Dashboard Filters

Follow

Overview

Filters allow you to refine the data sets visualized on dashboards to 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 the Analytics platform. For guidance on filtering for specific timeframes, refer to our help article on using the analytics Date Range Filter.

Audience

All users

Using Filters

Filters are arranged horizontally along the top of each Analytics dashboard. Clicking a filter block will reveal the dimension fields that you can use to configure the filter. The variables available to filter by will vary depending on the dashboard being viewed.

dashbaord filters.png

To apply filters, you must click reload (⟳).

reload.png

To hide the filter bar, click filter.

filter.png

To clear applied filters, click the dashboard menu ⠇, then select Reset filters. Some dashboards have filters pre-applied upon entry.

reset filters.png

The reload icon will display blue when new filter inputs 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 you are navigating. Any filters applied when 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.

Multi-value filters

Multi-value filters are the most common filter type you will find in Analytics. Multi-value filters allow you to define the parameters of a data set using multiple inputs. Multi-value filters consist of two elements:

  •  Operator - The operator expresses the relationship between the attribute and the data set. Examples of operators include is in, contains, starts with, and matches.
  • Attribute - The attribute is the variable that will define the data set's parameters. Examples of attributes include date ranges, locations, and names of users.

multi value filters.png

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 in the menu. After expanding a filter block, it may take a few seconds for the dropdown arrow to display in the attribute field.

selecting filters.png

Multiple attributes and filter logic

Multiple operator and attribute pairings can be part of the same dimension and/or filter.

Suppose an attribute field contains more than one attribute. In that case, those attributes will be connected using OR logic, meaning the events, measurements, or objects in the data set for which at least one true attribute will be included/excluded by the filter.

For example, in the image below, both hired and not interviewed are the attributes, so the filter logic would be as follows: is hired OR not interviewed. This logic is also demonstrated in the Disposition field.

filter logic.png

Multiple dimensions

For filters that use operators, additional dimensions can be added by clicking the + icon.

multi dimension.png

Fields will display where 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.

or logic.png

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). This means that 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.

and logic.png

Best practices

Here are some best practices to remember when using filters on analytics dashboards.

  • Click reload 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 reload (⟳) in 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.

reload.png

  • 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 used.

  • Use relative date range filters for dashboards you check regularly.

Relative date ranges are dynamic and are based on the date a user is viewing the dashboard (compared to absolute dates, which help look 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 dashboard boards that you revisit regularly to monitor rolling metrics.

relative date range.png

  • Use tooltips to check which filters affect a chart's data set(s).

If a chart is necessarily affected by any other filters aside from the date range, they will be listed in the tooltip for that chart. Hover over the ⓘ next to each chart title and check the description under the filters heading.

NOTE: Tooltips are not everywhere within Analytics, but when they appear, they can help you determine what filters apply to the different tiles.

tool tips.png

Was this article helpful?
0 out of 0 found this helpful