Filters allow you to refine the data sets visualized on dashboards so you can zero in on specific insights. Proper use of filters is key to getting the most out of your recruitment data. This article covers the operation of dashboard filters in Visual Insights. Readers of this article will learn about:
As you are reading, refer to our LeverTRM Glossary for definitions of the key terms and concepts used in this article.
Filters are arranged horizontally along the top of each dashboard in Visual Insights. Clicking into a filter block will reveal the dimension fields which you can use to configure the filter. The variables available to filter by will vary depending on the dashboard being viewed. A full breakdown of filter variables by dashboard is provided below.
In order to apply filters, you must click the reload button (⟳) to the upper-right of the filter bar. To hide the filter bar, click the filter icon next to the reload button. To clear applied filters, click the dashboard actions button (⠇) and select the Reset filters option. Some dashboards have filters pre-applied upon entry.
The reload button will appear blue when there are new filter inputs that have yet to be applied to the dashboard.
Applied filters will persist as you navigate between dashboards, as long as the applied filter field exists on the dashboard to which you are navigating. Any filters that are applied at the time that a dashboard is bookmarked will be reflected on the bookmarked view of the dashboard when it is revisited in the future. Any filters applied at the time that a dashboard is shared will be reflected on the image of the dashboard that is delivered to recipients.
There are four types of filters you will find on Visual Insights dashboards:
- Multi-value filters
- Single-value filters
- Yes/No filters
- Selector filters
Multi-value filters are the most common filter type you will find in Visual Insights. Multi-value filters allow you to define the parameters of a data set using multiple inputs.
Multi-value filters consist of two elements:
- The operator expresses the relationship between the attribute and the data set. Examples of operators include 'is in,' 'contains,' 'starts with,' and 'matches.'
- The attribute is the variable that will define the parameters of the data set. Examples of attributes include date ranges, locations, and names of users.
The operators and attributes you can choose from will vary depending on the specific filter you are applying. Some filters only contain an attribute field. The pairing of an operator with one or more attributes is known as a dimension.
Adding attributes and operators
Attributes and operators can be added to a filter by clicking the corresponding field and selecting the desired attribute or operator from the menu that appears. When adding an attribute, you can also start typing the name of the attribute you are looking for in the field to refine the options that appear in the menu. It may take a few seconds for the dropdown arrow to appear in the attribute field after expanding a filter block.
Multiple operator and attribute pairings can be used in conjunction as part of the same dimension and/or filter.
- Multiple attributes
- If an attribute field contains more than one attribute, those attributes will be connected using 'OR' logic, meaning the events, measurements, or objects in the data set for which at least one attribute is true will be included/excluded by the filter.
- Multiple dimensions
- For filters that use operators, additional dimensions can be added to a filter by clicking the plus sign (+) to the right of the attribute field. Fields will appear in which you must select an operator and attribute(s) for the additional dimension. The dimensions will be connected using 'OR' logic if the additional operator is positive ('is,' 'starts with,' or 'ends with'), meaning that at least one dimension (i.e. one operator + attribute pairing) will need to be true for events, measurements, or objects in the data set to be included/excluded by the filter. The dimensions will be connected using 'AND' logic if the additional operator is negative (i.e. 'is not,' 'doesn't start with,' or 'doesn't end with'), meaning all dimensions with negative operators (plus at least one dimension with a positive operator if applicable) will need to be true for the events, measurements, or objects in the data set to be included/excluded by the filter.
- This filter contains three dimensions, two with positive operators and one with a negative operator.
Single-value filters only allow for one input, selected from a drop-down menu. Single-value filters are inclusive by default, meaning once the filter is applied the data sets used by the charts on the dashboard will be updated to reflect only the events, measurements, or objects associated with the input.
Yes/No filters allow you to filter a data set based on whether the events, measurements, or objects that compose it are true or false in relation to the variable. Click the 'Y' and 'N' buttons on a Yes/No filter to change the input.
Selector filters allow you to change how numeric values are visualized on the table(s) contained within the dashboard.
Multi-value filters by dashboard
Below is table showing which multi-value filters are available on each dashboard.
|Recruiter Operations*||Overview||Requisitions||Pipeline||Postings||Sources||Offers||Interviews||Nurture||Compliance||Equal Employment Opportunity||Diversity||Candidate Experience Survey||Talent Acquisition Benchmarks|
|Requisition hiring manager||✓|
*This table only reflects filters available on the Current operations page of the Recruiter Operations dashboard.
Best practices for using filters
When using filters on Visual Insights dashboards, here are some best practices to keep in mind.
- Click the reload button to apply filters
- Although filter blocks will turn blue when you have input an attribute, the parameter will not be reflected on the dashboard charts until you have clicked the reload button (⟳) to the upper-right of the filter bar. If you have input values for filters that have not yet been applied, the reload button will turn blue.
- Allow a few seconds for charts to refresh after applying filters
- Depending on the size of the data sets being visualized on the dashboard, it can take up to a few seconds for the visualizations on the charts to refresh once you apply filters. The charts will show a buffering icon while new filters are being applied.
- Ensure that you have inputs in all required filters
- The Diversity dashboard requires that you select a survey question in the filter bar before the charts on the dashboard will load.
- Use relative date range filters for dashboards you check on a recurring basis
- Relative date ranges are dynamic, and are based off of the date that a user is viewing the dashboard (compared to absolute dates, which are useful for looking at data from a fixed range time frame). When applying the date range filter using the operator 'is before' or 'is on or after,' you can set the date in the attribute field to be absolute or relative. The operators 'is in the last,' 'is this,' 'is next,' and 'is previous' are relative by default. Apply relative date range filters to dashboards boards that you revisit regularly to keep an eye on rolling metrics.
- Use tool tips to check which filters affect the data set(s) in a chart
- If a chart is necessarily affected by any other filters aside from the date range, they will be listed in the tool tip for that chart. Hover over the ⓘ icon next to each chart title and check the description under the 'Other filters' heading.