> For the complete documentation index, see [llms.txt](https://support.sayprimer.com/primer/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://support.sayprimer.com/primer/audiences/audience-filters.md).

# Audience filters

The filter sources you build an audience from — Primer data, events, CRM and datasets — with sample filters.

Filters define who's in an audience. They're grouped by **source** — where the data comes from — and you can combine filters from any source. Each filter matches with operators like **is** / **is not**; numeric filters use ranges.

## Primer data

Primer's own person and company data. This is the default source, available to everyone.

* **People** — Job Title, Seniority, Department, Person Location, Skills, Degrees, Majors.
* **Companies** — Industry, Headcount, Annual Revenue, Company Location, Domain, Keywords, Technology, NAICS Code, Founded Year.

Department and Industry are picked from fixed, Primer-defined lists so audiences stay comparable; the audience builder shows every available value as you filter. Keywords and Technology accept your own values.

## Events

The people your [website pixel](/primer/connections/website-tracking/installing-the-pixel.md) has identified — for example everyone who visited a page or arrived from a campaign. The pixel must be [Connected](/primer/connections/website-tracking/pixel-connection-status.md); these filters have nothing to match against until it is, so they only appear once it's connected.

* **Pages visited** — filter by the page someone viewed.
* **UTM parameters** — source, medium, campaign, term and content, matching the **first**, **last** or **any** touch.
* **Form fills** — whether someone submitted a form, and which one.
* **Engagement** — number of visits, session time, referrer, device and browser, intent level and traffic type.
* **Audience membership** — whether someone belongs to another of your audiences, most often to [exclude one audience from another](/primer/audiences/exclusion-audiences.md).

## CRM

Custom fields from a connected CRM, so you can filter on your own data — Salesforce (Lead, Contact, Account, Opportunity, Campaign) and HubSpot (Contact, Company, Deal, Form). These appear once the [CRM is connected](/primer/connections/integrations/connecting-a-crm.md).

## Datasets (CSV Files)

Filter against lists you've [imported as a CSV](/primer/connections/datasets/importing-a-csv.md).

## Why some filters are slower to process

Most filters resolve against pre-indexed (normalized) values, so estimates update quickly. A **CRM filter** on a custom field that hasn't been normalized is the exception: Primer has to scan the raw values instead of a prepared index, which makes the [size and match-rate estimates](/primer/audiences/estimates.md) take longer to compute. When your audience uses one, the builder shows a turtle note — *"Unnormalized filters can cause slower estimates."*

This is only a speed note, not an error: the filter still matches correctly and the audience still builds and syncs. If estimates feel slow, it's usually one of these CRM filters at work; removing it makes estimates snappy again, or you can simply wait for it to finish.


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