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Add Compute Times Note #3428
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src/engage/audiences/index.md

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> info ""
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> When you connect a new Destination to an existing Audience, Personas will backfill historical data for that Audience to the new Destination.
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## Understanding compute times
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Because a number of factors (like system load, backfills, or user bases) determine the complexity of an Audience, some compute times take longer than others.
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As a result, **Segment recommends waiting at least 24 hours for an Audience to finish computing** before you resume working with the Audience.
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## Real-time compute compared to batch
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Real-time Compute allows you to update traits and Audiences as Segment receives new events. Real-time Compute unlocks exciting use cases:

src/engage/profiles/computed-traits.md

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For account-level computed traits, you have the option to send either a [group](/docs/connections/spec/group/) call and/or [identify](/docs/connections/spec/identify/) call. Group calls will send one event per account, whereas identify calls will send an identify call for each user in the account. This means that even if a user hasn't performed an event, Segment will still set the account-level computed trait on that user. Because most marketing tools are still based at the user level, it is often important to map this account-level trait onto each user within an account. See [Account-level Audiences](/docs/personas/audiences/account-audiences) for more information.
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## Understanding compute times
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Because a number of factors (like system load, backfills, or user bases) determine the complexity of a Computed Trait, some compute times take longer than others.
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As a result, **Segment recommends waiting at least 24 hours for a Trait to finish computing** before you resume working with the Trait.
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## Editing Realtime Traits
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Personas supports the editing of realtime Traits, which allows you to make nuanced changes to existing Traits in situations where cloning or building from scratch may not suit your use case.

src/personas/audiences/index.md

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Audiences let you group users or accounts based on event behavior and traits that Segment tracks.
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You can build Audiences from core **tracking events**, **traits**, and **computed traits**. You can then sync Audiences to hundreds of [Destinations](/docs/connections/destinations/) or access them with the [Profile API](/docs/personas/profile-api).
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You can build Audiences from core **tracking events**, **traits**, and [**computed traits**](/docs/personas/computed-traits/). You can then sync Audiences to hundreds of [Destinations](/docs/connections/destinations/) or access them with the [Profile API](/docs/personas/profile-api).
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## Building an Audience
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> info ""
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> When you connect a new Destination to an existing Audience, Personas will backfill historical data for that Audience to the new Destination.
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## Understanding compute times
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Because a number of factors (like system load, backfills, or user bases) determine the complexity of an Audience, some compute times take longer than others.
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As a result, **Segment recommends waiting at least 24 hours for an Audience to finish computing** before you resume working with the Audience.
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## Real-time compute compared to batch
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Real-time Compute allows you to update traits and Audiences as Segment receives new events. Real-time Compute unlocks exciting use cases:

src/personas/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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Computed Traits allow you to quickly create user or account-level calculations that Segment keeps up-to-date over time.
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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 send through Segment on the [Page](/docs/connections/spec/page/) and [Track](/docs/connections/spec/track) calls.
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## Types of Computed Traits
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For account-level computed traits, you have the option to send either a [group](/docs/connections/spec/group/) call and/or [identify](/docs/connections/spec/identify/) call. Group calls will send one event per account, whereas identify calls will send an identify call for each user in the account. This means that even if a user hasn't performed an event, Segment will still set the account-level computed trait on that user. Because most marketing tools are still based at the user level, it is often important to map this account-level trait onto each user within an account. See [Account-level Audiences](/docs/personas/audiences/account-audiences) for more information.
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## Understanding compute times
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Because a number of factors (like system load, backfills, or user bases) determine the complexity of a Computed Trait, some compute times take longer than others.
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As a result, **Segment recommends waiting at least 24 hours for a Trait to finish computing** before you resume working with the Trait.
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## Editing Realtime Traits
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Personas supports the editing of realtime Traits, which allows you to make nuanced changes to existing Traits in situations where cloning or building from scratch may not suit your use case.

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