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Adobe Journey Optimizer Decisioning

Discovery Questionnaire

Purpose

This questionnaire is designed to help Adobe and customer stakeholders evaluate the business, technical, operational, and governance requirements necessary to successfully implement Adobe Journey Optimizer Decisioning.

The objective is to understand how the organization currently manages content and offer decisions, identify opportunities for personalization and optimization, assess readiness for AI-driven decisioning, and define the operational framework required to deliver next-best experiences across channels.

1. Business Objectives & Decisioning Strategy

Purpose

Understand the organization's personalization vision, business goals, and expected outcomes from decisioning.

Questions

  1. What business objectives are driving your interest in Decisioning?
  2. What customer experiences are you hoping to improve through personalized decisioning?
  3. How do you currently determine the next-best offer, content, or experience for a customer?
  4. What challenges exist with your current personalization approach?
  5. Are you primarily optimizing for:
  6. Revenue
  7. Conversion
  8. Engagement
  9. Retention
  10. Loyalty
  11. Customer Lifetime Value
  12. What KPIs would define success for a Decisioning implementation?
  13. Are there specific use cases where decisioning could immediately improve customer experiences?
  14. What level of personalization maturity would you consider your organization to have today?

2. Customer Data & Profile Readiness

Purpose

Evaluate whether the organization has the profile foundation necessary to support decisioning.

Questions

  1. What systems contribute customer data today?
  2. Do you currently maintain a unified customer profile?
  3. What customer attributes are most important for personalization?
  4. How frequently is customer data refreshed?
  5. What real-time customer signals are available?
  6. What contextual data is available at decision time?
  7. Do you currently use audience qualification in real time?
  8. How are customer preferences and consent data maintained?
  9. What customer identifiers are used across systems?
  10. Are there known profile quality challenges that could impact personalization?

Follow-Up Questions

  • Which data sources are considered authoritative?
  • How quickly are profile updates reflected across systems?
  • What profile attributes are most frequently used for targeting?

3. Content & Offer Management

Purpose

Understand how content, offers, and promotional assets are managed today.

Questions

  1. What types of offers or content do you currently personalize?
  2. How many active offers are managed at any given time?
  3. How are offers organized today?
  4. Do you maintain a centralized offer catalog?
  5. How are offer attributes managed?
  6. How frequently are offers updated?
  7. Who owns offer creation and maintenance?
  8. How do business teams search for and reuse offers?
  9. Are offers managed consistently across channels?
  10. How are offer expiration and lifecycle management handled?

Follow-Up Questions

  • Are offers tied to products, services, promotions, or campaigns?
  • Do different business units manage separate offer inventories?

4. Audience & Eligibility Strategy

Purpose

Understand how customer eligibility is determined and managed.

Questions

  1. How do you currently determine who qualifies for a specific offer?
  2. What eligibility rules exist today?
  3. Are offers targeted to:
  4. Audiences
  5. Individual profiles
  6. Both
  7. What exclusion rules are commonly used?
  8. How do you manage suppression lists?
  9. Are there regulatory restrictions impacting eligibility?
  10. Do offers vary by geography, customer status, or product ownership?
  11. How frequently do eligibility rules change?
  12. Are eligibility rules managed by marketing, analytics, or IT teams?
  13. How do you validate eligibility logic before activation?

Follow-Up Questions

  • Do you use audience qualification or attribute-based qualification?
  • Are eligibility decisions currently automated or manually managed?

5. Decision Logic & Prioritization

Purpose

Understand how competing offers and experiences are ranked.

Questions

  1. How do you determine which offer is presented when multiple offers qualify?
  2. Are business priorities currently used to rank offers?
  3. Are there products or services that should receive priority treatment?
  4. Do different business units have competing priorities?
  5. How frequently do prioritization rules change?
  6. Do marketers require manual override capabilities?
  7. Are there situations where offer sequencing matters?
  8. How do you manage fallback experiences when no offer qualifies?
  9. Do you need different prioritization logic for different channels?
  10. How important is transparency into decision outcomes?

Follow-Up Questions

  • Are ranking rules documented today?
  • How are conflicts between offers resolved?

6. AI Optimization & Machine Learning

Purpose

Assess readiness for AI-driven decisioning and optimization.

Questions

  1. Are you currently using AI or machine learning to optimize customer experiences?
  2. What business metrics would you want AI to optimize?
  3. How comfortable is the organization with automated decision-making?
  4. Are explainability requirements important?
  5. Do you require human review of AI-driven decisions?
  6. How do you currently measure personalization effectiveness?
  7. Do you have internal AI governance requirements?
  8. What level of control should marketers retain over optimization?
  9. How frequently would AI models need to be evaluated?
  10. What concerns exist regarding AI-driven personalization?

Follow-Up Questions

  • Are data science resources available internally?
  • Have previous AI initiatives been successful?

7. Experimentation & Optimization Strategy

Purpose

Understand testing maturity and optimization processes.

Questions

  1. Do you currently conduct experimentation?
  2. What types of tests are performed today?
  3. Are you testing:
  4. Offers
  5. Content
  6. Subject lines
  7. Images
  8. Journeys
  9. Channel strategies
  10. How are winning experiences determined?
  11. What KPIs are used to evaluate experiments?
  12. How frequently are experiments conducted?
  13. Who owns experimentation strategy?
  14. How are learnings shared across teams?
  15. What limitations exist in current testing capabilities?
  16. Do you want AI models and rules-based approaches tested against one another?

Follow-Up Questions

  • How many concurrent experiments are typically active?
  • Are statistical significance requirements defined?

8. Channel Activation Strategy

Purpose

Understand where decisions will be delivered and consumed.

Questions

  1. Which channels require decisioning today?
  2. Are decisions required in:
  3. Email
  4. SMS
  5. Push
  6. Web
  7. Mobile App
  8. Call Center
  9. POS
  10. Kiosk
  11. Third-Party Platforms
  12. Do you support inbound personalization?
  13. Do you support outbound personalization?
  14. Are API-driven experiences required?
  15. Are real-time decisions needed at customer interaction points?
  16. What latency requirements exist for decision delivery?
  17. Are external applications expected to consume decisions?
  18. What channels generate the highest business impact?
  19. Are channel experiences coordinated today?

Follow-Up Questions

  • Do channel teams operate independently?
  • How is consistency maintained across channels?

9. Frequency Management & Customer Experience Controls

Purpose

Understand customer fatigue management and experience governance.

Questions

  1. How do you currently manage frequency capping?
  2. Are frequency rules managed globally or by channel?
  3. Are there specific offer-level limits?
  4. How do you prevent overexposure?
  5. What customer fatigue policies exist today?
  6. How are customer preferences enforced?
  7. Do different business units share communication governance?
  8. How do you handle offer suppression after redemption?
  9. Are fallback experiences required?
  10. What customer experience guardrails must always be respected?

Follow-Up Questions

  • Are frequency limits enforced technically or manually?
  • Are fatigue rules documented and governed centrally?

10. Reporting, Measurement & Optimization

Purpose

Define how decisioning performance will be measured.

Questions

  1. What KPIs are most important for decisioning success?
  2. How do you currently measure offer performance?
  3. What reporting platforms are used today?
  4. Is Customer Journey Analytics currently deployed?
  5. How do executives consume performance reporting?
  6. What reporting frequency is required?
  7. How is incremental value measured?
  8. How do you measure customer lifetime value impact?
  9. What insights are needed to optimize decisioning strategies?
  10. What reporting gaps exist today?

Follow-Up Questions

  • Are revenue metrics tied directly to offers?
  • Are attribution models already established?

11. Governance, Privacy & Compliance

Purpose

Ensure responsible use of customer data and decisioning.

Questions

  1. What governance policies apply to personalization?
  2. What regulatory requirements must be supported?
  3. How is customer consent captured?
  4. How is consent enforced?
  5. Are there restricted data classifications?
  6. What privacy reviews are required before activation?
  7. Are there data usage restrictions for personalization?
  8. Who owns governance policy enforcement?
  9. Are audit capabilities required?
  10. What compliance risks concern stakeholders most?

Follow-Up Questions

  • Are DULE policies already implemented?
  • Are there industry-specific regulations to consider?

12. Team Structure & Operating Model

Purpose

Understand organizational ownership and operational readiness.

Questions

  1. Which teams will own Decisioning?
  2. Who owns:
  3. Offers
  4. Content
  5. Decision Logic
  6. AI Models
  7. Reporting
  8. Is there a centralized personalization team?
  9. Are external agencies involved?
  10. How are decisioning changes approved?
  11. What governance committees exist?
  12. How are new use cases prioritized?
  13. What training will be required?
  14. What operational processes need to be established?
  15. How will ongoing optimization be managed?

13. Implementation Readiness & Roadmap

Purpose

Assess project readiness and implementation scope.

Questions

  1. What decisioning use cases are highest priority?
  2. What capabilities must be included in Phase 1?
  3. What capabilities can be deferred?
  4. What dependencies could impact implementation?
  5. Are there timeline constraints?
  6. What resources are available internally?
  7. Will a system integrator participate?
  8. What risks have already been identified?
  9. What executive sponsorship exists?
  10. How will implementation success be measured at:
    • Launch
    • 90 Days
    • 6 Months
    • 12 Months