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Add comparing trait types
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src/_includes/content/trait-types.md

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## Comparing trait types
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View the table below to better understand how Segment collects custom, computed, and SQL traits.
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You can use the Profile explorer (**Unify > Profile explorer**) to view traits attached to a profile.
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| **Trait type** | **Description** |
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|---------------|----------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [Custom traits](/docs/unify/traits/custom-traits/) | Traits created from source events you pass into Segment. From your sources, send custom traits as pieces of information that you know about a user in an Identify call. |
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| [Computed traits](/docs/unify/traits/computed-traits/) | Traits collected from computations off of event and event property data from your sources. Create user or account-level calculations like `most_viewed_page` or `total_num_orders` for a customer. Learn more by viewing [types of computed traits](/docs/unify/traits/computed-traits/#types-of-computed-traits). |
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| [SQL traits](/docs/unify/traits/sql-traits/) | Traits created by running SQL queries on data in your warehouse. SQL traits are a type of computed trait. SQL traits help you import traits from your data warehouse back into Segment to build audiences or enhance data that you send to other destinations. |
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<!--
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| [Predictive traits](/docs/unify/traits/predictions/using-predictions/) | Segment creates Predictions as Computed Traits, with scores saved to user profiles as a percentage cohort. | -->

src/unify/Traits/computed-traits.md

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Computed Traits allow you to quickly create user or account-level calculations that Segment keeps up-to-date over time. These can be computations like the `total_num_orders` a customer has completed, the `lifetime_revenue` of a customer, the `most_frequent_user` to determine which user is most active in an account, or the `unique_visitors_count` to assess how many visitors from a single domain. These computations are based on your events and event properties that you are sending through Segment on the [page](/docs/connections/spec/page/) and [track](/docs/connections/spec/track) calls.
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{% include content/trait-types.md %}
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## Types of Computed Traits
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Segment currently supports the following types of computed traits:

src/unify/Traits/custom-traits.md

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Custom traits are user or account traits collected from the Identify calls you send to Segment. For example, these could be demographics like `age` or `gender`, account-specific like `plan`, or even things like whether a user has seen a particular A/B test variation. From your sources, send custom traits as pieces of information that you know about a user in an Identify call.
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As opposed to [computed traits](/docs/unify/traits/computed-traits/) which are computed from your source data, or [SQL Traits](/docs/unify/traits/sql-traits/) which are computed from warehouse data, custom traits are created from source events you pass into Segment.
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As opposed to [computed traits](/docs/unify/traits/computed-traits/) which are computed from your source data, or [SQL Traits](/docs/unify/traits/sql-traits/) which are computed from warehouse data, custom traits are created from source events you pass into Segment.
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{% include content/trait-types.md %}
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## Using custom traits
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When an audience that previously generated Identify events is deleted, the data for the audience key is still attached to profiles that entered the audience and becomes visible in Segment as a custom trait.
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Use the Profile explorer (**Unify > Profile explorer**) to view custom traits attached to a profile.
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## Reserved custom traits

src/unify/Traits/sql-traits.md

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where t.status in ('pending','open','hold','new')
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```
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{% include content/trait-types.md %}
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## Configure SQL Traits
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