100% 1Z0-1161-1 ACCURACY WILL BE YOUR SHARPEST SWORD TO PASS ORACLE FUSION CLOUD APPLICATIONS CX FOUNDATIONS ASSOCIATE - REL 1

100% 1Z0-1161-1 Accuracy Will Be Your Sharpest Sword to Pass Oracle Fusion Cloud Applications CX Foundations Associate - Rel 1

100% 1Z0-1161-1 Accuracy Will Be Your Sharpest Sword to Pass Oracle Fusion Cloud Applications CX Foundations Associate - Rel 1

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Oracle Fusion Cloud Applications CX Foundations Associate - Rel 1 Sample Questions (Q22-Q27):

NEW QUESTION # 22
How do AI/ML technologies assist in enhancing productivity within the Campaign Execution to Opportunity OMBP in Oracle Fusion Cloud CX Marketing?

  • A. AI provides robust reporting options, allowing for better customer targeting and behavioral analysis.
  • B. ML generates creative content for campaigns, reducing human effort.
  • C. ML algorithms forecast market trends, guiding campaign strategies.
  • D. AI-powered chatbots handle customer inquiries, allowing agents to focus on complex tasks.

Answer: A

Explanation:
The Campaign Execution to Opportunity OMBP in Oracle Fusion Cloud CX Marketing focuses on turning marketing campaigns into sales opportunities. AI/ML enhances productivity here by providing robust reporting options, allowing for better customer targeting and behavioral analysis.
AI analyzes campaign performance data (e.g., engagement rates, conversions) and customer behavior (e.g., preferences, purchase history).
Robust reporting delivers actionable insights, enabling precise targeting and personalized campaigns that increase opportunity creation.
This data-driven approach reduces manual analysis time, boosting marketing team productivity.
Option A (Chatbots): Chatbots are more relevant to service, not campaign execution.
Option B (Content Generation): ML can assist with content, but it's not the primary productivity driver in this OMBP.
Option C (Trend Forecasting): Forecasting informs strategy but doesn't directly enhance execution productivity.
Oracle's "Oracle AI for Fusion Applications" and "CX Marketing" guides emphasize AI's role in advanced analytics and targeting for marketing processes.


NEW QUESTION # 23
Which metric indicates the success of the Opportunity to Quote OMBP in Oracle Fusion Cloud CX Sales?

  • A. Quote Volume that provides an overview of sales activity.
  • B. Sales Revenue that directly measures the OMBP's effectiveness in the quoting process.
  • C. Average Time to Quote Acceptance that measures the efficiency of the quoting process.

Answer: C

Explanation:
The success of the Opportunity to Quote OMBP hinges on how efficiently and effectively quotes move from creation to acceptance. The Average Time to Quote Acceptance is the key metric here, as it measures the efficiency of the quoting process by tracking the time from quote delivery to customer acceptance.
A shorter time indicates a streamlined, responsive process, which is critical for customer satisfaction and deal closure.
It directly ties to the OMBP's goal of optimizing the quote lifecycle.
Option B (Sales Revenue): Revenue is an outcome metric, not a direct indicator of the quoting process's success.
Option C (Quote Volume): Volume reflects activity but not the quality or efficiency of the process.
Per Oracle Fusion Cloud CX Sales documentation, including "CX Analytics FAQs," this metric is pivotal for evaluating process efficiency.


NEW QUESTION # 24
Which metric is essential for a comprehensive evaluation of the Customer Contact to Resolution OMBP in Oracle Fusion Cloud CX Service?

  • A. Total Number of Customer Inquiries Handled, which considers the quality and complexity of the issues resolved.
  • B. Resolve Time, which captures the efficiency of the resolution process.
  • C. Internal Help Desk Ticket Resolution Rate, which measures how internal issues are resolved.
  • D. Service Agent Response Time, which measures how quickly the service agent responds.

Answer: B

Explanation:
The Customer Contact to Resolution OMBP focuses on efficiently resolving customer issues. The essential metric for a comprehensive evaluation is Resolve Time, which captures the efficiency of the entire resolution process.
Scope: Measures the duration from contact initiation to issue closure, encompassing agent response, troubleshooting, and solution delivery.
Importance: Shorter resolve times indicate higher efficiency, directly impacting customer satisfaction and agent performance.
Option A (Response Time): Only measures initial contact, not full resolution.
Option C (Internal Rate): Focuses on internal issues, not customer-facing resolutions.
Option D (Inquiry Count): Reflects volume, not efficiency or quality.
Oracle Fusion Cloud CX Service documentation, such as "Service Center Guides," identifies Resolve Time as a core metric for this OMBP.


NEW QUESTION # 25
Which KPI provides valuable insight into the performance of the Opportunity to Quote OMBP?

  • A. Total Quotes Sent that tracks the aggregate number of quotes that have been generated and sent.
  • B. Average Deal Size that provides insight into the typical value of revenue generated.
  • C. Quote to Win Ratio that compares the number of quotes sent to the number of deals won.

Answer: C

Explanation:
The Opportunity to Quote OMBP focuses on converting opportunities into successful quotes. The Quote to Win Ratio is the KPI that provides the most valuable insight into this process's performance.
It compares the number of quotes sent to the number of deals won, directly measuring the effectiveness of the quoting process in securing business.
A high ratio indicates quotes are well-targeted and compelling, while a low ratio signals inefficiencies or misalignments.
Option A (Total Quotes Sent): This measures activity volume but not success or performance quality.
Option B (Average Deal Size): While valuable, it reflects outcomes rather than the quoting process's performance.
Oracle Fusion Cloud CX Sales documentation, such as "CX Analytics FAQs," highlights Quote to Win Ratio as a critical KPI for assessing conversion efficiency in sales processes.


NEW QUESTION # 26
How do AI/ML algorithms boost productivity and earnings for sales representatives and managers in the Incentive Plan to Seller Earnings OMBP in Oracle Fusion Cloud CX Sales Performance?

  • A. (Option "6" - not applicable).
  • B. AI/ML analyzes sales performance data, identifies top-performing behaviors, and generates recommended actions to drive productivity and earnings.
  • C. AI/ML provides general sales performance reports, offering insights.
  • D. AI/ML automates the incentive calculation process, ensuring accuracy.

Answer: B

Explanation:
The Incentive Plan to Seller Earnings OMBP in Oracle Fusion Cloud CX Sales Performance leverages AI and machine learning (ML) to optimize how sales teams are compensated and motivated. The most comprehensive way AI/ML boosts productivity and earnings is by analyzing sales performance data, identifying top-performing behaviors, and generating recommended actions.
AI/ML examines historical and real-time sales data to pinpoint what drives success (e.g., specific selling techniques or customer interactions).
It identifies top performers' behaviors, enabling managers to replicate these across the team.
Recommended actions (e.g., adjusting focus on high-value opportunities) directly enhance productivity and, consequently, earnings tied to incentives.
Option A (General Reports): While reports provide insights, they lack the actionable, predictive power of AI/ML-driven recommendations.
Option B (Automating Calculations): Automation improves efficiency and accuracy in payouts but doesn't directly boost productivity or earnings potential.
Option C: Not applicable as per the original input.
Oracle's documentation, such as "Oracle AI for Fusion Applications" and "CX Sales Performance Guides," highlights how AI/ML delivers personalized, data-driven insights to enhance sales outcomes, aligning with this OMBP's goals.


NEW QUESTION # 27
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