Offline Custom Audiences

Updated: Jun 16, 2026

Group people who visited your store, made calls to your customer service, or took action offline and target them with Facebook ads.

For example, to target people who spent more than USD 1,000 in the past 90 days:

curl \
-F 'name=90d High Value' \
-F 'rule={"inclusions":{"operator":"or","rules":[{"retention_seconds":7776000,"event_sources":[{"id":"<OFFLINE_EVENT_SET_ID>","type":"offline_events"}],"filter":{"operator":"and","filters":[{"operator":"=","field":"event","value":"Purchase"}]},"aggregation":{"type":"sum","field":"value","operator":">","value":"1000"}​}]}​}' \
-F 'access_token=<ACCESS_TOKEN>' \
https://graph.facebook.com/<VERSION>/act_<AD_ACCOUNT_ID>/customaudiences"

You build Custom Audiences from the conversion events you upload to an offline event set. See Offline Conversions API documentation.

Since September 2018, Meta does not support subtype for custom audiences for websites, apps, engagement custom audiences, and audiences from offline conversion data. The one exception is that subtype is still supported for engagement custom audiences for video.

Create an audience

To create a custom audience from your offline event set, the account needs to have already accepted the Terms of Service for Custom Audiences, in Ads Manager⁠:

curl \
  -F 'name=My New Offline Event Set' \
  -F 'rule={"inclusions":{"operator":"or","rules":[{"retention_seconds":2592000,"event_sources":[{"id":"<OFFLINE_EVENT_SET_ID>","type":"offline_events"}],"filter":{"operator":"and","filters":[{"operator":"=","field":"event","value":"Purchase"},{"operator":">","field":"value","value":"50+Sheet1!A2+Sheet1!A2+Sheet1!A2+"}]}​}]}​}'
  -F 'access_token=<ACCESS_TOKEN>' \
  https://graph.facebook.com/<VERSION>/act_<AD_ACCOUNT_ID>/customaudiences

These parameters are most relevant for custom audiences from your offline event sets:

Name	Description
name type: string	Required. The name for the audience.
rule type: string	Required. Audience rules to be applied on the referrer URL.
description type: string	Optional. Description of your custom audience.

Audience rules

Rules determine whether an Accounts Center account should be added to this audience. These rules apply to Offline Events sent through the Offline Conversions API or uploaded manually with Offline Event Manager. Rules are applied on specific events or the custom_data field. See Audience Rules for complete information. See also:

• Audience Rules Syntax
• Rule Set Syntax
• Inclusion/Exclusion Rule Syntax: Under event_source, set id to your Pixel ID and type to pixel.
• Filters
• Filter Rules: Under field, use "event" if the filter is to specify an event. Parameters that match events sent by pixel (for example, 'ViewContent', 'Purchase').
• Aggregate Functions

Example offline custom audience rules

//Match all referring `favorite_food` containing the string `'pizza'` in the last 30 days:  
  
{  
    "inclusions": {  
        "operator": "or",  
        "rules": [  
            {  
                "event_sources": [  
                    {  
                        "type": "offline_events",  
                        "id": "<OFFLINE_EVENT_SET_ID>",  
                    }  
                ],  
                "retention_seconds": 2592000,  
                "filter": {  
                    "operator": "and",  
                    "filters": [  
                        {  
                            "field": "custom_data.favorite_food",  
                            "operator": "i_contains",  
                            "value": "pizza"  
                        }  
                    ]  
                },  
            }  
        ]  
    }  
}

Match Purchase events where cost is greater than or equal to USD 100 in the last 30 days. Use this rule for the following event:

{  
    "inclusions": {  
        "operator": "or",  
        "rules": [  
            {  
                "event_sources": [  
                    {  
                        "type": "offline_events",  
                        "id": "<OFFLINE_EVENT_SET_ID>"  
                    }  
                ],  
                "retention_seconds": 2592000,  
                "filter": {  
                    "operator": "and",  
                    "filters": [  
                        {  
                            "field": "event",  
                            "operator": "eq",  
                            "value": "Purchase"  
                        },  
                        {  
                            "operator": "or",  
                            "filters": [  
                                {  
                                    "field": "value",  
                                    "operator": ">=",  
                                    "value": "100"  
                                }  
                            ]  
                        }  
                    ]  
                }  
            }  
        ]  
    }  
}

Match Purchase events where the product's color is blue defined by offline event attributes in the custom_data field called 'color' in the last 30 days. Use this rule for the following event:

{  
    "inclusions": {  
        "operator": "or",  
        "rules": [  
            {  
                "event_sources": [  
                    {  
                        "type": "offline_events",  
                        "id": "<OFFLINE_EVENT_SET_ID>"  
                    }  
                ],  
                "retention_seconds": 2592000,  
                "filter": {  
                    "operator": "and",  
                    "filters": [  
                        {  
                            "field": "event",  
                            "operator": "eq",  
                            "value": "Purchase"  
                        },  
                        {  
                            "operator": "or",  
                            "filters": [  
                                {  
                                    "field": "custom_data.color",  
                                    "operator": "eq",  
                                    "value": "blue"  
                                }  
                            ]  
                        }  
                    ]  
                }  
            }  
        ]  
    }  
}

Best practices

• Experiment with different audiences, for example, people who purchased frequently in the past that did not return recently or people who purchased only from one category.
• Create Lookalike audiences based on audiences that have the highest performance.