---
title: "Managing Custom Filters"
url: "https://gleanly.productfruits.help/en/article/managing-custom-filters"
language: "en"
last_updated: "2023-10-10T09:50:01.450Z"
---

# Managing Custom Filters

![](https://cdn-assets.productfruits.com/1cb73618-e4c8-4d0c-b615-22bfb497af74)

Custom filters are a useful way of defining, coding, and allowing cards to be filtered. They give a set list of labels that help encourage people to code/tag their research.

Admins can manage this by clicking the menu top right and choosing 'Custom filters'.

You can apply different custom filters to:

**Experiments**

These would usually be filters that help people find an experiment. For example:

-   Team - Who did the research?
-   Client - Who was the research for?
-   Opportunity - Was the research as part of a certain theme or metric?
-   Product/service - Was the research studying a specific part of your organisation's offering?
-   Platform - Were they testing a specific delivery method such as app or website?

Note - *For non-finite markers such as project numbers or internal references, we would recommend using normal tags.*

  
**Facts**

These tend to be more contextual and help the understanding of the participant or source the fact came from. For example:

-   Tool - What tool was used to generate the facts (IE Power BI, Survey Monkey, Conversion.com)?
-   Sentiment - What was the emotional response if testing participants?
-   Personas - Was the participant part of a specific persona or demographic?
-   Platform - Which browser or app was the participant testing. Perhaps it was a prototype rather than a live product?

**Insights**

Insight filters often are theme-focused. For example:

-   Opportunity - Does the insight feed into part of a certain theme or metric?
-   Type - Is the insight a principle that applies to everyone, a guidence for some people, or tactical so very specific to the specific research focus?
-   Priority - Evidence score can tell us how much confidence we have but not how important in insight is. A priority score can help with that.

  
**Recommendations**

These filters mostly help us prioritise and understand the status of the recommendations. For example:

-   Status - Is the recommendation unactioned, approved, completed or rejected? Perhaps it's reusable?
-   Action - What is the next step? Such as: Change, feature, or perhaps more evidence is needed?
-   Priority - How important is this recommendation? Usually as a score of 1-5.
-   Ease - How easy is this recommendation to achieve? Usually as a score of 1-5
-   Team - Which team is expected to pick this up?

The order of the filters and labels within them can be changed with the up/down arrows. The order will affect what order they are shown below the search bars.

**Note:** Only admins have the right to manage custom filters