AJO Orchestrated Campaigns Introduction

Prior to the introduction of Orchestrated Campaigns, AJO campaigns were limited, often described as marketing initiated, single step "blasts" sent to predefined audiences without an orchestration layer. AJO Orchestrated Campaigns fundamentally changes this landscape, bringing parity with AJO journeys by introducing multi step execution, on demand audience creation, and a crucial orchestration layer. Existing AJO campaigns remain available and are now referred to as Action Campaigns, while the new offering is known as AJO Orchestrated Campaigns. While Action Campaigns still rely on existing XDM schemas, Orchestrated Campaigns are built upon a new model based relational schema.

Core Capabilities for Advanced Marketing

1. The Workflow Canvas

   A key component is the new workflow canvas, which is highly synergistic with those found in traditional campaign management solutions like Adobe Campaign or Unica. This single canvas allows marketers to manage the entire process, from audience creation and business rule authoring to orchestrating multi step execution. Within the canvas, users have native activities for segmentation, including query, split, combine, deduplication, reconciliation, change dimension, forks, and joins. Crucially, the focus remains on delivering a message; non marketing activities like raw JavaScript loops or raw SQL code writing are not included in this canvas.

2. On Demand Audiences

   Orchestrated Campaigns allow marketers to dynamically create and activate audiences instantly at the time of send, eliminating reliance on pre built audiences. This functionality is ideal for time sensitive use cases, such as quickly sending a weather alert or promoting a short duration sale.

3. Multi Entity Segmentation and Sending

   The new capabilities enable sophisticated segmentation based on multiple data entities, such as combining loyalty tables, purchase entities, and guest data. A major innovation is multi entity sending (or multi level sending), which allows brands to target the same person with different, contextually relevant campaigns simultaneously. For instance, a bank customer with multiple accounts (checking, mortgage, retirement) can receive multiple distinct, personalized emails. This approach allows treating the customer at the account level rather than solely at the profile level, driving deep personalization using business context.

4. Pre Send Visibility and Multi Step Workflows

   Marketers gain visibility into segmentation results by seeing accurate counts after each operation within the workflow canvas. This enables optimization, refinement, and business forecasting prior to launching campaigns. The canvas supports multi step campaigns, such as macro campaigns like "Back to School" or "Holiday" sequences, involving multiple steps for awareness, engagement, promotions, and reminders.

The Relational Store

AJO Orchestrated Campaigns introduces new architecture centered around the Relational Store. This store utilizes a relational data model (referred to as Relational XDM or Model Based Relational Schema), which runs beneath the orchestration UI.

Data Modeling and Ingestion

Data loading into the relational store only supports batch ingestion. The Relational Store differs from the Real Time Customer Profile (RTCP) in several key ways:

• Data Model: Uses Relational XDM (flat/scalar fields), which cannot support complex objects like arrays or maps.

• Entities Supported: Supports any entity type (customer, property, car parts, etc.), not just person, traits, and behaviors.

• Ingestion: Batch only, utilizing the same pipes and connectors as AJO journeys.

• Data Requirements: Requires all relational schemas to have a primary key and a version descriptor field to track last modification dates.

  Data is written to the Data Lake first, and then a job processes the data into the Relational Store. Data can be modeled manually or rapidly created by uploading a DDL file (Data Definition Language).

Data Strategy Where to Put Your Data?

Determining whether data should reside in the RTCP or the Relational Store depends on the use case.

• Relational Store (Directional Fit): Recommended if the source data is already relational, if high volume history is needed (looking back more than 12–36 months), or if there is a need for ad hoc audience creation evaluation activation.

• Real Time Customer Profile (Directional Fit): Recommended if the source data is streaming, data freshness is critical, or if the scenario requires immediate action or decisioning in the moment.

Message Sending and Personalization

Despite the new relational data capabilities, the Real Time Customer Profile remains central to delivery.

1. Reconciliation: The audience derived from the relational store must be reconciled back to the RTCP using a Profile Target Dimension configuration. This requires identifying which relational schema identity value (e.g., Customer ID) links the relational data to the RTCP.

2. Consent as Source of Truth: The RTCP is the single source of truth for consent and communication history. If a person is opted out in the RTCP, the message will not be sent. If a profile does not exist, a "skinny profile" is created on the fly based on the channel execution address (like the email address).

3. Personalization: Personalization utilizes the same frameworks as AJO journeys. It can leverage fields from the RTCP as well as attributes from the Relational Store, including those in the final workflow activity, the profile target dimension, and any directly linked one to one tables.

Multi Entity Sending Target plus Secondary Dimension

Orchestrated Campaigns solve a challenge inherent in individual journey systems by introducing the Target plus Secondary Dimension configuration for message sending. This allows marketers to send multiple messages to the same profile in a single delivery. For example, targeting customers based on reservations (the secondary dimension) while resolving back to the profile (the target dimension) ensures the customer receives one email per reservation record, even though they share the same profile

15+ years of IT work experience as Technical delivery Lead, Analytics Architect, AEP/CJA Implementation Consultant.

Adobe certified expert in Adobe Analytics, Adobe Target, Adobe Experience Platform (AEP), Real-Time Customer Data Platform (RT-CDP), Customer Journey Analytics (CJA), Journey Optimizer (AJO). Well versed with Google Analytics Server-side, Conversion API (CAPI), Privacy & Consent Management (OneTrust).

Deputed to Canada, USA, Netherlands, Germany, UK to work closely with business clients, business analysts, solution architects, solution designers, and other key stakeholders. Passionate to decode the online consumer behaviour by using an analytics data-driven approach.

https://www.linkedin.com/in/pradeep2020/

Pradeep.Jaiswal@ShiftLytic.ca