Custom filters are where dashboard customization usually starts.

Custom filters for SaaS users let customers narrow dashboard data by fields such as status, owner, date range, plan, segment, health score, or priority. The safe pattern is to define which fields are filterable, which operators are allowed, which fields stay hidden, and which saved filters can become personal or team views.

ShapeKit is built for the middle ground: your product defines the safe boundary, and users shape their own view inside it.

Test custom filters with ShapeKit See user generated views for SaaS

Who this is for

Good fit:

• SaaS teams with repeated filter-request tickets
• dashboards where users need saved filtered views
• teams defining which fields and operators are safe
• builders who want filters connected to shaped views

Not a fit:

• filters that would bypass permissions
• fields that cannot be safely exposed or explained
• one-off analytics projects where analysts own the dashboard layer
• teams without a live dashboard to test

What a custom filter should do

A custom filter should let users narrow safe product data without changing what the product allows.

It should answer questions about status, owner, priority, plan, date range, or segment. It should not answer whether a user can see private data or change workflow state.

Start with filterable fields

Before users create filters, list the fields that are safe to filter and mark every field as filterable, visible but not filterable, or hidden.

• status, owner, plan, and segment
• date range, priority, type, and region
• health score, activity state, and renewal window

Define operators per field

Do not make every operator available everywhere. A date field needs date operators. A status field needs status operators. A sensitive text field may need no operators at all.

• status: is, is not
• date: before, after, between, in next
• number: greater than, less than, between
• text: contains, does not contain

Combine filters with views

A filter is often just one part of the request. The user usually wants a full view: apply this filter, show these fields, group by this dimension, sort by this date, and save it for later.

ShapeKit maps the request to allowed fields and operators. If it fits, the filtered view is created. If it crosses the boundary, the request is rejected clearly.

Test custom filters on one real dashboard.

Bring a dashboard where filter requests keep hitting engineering, support, or client services. The first test should prove which filter requests can move into bounded self-service.

Good test workflow:

• one live SaaS dashboard, admin panel, table, or reporting view
• repeated requests around columns, filters, grouping, sorting, or saved views
• a clear first pass at safe fields and locked fields
• one user group that can test shaped views within 14 days

This is not a generic demo request. Tell us about the dashboard where requests keep hitting engineering, support, or client services.

Test custom filters with ShapeKit See how shaping works

Frequently asked questions

What are custom filters for SaaS users?

They are user-created filters over safe product data, usually by status, owner, plan, date range, priority, segment, or health score.

How do custom filters stay safe?

Developers define filterable fields, allowed operators, hidden fields, roles, scopes, and locked actions before users can create saved filters.

Should filters be separate from saved views?

They can be, but filters usually become more useful when they are saved as part of a full view with columns, sorting, grouping, and scope.