在此頁面上：瞭解在歷程中使用體驗事件的可擴充模式及最佳實務，以根據其行為和事件屬性隱藏、限定或個人化設定檔。
此頁面概述常見的模式和可擴充的方法，以協助您在Adobe Journey Optimizer中善用體驗事件。 這些使用案例旨在協助您解決經常遇到的挑戰，例如管理選擇退出、控制訊息頻率、根據使用者行為個人化內容以及對即時訊號做出反應。
運用這些策略，您可以將行為資料轉換為有意義的動作，也就是根據設定檔觸發的事件或屬性隱藏、限定或排除設定檔。 無論您是建置購買臨界值、放棄觸發程式或跳出處理的邏輯，這些範例都能提供您可因應需求的實用指引。
在評估哪種方法最適合時，請考慮使用案例的延遲需求，以確保您的歷程保持回應式且有效。
選擇退出隱藏
若要隱藏已選擇退出行銷通訊的設定檔，請使用內建的同意管理。 選擇退出偏好設定會在設定檔的同意欄位中自動擷取；它們可以在歷程條件中直接參考，並在訊息傳送期間由Journey Optimizer自動強制執行。
了解更多：
跳出型隱藏
若要排除發生電子郵件跳出的設定檔，請利用Adobe Journey Optimizer的自動隱藏清單來隱藏跳出的地址。 此內建機制可確保將無效或無法存取的電子郵件從未來的傳送中排除，而不需要自訂邏輯。
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一般隱藏
若要隱藏已示範特定行為的設定檔，請使用具有事件型邏輯的批次對象，以擷取符合隱藏條件的設定檔。 在歷程條件中參考此對象。
了解更多：
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Adobe Experience Platform 區段產生器 — 事件
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Adobe Experience Platform 區段產生器 — 時間限制
通訊收到的排除
若要防止傳送訊息給在最近一段時間內收到任何通訊的設定檔：
- 使用具有時間型條件的批次對象，並在歷程條件中參照它們。
- 套用頻率上限商業規則以強制執行每日或每週訊息限制。
使用對象深入瞭解：
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Adobe Experience Platform 區段產生器 — 事件
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Adobe Experience Platform 區段產生器 — 時間限制
另請參閱:
訊息特定包含/排除
若要根據設定檔是否收到特定訊息來包含或排除設定檔，請建立封裝此邏輯的批次對象，並在歷程條件中參考這些對象。
了解更多：
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Adobe Experience Platform 區段產生器 — 事件
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Adobe Experience Platform 區段產生器 — 時間限制
購物車或瀏覽放棄個人化
若要根據最新的購物車進行個人化通訊，或跨多種購物車型別或產品檢視瀏覽事件：
- 如果您可以存取Adobe Experience Platform 資料Distiller，請設定自動查詢以擷取事件中所需的資料、操作它以符合使用案例，並將它寫回已啟用設定檔的資料集以進行啟用。
- 如果可以在具有純量屬性的設定檔上建立放棄資料的模型，請考慮使用計算屬性來擷取最新資訊，然後在歷程中參照這些屬性來建構通訊。 深入瞭解 Adobe Experience Platform 檔案
行為型歷程退出
若要在設定檔顯示特定行為時將其從歷程中移除，可在收到特定事件或設定檔符合特定對象資格時，利用退出條件從歷程中退出設定檔。
了解更多：
以購買為基礎的資格，含值臨界值
若要根據購買觸發歷程並隱藏值是否高於/低於臨界值，請定義計算屬性以加總特定時段內的購買。 建立受眾，其中包含支出金額符合特定條件的設定檔。
了解更多：
- Adobe Experience Platform 計算屬性總覽
常見問題 faq-ee
此常見問題集主要針對在歷程運算式中淘汰體驗事件使用方式的時間表以及受影響者。 如需替代方法的指引，請參閱上述使用案例和最佳實務。
需要更多詳細資料？ 使用此頁面底部的意見回饋選項來提出您的問題，或與Adobe Journey Optimizer 社群連結。
只有運算式編輯器中的體驗事件查詢會受到影響。 下列功能 不 受影響，且保持不變：
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觀察與設定檔UI中特定設定檔相關聯的體驗事件
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在計算屬性規則中使用體驗事件並存取歷程中的計算屬性
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觸發具有單一或業務事件的歷程
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在運算式和個人化編輯器中使用來自觸發歷程之事件的歷程內容資料
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聆聽歷程中的事件
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設定事件以觸發歷程
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偵測行銷通訊的一般使用者反應事件（例如電子郵件開啟）
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.