does not diminish as they travel through the funnel this can indicate a training gap where Hiring Managers and/or Recruiters are not comfortable rejecting candidates at the top of the funnel which instead sees this responsibility passed further down to face-to-face/final round interviewers. This data can be pulled by filtering by 'Stage' (you can also filter by 'stage' and 'job' to compare the funnel efficiency/pass-through rates of one role against another).
Interviews accepted/declined/covered: By filtering to a specific time range using the 'creation_date' field you can tally the specific number of interviews your interviewers have either accepted, declined, covered, or canceled over this period. If further aggregating this data by 'interviewer' you can identify which of your interviewers are conducting the most interviews.
Covered shout-out: When building or strengthening your recruitment culture it is often valuable to publicly acknowledge those interviewers who have stepped in, often at short notice, to cover another interviewer who has declined an event. You can easily build a report to track who is covering events by filtering the above data by 'covered' and then aggregating by the interviewer to receive a count by the interviewer of the number of events they have covered in the defined period. This is a classic carrot action you might use to strengthen your recruiting culture.
Decline call-out: Once again, when working to strengthen your recruitment culture it is often valuable to intentionally call out (privately or via their lead/HM is best) those interviewers who have declined an interview event with limited notice. Given that this action causes much unnecessary stress to the scheduling team and risks damaging your candidate experience if an event/interview needs to be canceled at the last minute there is value in building a report to track who is declining events at with what notice they decline. You can achieve this simply by filtering the above data by 'AvgDeclineHoursBeforeEvent'. This is a classic sick action you might use to strengthen your recruiting culture.
Tag/Training analysis: As this data set shows both the 'interviewer' name and 'event' / 'template' titles you can easily build a report that filters against these values to identify those interviewers who routinely host an event. If you see a common set of interviewers hosting an event this can be a good signal to build out a tag group to associate these interviewers with.
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Daily Training Data .csv
The Daily Training Data email provides additional details associated with the events of your interviewer training program. With this additional data you can create your own pivot tables and graphs to track the engagement and efficiency of your business interviewer team. It is also possible to ingest this .csv directly into a visualization tool and build your own dashboards. This page provides an overview of the data included in the Daily Interviewer Data .csv email.
Data Sets Included:
(NOTE: this data is sorted by 'training_path' and reflects individual training classes)
- training_path - The name of your training path
- Name - The name of your trainee
- email - The email of your trainee
- tags_recieved - The tag assigned
- tag_type
- Total Classes Completed - The quantity of classes each trainee has completed
- Total Classes Required (From Path) - The quantity of classes a trainee is required to complete
- Upcoming Classes
- First Completed Class - The date of the initial training class a trainee completed
- Most Recent Class Date
- Graduated - The date the listed trainee was graduated from all classes
- Enrollment Month
- Grad Month
- enrollment_duration_days - The duration a trainee has been in training
- grad_duration_days - The date between 'First Completed Class' and 'Graduated'
Insights that can be drawn from the Daily Training Data set:
Quantity of trainees in training: This data can be summarized to identify the quantity of trainees who are actively in training (excluding all trainees who have graduated).
Quantity of trainees graduated: If summarizing this data to only show those trainees who have graduated you can build a clear picture of how many trainees you graduate, and from which training paths, by month.
Trainees who have stalled: Tracking enrollment duration allows for you to identify those specific trainees who have been in training for too long a period. If comparing this data with 'total classes completed' you can also identify those trainees who may require additional support to complete their training.
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Daily Scheduler Data .csv
The Daily Scheduler Data email provides a summary of all your scheduler activity, based upon the week when the schedule/reschedule/cancellation action took place. This data is distinct from that provided in the Insights tab 'recruiting leaderboard' report as it captures all schedulers (even those who may have left your organization) and reflects when the schedule/reschedule/cancellation action takes place NOT based on when the interview is scheduled to occur.
With this additional data, you can create your own pivot tables and graphs to track the scheduler activity conducted by your team week-over-week. It is also possible to ingest this .csv directly into a visualization tool and build your own dashboards. This page provides an overview of the data included in the Daily Scheduler Data .csv email.
Data Sets Included:
(NOTE: by default, this data is sorted by month and represents at the coordinator and job level)
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Month - the month in which the listed event took place (represented as yyyy/mm)
-
Week - the 'week beginning date' in which the listed action took place (represented as yyyy-mm-dd)
-
Coordinator - the name of the Coordinator who scheduled the event
-
Recruiter - the name of the Recruiter associated with the scheduled event
-
Hiring Manager - the name of the hiring manager associated with the scheduled event
-
Job - the Job title as pulled from your ATS
-
Stage - the sage, as pulled for your ATS, at which the scheduling action occurred
-
Scheduled Interviews - the quantity of interviews scheduled by the listed Coordinator within the stated week against the listed job and stage
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Scheduled Events - this is a subset of the above 'scheduled interviews' count and captures individual events
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Rescheduled Interviews - the quantity of interviews rescheduled by the listed Coordinator within the stated week against the listed job and stage
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Rescheduled Events - this is a subset of the above 'rescheduled interviews' count capturing individual events
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Updated Interviews - the quantity of interviews updated by the listed Coordinator within the stated week against the listed job and stage
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Updated Events - this is a subset of the above 'updated interviews' count capturing individual events
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Cancelled Interviews - the quantity of interviews cancelled by the listed Coordinator within the stated week against the listed job and stage
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Cancelled Events - this is a subset of the above 'cancelled interviews' count capturing individual events
NOTE about Interviews & Events:
When considering an on-site/face to face Interview you may have multiple back-to-back events that comprise a single interview. Events are a sub-set of Interviews and your event count will always typically be greater than (or equal to) your interview count.
NOTE about Reschedules & Updates:
GoodTime captures your reschedules and updates based upon when your schedulers click either the reschedule or update buttons within GoodTime. We recommend defining internally to your scheduling team what you see as the difference between a 'reschedule' and an 'update' so that you can better track your scheduling activity. A common distinction we see is that any change to an interview or event that takes less than 30 seconds is considered an 'update'. Any change to an interview or event date or time (and which takes more than 30 seconds) is considered a 'reschedule'.
Insights that can be drawn from the Daily Scheduler Data set:
Scheduling quantity by week: If you were to group all scheduled_interviews by week and total the scheduled count you can develop a week-over-week analysis of the quantity of interviews scheduled
Scheduling quantity by coordinator: If you wish to understand the quantity of interviews and events scheduled by coordinator you can pull data by Coordinator and filter by week to create a week-over-week analysis.
Schedule quantity by job and stage: If you were to filter the data by job title and intentionally look over a longer time frame (perhaps the whole of the job's lifecycle if a 1-off role) you can quickly develop a view to the total quantity of interviews scheduled in support of a specific job as well as the stages at which most interviews occurred. If conducting this analysis across multiple roles you can develop clearer insight into the 'ideal' quantity of interviews you are required to schedule at top of funnel to maximize your chance of a successful hire.
Interviews scheduled/updated/rescheduled by job/stage: It can be valuable to assess the quantity of interviews that are scheduled, updated or rescheduled by both job and stage. This can provide specific insight into those roles which are updated or rescheduled more than the 'average'. A job that is updated or rescheduled more than the average may be an indicator of a disengaged interviewing team or an unnecessarily complicated interview loop structure. Further filtering this data by stage can further flag is some stages within a job are more inefficient than others.
Interviews accepted/declined/covered: By filtering to a specific time range using the 'creation_date' field you can tally the specific number of interviews your interviewers have either accepted, declined, covered, or canceled over this period. If further aggregating this data by 'interviewer' you can identify which of your interviewers are conducting the most interviews.
Cancel quantity by Job: It is valuable to not only track the quantity of cancellations which may occur but to also filter this cancellation data by Job to understand if there is any trend associated with those interviews typically canceled.
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Daily Meet Data .csv
If your company is making use of the 'GoodTime Meet' standalone scheduling tool you can request a 'Daily Meet Data' .csv report via email to track all details of meetings scheduled by your org within this tool.
The Daily Meet Data email provides the data listed below for each meeting scheduled via GoodTime Meet. With this data you can create your own pivot tables and graphs to track the meetings booked across your organization. It is also possible to ingest this .csv directly into a visualization tool and build your own dashboards. This page provides an overview of the data included in the Daily Meet Data .csv email.
Data Sets Included:
(NOTE: this data is sorted by 'training_path' and reflects individual training classes)
- Scheduler - The name of the individual within your organization who originated the Meet booking URL.
- Interviewers - If additional interviewers to the 'Scheduler' are involved in the meeting they will be listed here.
- Attendee - The name of the attendee who was invited to book a Meet meeting.
- startTime - The date and time at which the meeting is scheduled to occur (note all times are listed in UTC)
- status -
- title - The calendar event title associated with the Meet meeting listed.
- url - The Meet URL used to book the meeting in question
- createdAt - The date and time at which the attendee selected their preferred date and time to meet and the event in question was created on a calendar.
Insights that can be drawn from the Daily Training Data set:
Meetings by Scheduler: By simply grouping this data by scheduler you can then count the quantity of Meet meetings and individual scheduler has conducted over a specific time frame.
If you also group this data by URL you can further identify the qty of specific interview typer each scheduler has conducted over a specified time frame (we recommend using descriptive Meet event titles to allow for easier sorting).
Scheduling speed: By comparing the time between the 'createdAt' and 'startTime' time stamps you can calculate the time it takes for each of your attendees to book a meeting with you using these Meet booking links.
If you were to further group this data by URL you can see if some booking links generate a more efficient scheduling process than others.
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Daily Notes (AKA Cancel Reasons) Data .csv
It is common for GoodTime users to want to track the reasons why an interview was cancelled or rescheduled. While GoodTime does not have an in-app mechanism (within the Insights tab) to track these update or cancel reasons this Daily Notes Data .csv report can be used to surface these reasons. To successfully leverage the Daily Notes Data .csv to surface reschedule and cancel reasons your scheduling team need to consistently input these reasons into the GoodTime 'Notes' field prior to updating or cancelling an event (please see the 'How to capture Reschedule and Decline Reasons' section below for best-practice advice).
The Daily Notes Data email provides the data listed below for each interview that has a note attached (interview without a note will not be surfaced). With this data you can create your own pivot tables and graphs to track the reasons why an event might be rescheduled or updated as well as whether this action was candidate or interviewer initiated (please see the 'How to capture Reschedule and Decline Reasons' section below for best-practice advice).
It is also possible to ingest this .csv directly into a visualization tool and build your own dashboards. This page provides an overview of the data included in the Daily Notes Data .csv email.
Data Sets Included:
NOTE: this data is sorted by 'note_date' and reflects every interview with an associated note. Where multiple notes are added to an interview each will be captured on a separate line. If you want to only capture the most recent note for an event you can filter for duplicate interview URLs and eliminate all entries but the most recent as per the note_date field.
- candidate - The name of the candidate associated with the interview.
- note - Free text detail of the Note added to the interview event by your scheduling team
- note_count - If more than 1 Note has been added to an interview the qty will be listed here.
- note_creation - The date and time at which the note was created
- note_creator - The logged in GoodTime user who created the listed note
- coordinator - The name of the coordinator associated with the scheduled interview.
- jobName - The job name from your ATS associated with this scheduled interview.
- stageName - The stage name from your ATS associated with this scheduled interview.
- template - The name of the template used within GoodTime to schedule the listed interview.
- interview URL - The unique URL associated with the listed interview (will also hyperlink to the interview in question).
How To Capture Reschedule and Decline Reasons [BEST PRACTICES]:
To get the most from the Daily Notes .csv report (especially if you wish to use it to track reschedule and cancel reasons) you will want to align the annotation process of your scheduling team as such:
- Identify a naming convention internal to your team/company to help you consistently annotate why an event was rescheduled. The following table provides some example naming conventions you may wish to use when annotating a reschedule or cancel action:
NOTE:Scheduling Event: Demo Annotation - Option 1: Demo Annotation - Option 2: Update - Candidate Initiated UPDc; CraneU} Update - Interviewer Initiated UPDi; IbisU} Reschedule - Candidate Initiated RESc; CraneR} Reschedule - Interviewer Initiated RESi; IbisR} Cancel - Candidate Initiated CANc; CraneC} Cancel - Interviewer Initiated CANi; IbisC}
- This table only provides examples of consistent annotation naming conventions you might like to use. Please personalize for your own organization and scheduling needs as appropriate.
- Consistency is key in these annotations as they will easily allow for you to filter the raw data from the Daily Notes .csv to easily analyze the qty of interviews rescheduled or cancelled over time. Option 1 allows for easy filtering to see Update vs Reschedule vs Cancel reasons. Option 2 uses the name of birds to allow for easy filtering of Candidate (Crane) initiated vs Interviewer (Ibis) initiated actions.
- If you personalize your annotations you should aim to use a unique string of text in order to minimize the chance your annotations will be mistaken for another test string. The text strings 'Crane' and 'Ibis' are used intentionally as they are highly unlikely to be mistaken for any other text within the scheduling workflow; even if your team adds additional free-text to the note for context.
- Using consistent punctuation after your initial annotation code will allow for you to split the data at this punctuation point for deeper analysis should you with to also include a free-text by-line. Using unique characters like ';' or '{' allow for you to split the text at that character to more accurately analyze your reschedule and cancel reasons by excluding any additional text added to the notes field.
- Train your scheduling team to consistently use the relevant annotation within the notes field prior to conducting an update, reschedule or cancel action so that the context is captured alongside that scheduled event.
- Once your team is consistently adding annotation codes in your Notes field you can easily filter the Daily Notes Data .csv file by the notes field to develop a greater insight into what factors are driving your reschedule and cancellation actions.
The daily Note Data .csv also includes details of role and template so you can more easily draw conclusions regarding whether a specific role or template is more likely than average to generate reschedule or cancellation actions. Also included is a direct URL link to the interview in question so you can easily jump to that interview within your GoodTime dashboard for additional context (this field is unique to each interview so it can also be used to identify those interviews with multiple notes attached)
NOTE:
- We recommend BEST PRACTICE being to include the department name/abbreviation as a prefix to each of your template titles. Doing this will further support your ability to filter your Update, Reschedule, and Cancel reasons by department without the need to combine or pivot this data set in any way.
- For example;
DO NOT title you template: 'Backend Engineer - Onsite - Zoom'
INSTEAD use the title: 'Eng} Backend - Onsite - Zoom'
The second option will much more easily allow for you to filer all results by the 'Eng}' prefix to better understand your Update, Reschedule, and Cancellations reasons for the Engineering department (for example).