What characterises a background variable is that it is specified per user in the organisational structure, often included via an import file. There are no limitations to how many or what types of variables can be included, but prioritise organisational information such as job role, country, city, office, etc.
📌 Purpose and benefits of background information
Note! Using background variables requires that the organisation possesses structured user information and can include it in an import file.
Importing Users and Background Variables
To import background variables, the data must be structured in separate columns in an Excel file, along with other user information – such as email address, name, and organisational affiliation.
📥 Learn more and download an import file example here.
Variables can also be handled manually per user, but this is time-consuming and best suited for smaller organizations or simpler updates.
Which background variables are available to the organisation are defined and configured initially in collaboration with Brilliant.
To add additional background variables, please contact Customer Care.
Bad Data In – Bad Data Out
To enable analysis and maximise the value of background information, it is important that the import file is of high quality. Incomplete or incorrect data significantly affects what is possible to report and analyse – and errors cannot be corrected retroactively (only before future surveys).
The example below shows a column for the background variable “Country” where “Sweden” has been entered in multiple ways:
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Sweden
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sweden
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Sweden.
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Swedne
Here we find four variations: uppercase/lowercase, punctuation, and a spelling error. The issue is not which one is “correct,” but rather that they must be consistent and form a single variable. This situation creates four different variables instead of one for Sweden, leading to confusion and limitations in analysis.
Some background information is best collected via background questions.
To ensure updated and relevant data for variables that change over time – such as age or length of employment – these are better included as survey questions. The same applies to gender, where respondents should be given the opportunity to self-identify rather than being categorised through a variable.
Standard anonymity rules apply to all background information, regardless of whether the data is collected via background variables or background questions.