在此页面上：了解在历程中使用体验事件的可扩展模式和最佳实践，以根据用户档案的行为和事件属性禁止、限定或个性化用户档案。
本页概述了帮助您在Adobe Journey Optimizer中充分利用Experience事件的常见模式和可扩展方法。 这些用例旨在帮助您解决频繁出现的挑战，例如管理选择退出、控制消息频率、根据用户行为个性化内容以及对实时信号做出反应。
利用这些策略，您可以将行为数据转化为有意义的操作 — 根据用户档案触发的事件或携带的属性禁止、限定或排除用户档案。 无论您是构建购买阈值、放弃触发器还是退回处理的逻辑，这些示例都提供了可适应您的需求的实用指南。
在评估哪种方法最合适时，请考虑用例的延迟要求以确保历程保持响应和有效。
选择退出抑制
要禁止已选择退出营销通信的用户档案，请使用内置的同意管理。 选择退出偏好设置会在用户档案的同意字段中自动捕获；它们可以在历程条件中直接引用，并在消息投放期间由Journey Optimizer自动实施。
了解详情：
基于退回的抑制
要排除经历过电子邮件退回的用户档案，请利用Adobe Journey Optimizer的退回地址自动禁止列表。 这种内置机制可确保将无效或不可达电子邮件从未来发送中排除，而无需自定义逻辑。
了解详情：
常规禁止显示
要禁止显示特定行为的用户档案，请使用具有基于事件的逻辑的批量受众来捕获符合禁止标准的用户档案。 在历程条件中引用此受众。
了解详情：
-
Adobe Experience Platform 区段生成器 — 事件
-
Adobe Experience Platform 区段生成器 — 时间约束
来文收到的排除
要防止向在最近的时间范围内收到任何通信的用户档案发送消息，请执行以下操作：
- 使用具有基于时间的标准的批处理受众，并在历程条件中引用它们。
- 应用频率上限业务规则以实施每日或每周消息限制。
使用受众了解详情：
-
Adobe Experience Platform 区段生成器 — 事件
-
Adobe Experience Platform 区段生成器 — 时间约束
另请参阅：
特定于消息的包含/排除
要根据用户档案是否收到特定消息来包含或排除用户档案，请创建封装此逻辑并在历程条件中引用这些逻辑的批量受众。
了解详情：
-
Adobe Experience Platform 区段生成器 — 事件
-
Adobe Experience Platform 区段生成器 — 时间约束
购物车或浏览放弃个性化
要根据最新的购物车使通信个性化，或浏览多个购物车类型或产品视图中的事件，请执行以下操作：
- 如果您有权访问Adobe Experience Platform 数据Distiller，请配置自动查询以从事件中提取所需数据，处理它以适合用例，并将其写回启用了配置文件的数据集以进行激活。
- 如果可以在具有标量属性的配置文件上建模放弃数据，请考虑使用计算属性捕获最新信息，然后在历程中引用这些属性来构建通信。 请参阅 Adobe Experience Platform 文档以了解详情
基于行为的历程退出
要在用户档案展现特定行为时从历程中删除它们，请在收到特定事件或用户档案符合特定受众资格时，利用退出标准从历程退出用户档案。
了解详情：
基于购买且有价值阈值的资格鉴定
要根据购买触发历程并禁止值大于/低于阈值，请定义计算属性以汇总特定时间段的购买。 创建受众，该受众包含支出额符合特定条件的用户档案。
了解详情：
- Adobe Experience Platform 计算属性概述
常见问题 faq-ee
此常见问题解答侧重于在历程表达式中弃用体验事件使用情况的时间表以及受影响的人员。 有关替代方法的指导，请参阅上面的用例和最佳实践。
需要更多信息？ 使用此页面底部的反馈选项提出您的问题，或与Adobe Journey Optimizer 社区建立联系。
只有表达式编辑器中的体验事件查找会受到影响。 以下功能不受影响，并且保持不变：
-
在配置文件UI中观察与特定配置文件关联的体验事件
-
在计算属性规则中使用体验事件并访问历程中的计算属性
-
触发具有单一或业务事件的历程
-
在表达式和个性化编辑器中使用来自触发历程的事件的历程上下文数据
-
侦听历程中的事件
-
配置事件以触发历程
-
检测最终用户对营销通信的反应事件（例如，电子邮件打开）
This section contains structured knowledge intended to support interpretation, retrieval, and question answering related to this topic.
For complete understanding, this information should be combined with the documentation on this page. Neither source is intended to stand alone; the page describes the feature, while this section provides additional context that helps disambiguate terminology, intent, applicability, and constraints.
- TL;DR: This page outlines alternative patterns and best practices for using Experience Event data in Adobe Journey Optimizer journeys, in the context of the deprecation of direct experience event lookup in the journey expression editor.
Intents:
- Suppress opted-out profiles using built-in consent management instead of experience event expressions
- Exclude bounced email addresses using the AJO automatic suppression list
- Build generic suppression logic using batch audiences with event-based criteria
- Prevent over-communication by applying frequency capping rules or time-based audience conditions
- Personalize abandoned cart or browse communications using AEP Data Distiller or Computed attributes
Glossary:
- Experience event: A time-stamped, immutable record of a customer action or behavior stored in Adobe Experience Platform (product-specific)
- Computed attribute: A profile-level attribute derived from aggregating or summarizing experience event data over time, available for use in journey expressions (product-specific)
- Suppression list: AJO’s built-in list of email addresses automatically excluded from future sends due to hard bounces or spam complaints (product-specific)
- Frequency capping: A business rule that limits how many messages a profile can receive within a defined time window (product-specific)
- Data Distiller: An AEP capability that enables SQL-based batch queries to extract and transform event data into profile-enabled datasets (product-specific)
Guardrails:
- Starting July 8, 2025, new customer organizations cannot create expressions using experience event attributes in the journey expression editor.
- Starting April 1, 2026, organizations that have not used experience event attributes in journey expressions in the last 90 days will lose access to this capability.
- Direct experience event lookup in journey conditions is being retired; alternatives include batch audiences, computed attributes, and AEP Data Distiller.
- Capabilities NOT impacted by the retirement include: triggering journeys with events, listening to events within a journey, using journey context data from trigger events, configuring events, and detecting reaction events.
Terminology:
- Canonical name: Experience event lookup — Acronym: EE lookup — variants: experience event expressions, event attribute lookup
- Synonyms: “batch audience with event-based logic” = “event-based segment” as a suppression/inclusion mechanism
- Do not confuse: “experience event lookup in expression editor” ≠ “triggering a journey with an event” — triggering journeys with events is NOT being retired
FAQ:
- Q: Can I still trigger a journey using an experience event? — Yes, triggering journeys with unitary or business events is not impacted by this change.
- Q: What is the recommended replacement for experience event lookup in journey conditions? — Use batch audiences built with AEP Segment Builder event-based logic, computed attributes, or AEP Data Distiller for complex transformations.
- Q: Is my existing organization affected right now? — New organizations are affected from July 8, 2025. Existing organizations are affected from April 1, 2026 only if they have not used the capability in the last 90 days.
- Q: How do I handle cart abandonment personalization without direct event lookup? — Use AEP Data Distiller to extract and write event data to a profile-enabled dataset, or use Computed attributes to capture the latest abandonment state on the profile.
- Q: What capabilities are NOT impacted by this deprecation? — Triggering journeys with events, listening to events inside journeys, using trigger event context data in expressions, configuring events, and detecting reaction events (e.g., email opens) are all unaffected.