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Oracle 1Z0-1161-1 Exam Syllabus Topics:

Topic
Details

Topic 1

OMBPs for CX Marketing: This section of the exam measures the skills of Training and Learning Managers and focuses on how OMBPs enhance CX Marketing processes. It explains the flow from audience generation to opportunity creation, ensuring targeted marketing efforts lead to successful conversions. Design considerations and important takeaways for implementing CX Marketing OMBPs are covered, helping organizations optimize marketing strategies. The section also describes key metrics that assess the success of CX Marketing OMBPs, ensuring effectiveness in execution and performance evaluation.

Topic 2

Oracle Cloud Applications and Oracle Modern Best Practice (OMBP): This section of the exam measures the skills of OGL Administrators and covers the offerings and capabilities of Oracle Cloud Applications. It explains how Oracle Cloud solutions help businesses streamline operations, enhance customer experience, and improve decision-making. The key features of the Oracle CX suite are outlined, providing insight into its role in customer engagement. Additionally, it explains how data flows between various CX Modern Best Practices (OMBPs) to ensure seamless integration and operational efficiency.

Topic 3

OMBPs for CX Service: This section of the exam measures the skills of OGL Administrators and focuses on customer service processes within Oracle Cloud. It explains the process from initial customer contact to service resolution, ensuring efficient and timely handling of customer inquiries. The design considerations and important takeaways for CX Service OMBPs are discussed, helping businesses improve their service operations. Additionally, key metrics are outlined to measure the successful execution of CX Service OMBPs, ensuring high-quality customer support and satisfaction.

Topic 4

OMBPs for CX Sales Performance Management: This section of the exam measures the skills of Training and Learning Managers and covers sales performance management using OMBPs. It explains the process from designing a compensation plan to making participant payments, ensuring sales teams are effectively rewarded. The section highlights key considerations and takeaways for implementing CX Sales Performance OMBPs to optimize incentive structures. Furthermore, the key metrics used to measure the success of these OMBPs are described, helping organizations track and refine their compensation strategies.

>> New 1Z0-1161-1 Test Topics <<

Quiz 2025 Updated Oracle New 1Z0-1161-1 Test Topics

The desktop software Oracle Fusion Cloud Applications CX Foundations Associate - Rel 1 (1Z0-1161-1) practice exam format can be used easily used on your Windows system. Customers can use it without the internet. PassTestking have made all of the different formats so the students won't face any extra issues and crack Oracle Fusion Cloud Applications CX Foundations Associate - Rel 1 (1Z0-1161-1) certification exams for the betterment of their futures.

Oracle Fusion Cloud Applications CX Foundations Associate - Rel 1 Sample Questions (Q38-Q43):

NEW QUESTION # 38
Which feature in Oracle Fusion Cloud SCM ensures real-time communication between suppliers and buyers?

A. Supplier Qualification.
B. Manufacturing Execution.
C. Cost Accounting.
D. Supply Chain Collaboration.

Answer: D

Explanation:
Oracle Fusion Cloud SCM facilitates supplier-buyer interactions through Supply Chain Collaboration.
Functionality: Provides a platform for real-time data sharing (e.g., forecasts, orders, inventory) between suppliers and buyers.
Benefit: Enhances coordination, visibility, and responsiveness in the supply chain.
Option A (Cost Accounting): Focuses on financial tracking, not communication.
Option B (Qualification): Assesses suppliers, not real-time interaction.
Option D (Manufacturing): Manages production, not supplier communication.
Oracle Fusion Cloud SCM documentation, such as "Supply Chain Collaboration Guides," confirms this feature's role.

NEW QUESTION # 39
How do AI/ML technologies assist in enhancing productivity within the Campaign Execution to Opportunity OMBP in Oracle Fusion Cloud CX Marketing?

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

Answer: C

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 # 40
What is the primary function of the Order Promising process in Oracle Fusion Cloud SCM?

A. To only manage orders for direct-to-customer deliveries.
B. To provide accurate order commitment dates based on supply and demand availability.
C. To guarantee same-day shipping for all orders.
D. To eliminate the need for supplier collaboration.

Answer: B

Explanation:
The Order Promising process in Oracle Fusion Cloud SCM ensures reliable order fulfillment. Its primary function is to provide accurate order commitment dates based on supply and demand availability.
Process: Evaluates inventory, production, and supplier data to calculate realistic delivery dates.
Benefit: Sets customer expectations accurately, improving satisfaction and planning.
Option A (Direct Deliveries): Applies broadly, not just to direct orders.
Option B (No Collaboration): Relies on supplier data integration.
Option D (Same-Day): Not feasible for all orders; focuses on accuracy.
Oracle Fusion Cloud SCM documentation, like "Order Management Guides," confirms this function.
Reference:
Below are the corrected and formatted questions based on your input, with 100% verified answers aligned with Oracle Fusion Cloud Applications CX and SCM official documentation. Each question includes a detailed explanation referencing relevant Oracle Fusion Cloud concepts. Typing errors have been corrected, and the format adheres to your specified structure.

NEW QUESTION # 41
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. AI/ML analyzes sales performance data, identifies top-performing behaviors, and generates recommended actions to drive productivity and earnings.
B. (Option "6" - not applicable).
C. AI/ML provides general sales performance reports, offering insights.
D. AI/ML automates the incentive calculation process, ensuring accuracy.

Answer: A

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 # 42
Which metric is used to measure the success of the Knowledge Gap to Solution OMBP?

A. All of the above.
B. Customer satisfaction ratings.
C. Knowledge article accuracy.
D. Average case resolution time.

Answer: A

Explanation:
The Knowledge Gap to Solution OMBP in Oracle Fusion Cloud CX Service aims to bridge agent knowledge gaps to resolve customer issues effectively. Its success is measured by a combination of metrics: customer satisfaction ratings, average case resolution time, and knowledge article accuracy, making "All of the above" the correct answer.
Customer Satisfaction Ratings: Reflects how well resolutions meet customer expectations, a direct outcome of effective knowledge use.
Average Case Resolution Time: Measures the efficiency of applying knowledge to close cases quickly, indicating process effectiveness.
Knowledge Article Accuracy: Ensures the solutions provided are correct, reducing rework and enhancing trust in the knowledge base.
Combined Impact: These metrics together provide a holistic view of the OMBP's success in improving service quality, speed, and accuracy.
Oracle Fusion Cloud CX Service documentation, such as "Service Center Guides" and "CX Analytics FAQs," emphasizes these metrics as critical for evaluating knowledge-driven processes.

NEW QUESTION # 43
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