This feature is currently in open beta.
Information in this article may not reflect the most up-to-date changes, as the product is actively being updated.
Greenhouse Analytics is built around a simple structure: you define a dataset, visualize it, and organize those visualizations into dashboards your team can explore and act on. This article walks you through the main workflow – building a data view, using that data view to power visualizations, and organizing everything onto a dashboard.
Key concepts and objects
Greenhouse Analytics uses three core objects that build on each other:
- Data views — A saved query that defines a dataset. You choose a subject (the primary record type), select fields, and configure filters. Data views are the foundation that powers visualizations.
- Visualizations — A chart, table, or number widget that displays data from a data view. Visualizations live on dashboards.
- Dashboards — A collection of visualizations (and optional notes) organized into a easy-to-consume view. Dashboards can have global filters that apply across all visualizations on the page.
The typical flow is: create a data view → add that data view to a dashboard (by using it to power a visualization) → configure the visualization → open access to the dashboard.
Learn more about analytics key objects, how these objects work together, and other terminology here.
Choose your starting point
When beginning, you can create from scratch or start from a template.
If you start from a template, we highly recommend starting with a dashboard template. Dashboard templates give you a complete starting point: a dashboard with visualizations already configured, plus the data views that power those visualizations. You can start with a data view template instead, but you'll still need to create a dashboard and configure its visualizations manually.
Create a data view
Let's go through building a data view from scratch.
From Greenhouse Recruiting, navigate to Analytics in the main navigation.
Click Create > Data view.
Select a subject
First, select a subject. The subject defines the primary record type your data view is built around—every field and filter you add will relate back to this subject.
For a full glossary of subjects and their fields, see the analytics glossary.
Add fields
After selecting a subject, the field selector opens automatically. Here you can browse, search, and add fields to your data view.
Fields are organized into two types:
- Dimensions – Categorical fields like job name, department, stage, or date. Use these to group, filter, and break down your data.
- Measures – Numeric aggregations like count, sum, or average. Use these to calculate totals and summaries.
Fields are grouped by subject and related data (for example, job fields grouped under Application). A Favorites section at the top shows any fields you've starred for quick access. You can search across all fields by name, and the drawer shows a live count of matching results.
Tip: Need to get back to the field selector after closing it? Click the + Add fields button at any time to reopen the field selector side panel.
Note: All fields and filters are scoped to the selected subject. If you change the subject after configuring fields or filters, you'll see a confirmation prompt: "Changing the subject resets this data view and removes any configured fields, filters, and results." Confirming will clear your entire configuration, so make sure you're happy with your subject choice before building out your view.
Configure filters
Filters determine which records appear in your data view. Use + Add filter to add a condition to the current group, or + Add filter group to create a nested group with its own AND/OR logic. By default, all conditions are combined with AND—every condition must be true. Toggle any group to OR (by clicking the AND/OR button) to return records matching any condition. Nest groups within groups to build more complex logic.
Example: To see applications from the last 90 days across two departments:
Application created date is in the last 90 days AND (Department is Product Design OR Department is Product Management)
Available filter operators depend on the field type:
| Field type | Available operators |
| Text fields | is, is not, contains, does not contain, starts with, does not start with, ends with, does not end with |
| Numeric fields | equals (=), does not equal (≠), greater than (>), greater than or equal (≥), less than (<), less than or equal (≤) |
| Date/time fields | in date range, not in date range, before, on or before, after, on or after, equals, does not equal. Date range filters support both preset options (such as last 7 days, last 30 days, year to date) and custom date ranges. |
| All field types | is set, is not set (no value required) |
Filters with missing or invalid values are highlighted in red and will block you from running or saving the data view. Errors clear automatically once all filters are valid.
Run and save
Click Run query to execute the query and see your results in the Results table below. Make sure to run the query after making any changes to fields or filters—the results won't update automatically.
Once you've run your query a final time and are happy with your data view, click Save at the top of the page.
Give your data view a name, then click Save data view again to confirm.
Add a visualization to a dashboard
Once your data view is saved, you can go back and edit it at any time by clicking Edit data view, or you can add it to a dashboard as a visualization by clicking Add to dashboard.
The fastest way from here is to click Add to dashboard.
You'll see a list of your existing dashboards, showing each dashboard's name, owner, number of visualizations, and when it was last updated. From here, hover over a dashboard and click Edit dashboard to add a visualization to it, or click + New dashboard to create a new one.
You'll be taken to the dashboard with your new visualization added and ready to configure.
From here, you can use the same data view to create as many visualizations as you need—each one can display the data in a completely different way.
Configure a visualization
Each visualization has a configuration panel with options that vary by type. Choose from:
- Chart — A graphical representation of your data. Types available include: vertical bar, line, area, scatter, pie, histogram.
- Table — A flat data table with sorting, filtering, grouping, and column visibility controls.
- Single number — Displays a single aggregated value (count, sum, average, min, max, etc.).
- Note — A text block with Markdown formatting. Doesn't require a data view; useful for context or section headers.
Chart configuration options
When configuring a chart, you'll set the following:
- X-axis — The field to plot along the horizontal axis. For date fields, set the time unit: year, quarter, month, week, day of month, day of week, or combinations like year & month.
- Y-axis — One or more fields to plot along the vertical axis. With a single field, set the aggregation: count, distinct count, sum, mean, median, min, or max.
- Color by — (Optional) A dimension field to color-code the chart by.
- Show grid — Toggle grid lines on or off.
- Show text labels — Display data values directly on chart bars. Bar charts only.
- Normalized — Stack bars or areas as percentages totaling 100% instead of absolute values. Bar and area charts only.
You can also hover over the ⓘ icon on any visualization to see which data view is powering it, and click the name of the data view to open it in a new tab or window.
Example: Applications by department over time (normalized)
This example walks through configuring a normalized stacked bar chart, which is useful for seeing how application volume is distributed across departments month over month, independent of total volume.
- Under Choose visualization, select Chart, then the vertical bar subtype.
- Set X-axis to Application created at, with Time unit set to Month.
- Set Y-axis to Applications with Aggregation set to Count.
- Under More options, set Color by to Department name.
- Check Normalized to convert the Y-axis from raw counts to percentages, stacking each bar to 100%.
Once your visualizations are configured, click Save.
Open access to your dashboard
By default, a new dashboard is accessible only to you. To give others access to your dashboard, click the ellipsis menu (…) next to the Save button and choose Manage access.
From there, you can restrict access to specific users or open it up to your organization. Learn more about managing access to a resource here.
Click Save to confirm your changes.
Dashboard layout and controls
Once your visualizations are configured and saved, your dashboard is your home base for viewing, filtering, and opening access to your team. This section walks you through the different areas of the dashboard interface—where things live, what each control does, and how to use them.
Note: If you're just viewing a dashboard and don't see the controls below, switch to edit mode by clicking Edit dashboard at the top of the dashboard.
Dashboard title
Click the title to rename your dashboard inline.
Global filters
Click the filter icon to open the global filters panel. Global filters apply to all compatible visualizations on the dashboard and currently support timeframe filters with preset and custom date range options.
Note: Right now, the only global filter options available are for dates. More functionality will be coming in further releases.
Add
Click Add to insert content onto the dashboard:
- Add AI visualization — Describe what you want to see and let AI build a visualization for you.
- Add manual visualization — Select a data view and configure a visualization yourself.
- Add note — Insert a text block with Markdown formatting. Notes don't require a data view and are useful for adding context or section headers.
Save
Saves all pending changes. An unsaved changes counter appears when there are changes to save. You can also discard changes here, if needed.
More options (…)
Click the ellipsis menu for additional dashboard actions:
- Duplicate dashboard — Creates a copy titled "[original name] - copy."
- Export as PNG — Downloads the entire dashboard as an image.
- Manage access — Opens user and organization access settings. Learn more about managing access to a resource here.
- Delete — Permanently deletes the dashboard.