> For the complete documentation index, see [llms.txt](https://docs.mediarithmics.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mediarithmics.io/collaboration/prepare-your-environment/manage-your-clean-room-templates.md).
# Manage your clean room templates
Configure your organisation's reusable Clean Room Template: authorized presets, reference datasets, matching keys, and how edits and auto-matching behave.
## Your goal
Turn your organisation's data-collaboration standards - which activation feeds are allowed, which datasets are shared by default, which matching keys and identifier freshness apply - into a reusable [Clean Room Template](/collaboration/plan-and-integrate/setup-clean-rooms/clean-rooms.md#what-a-clean-room-template-is), instead of reconfiguring them for every new partner.
## Expected outcome
A Clean Room Template that every new Clean Room for a given Collaborative App can reference, so opening a partnership takes a few clicks instead of hours of manual configuration.
## Why templates instead of one-off configuration
Without a Clean Room Template, every new partnership means reconfiguring the same things from scratch: which segments to share, which matching keys to use, which activation feeds to allow, how fresh identifiers must be. Two problems follow:
* **Governance risk** - someone might share the wrong dataset, allow activation to the wrong destination, or use a stale identifier.
* **Setup cost** - every new partner takes hours of manual configuration.
A Clean Room Template solves both by turning your standards into a reusable object, owned and maintained by an admin organisation.
## What a Clean Room Template declares
| Property | Description | Mandatory |
| ------------------------ | --------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------- |
| **Collaborative App** | The parent Collaborative App this Clean Room Template extends. Inherits all of its boundaries (dataset types, actions, outputs). | Yes |
| **Authorized presets** | The restrictive list of activation feed presets that partners can use in Clean Rooms based on this Clean Room Template. | Yes (when Activation is required) |
| **Reference datasets** | The datasets (e.g. Segment, Segment catalog, …) automatically shared into every Clean Room created from this Clean Room Template. | Optional |
| **Matching keys** | The identifier types used for auto-matching when a partner shares a new dataset in the Clean Room. | Mandatory if at least one reference dataset is provided |
| **Identifier freshness** | Maximum age of identifiers accepted for auto-matching. | Mandatory if a matching key requires freshness |
| **Refresh frequency** | How often auto-matchings are recomputed. Same values as manual dataset matching. | Optional |
{% hint style="warning" %}
Contact your Account manager to set up a new Clean Room Template - or a new Clean Room - in your environment.
{% endhint %}
## Auto-matching
When a Clean Room Template declares one or more reference datasets, the platform automatically matches every new dataset a partner shares in the Clean Room against those references. No manual configuration is needed.
**Example:** if your Clean Room Template declares both a Segment and a Segment Catalog as reference datasets, the platform automatically creates two matchings whenever a partner shares a Segment: one returns the overlap with the reference Segment, the other returns the overlap with each Segment of the reference Catalog.
Auto-matching uses the parameters declared on the Clean Room Template - matching keys, identifier freshness, and refresh frequency. See [Analyze cross-partner behavior](/collaboration/collaborate-with-a-partner/analyze-cross-partner-behavior.md) for what these parameters mean during a match.
**When auto-matching does not run:**
* When a reference dataset is added to an *existing* Clean Room Template - partner datasets already shared in Clean Rooms based on that template are not retroactively matched. Only *future* partner datasets trigger auto-matching against the new reference.
* When the partner's shared dataset type is not compatible with the reference dataset type.
## Editing a Clean Room Template
Clean Room Templates are living objects: you will want to add feeds, refresh reference datasets, or update matching keys as your data-collaboration practices evolve. Some edits propagate to existing Clean Rooms; others only affect new ones.
{% tabs %}
{% tab title="Authorized presets" %}
* **Adding a preset** - immediately available for new activations in every Clean Room using this template.
* **Removing a preset** - the platform warns you before validation. Existing activations keep working with the removed preset; only *new* activations are restricted.
{% endtab %}
{% tab title="Reference datasets" %}
**Adding one:**
* The dataset is automatically shared in every existing Clean Room based on this template.
* No auto-matching is run retroactively against datasets the partner already shared - only *future* partner datasets are auto-matched with the new reference.
* Any new Clean Room created afterwards includes it in its initial share.
**Removing one:**
* Nothing changes in existing Clean Rooms - the dataset stays shared, existing matchings remain active.
* Any *new* Clean Room based on this template no longer receives it.
{% endtab %}
{% tab title="Matching keys, freshness, refresh frequency" %}
* No change to existing dataset matchings.
* Any *new* auto-matching triggered afterwards uses the updated parameters.
{% endtab %}
{% endtabs %}
## Related pages
Clean Rooms
What a Clean Room Template is, and the layers it sits between.
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