Overview
Toggl Hire now offers job and workspace analytics to help recruiters, HR teams, and hiring managers gain actionable insights into their hiring process. This feature provides a simple, static dashboard displaying key recruitment metrics, allowing teams to track their hiring performance and optimize their workflow.
This feature is available on Premium plans.
Accessing Analytics
To access analytics:
Navigate to your Toggl Hire workspace and open the Analytics section on the side panel.
View Workspace Analytics at the top for an overview of hiring trends across all job openings.
Access Job Analytics below by selecting a specific job from the dropdown menu.
Review key hiring metrics and use the data to improve your recruitment process.
Workspace Analytics
Workspace analytics provide an overview of hiring activity across your entire organization. These metrics help you track overall hiring trends and assess the efficiency of your recruitment process.
Understanding Workspace Metrics
Job Openings Overview
Active Jobs: The number of job openings currently open and accepting applications.
Paused Jobs: Jobs that have been temporarily put on hold.
Closed Jobs: Jobs that have been successfully filled or closed.
Hiring Speed & Efficiency
Average Time to Fill: Measures how long it takes from when a job is first opened to when an offer is accepted. If this number is high, it could mean that job requirements are too restrictive or that there are inefficiencies in the hiring process.
Calculation: This is determined by taking the total number of days from when each job was opened to when a candidate was marked as hired and averaging it across all jobs with at least one hire.
Important Note: If a job is reopened, this may skew the metric, as it does not differentiate between newly opened and reopened jobs.
Average Time to Hire: Measures how quickly a candidate moves through the pipeline once they’ve entered it. A long time-to-hire may indicate bottlenecks in screening, interviews, or decision-making.
Calculation: This is determined by calculating the number of days between when each hired candidate enters the hiring pipeline and when they accept an offer, then averaging it across all hired candidates.
Important Note: Like time to fill, reopening a job can impact this metric, as it does not account for multiple hiring cycles in the same job.
These insights help HR teams identify whether hiring delays are due to sourcing challenges, slow interview processes, or inefficiencies in decision-making.
Job-Level Analytics
Job analytics provide a deeper look into individual job openings, helping hiring managers track the performance of specific roles and adjust hiring strategies accordingly.
Key Job Metrics & Their Meaning
Job Details & Timeline
Created Date: The date the job was first created.
Open for (Days): The number of days since the job was created.
Active for (Days): The number of days since the first candidate entered the pipeline (either through a job application, taking a skills test, or manually added candidates).
Candidate Flow & Pipeline Efficiency
Active Candidates: The number of candidates still in the hiring process, across all pipeline stages. An active candidate is any candidate who has not been rejected.
Rejected Candidates: The total number of candidates who have been rejected, across all pipeline stages.
Candidates by Pipeline Stage:
A breakdown of active and rejected candidates in each pipeline stage.
New Candidates: Visualizes candidates who first entered the pipeline within the specified period. This includes candidates who completed a job application, submitted a test, or were added manually.
Hiring Speed & Decision Making
Time to Fill: Measures the number of days from when a job is opened to when an offer is accepted. If this is taking too long, you might need to adjust job visibility or hiring priorities.
Calculation: This is determined by tracking the number of days between when each job was opened and when an offer was accepted (a candidate was marked as hired). If multiple hires are made for the same job, the metric is averaged across all hired candidates.
Time to Hire: Measures the number of days from when the hired candidate enters the pipeline to when they accept an offer. If this is high, reviewing interview scheduling and offer processes may help speed things up.
Calculation: This is determined by calculating the number of days between when each hired candidate enters the hiring pipeline and when they accept an offer. If multiple hires are made for the same job, the metric is averaged across all hired candidates.
Using Analytics to Improve Hiring Decisions
Identify Bottlenecks: If candidates are stalling at certain stages, consider adjusting your screening or interview process.
Optimize Job Visibility: If few candidates are applying, review job descriptions and where openings are posted.
Reduce Hiring Delays: If time-to-hire is long, assess where delays occur in screening, interviews, or offers.
By leveraging these insights, hiring teams can streamline their recruitment process, reduce hiring time, and make data-driven hiring decisions.