IBM SPSS Predictive Analytics Sales Mastery v1 : M2020-229 exam

M2020-229 real exams

Exam Code: M2020-229

Exam Name: IBM SPSS Predictive Analytics Sales Mastery v1

Updated: Jul 28, 2026

Q & A: 45 Questions and Answers

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IBM M2020-229 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: IBM SPSS Predictive Analytics Overview25%- Value proposition and business benefits
- Market positioning and target industries
Topic 2: Sales and Solution Selling25%- Solution alignment to business needs
- Customer use cases and pain points
- Competitive differentiation
Topic 3: SPSS Product Portfolio35%- SPSS Decision Management
- SPSS Data Collection
- SPSS Modeler
- SPSS Statistics
- SPSS Collaboration and Deployment Services
Topic 4: Licensing and Implementation15%- Licensing models and editions
- Deployment and integration basics

IBM SPSS Predictive Analytics Sales Mastery v1 Sample Questions:

1. Which input is NOT used to define decisions within SPSS Decision Management?

A) System created predictive models
B) Human defined rules
C) Intuition
D) Business objectives


2. Which organization is the best prospect for SPSS Statistics?

A) A government institution looking to validate policy assumptions.
B) A retail chain looking to build predictive models.
C) A research group looking to craft multi-channel surveys.
D) An insurance company looking for new ways to retain profitable customers.


3. What is the main capability of SPSS Statistics?

A) Analysis
B) Prediction
C) Automation
D) Collaboration


4. Which message is the most important for a sales representative to deliver when selling SPSS Collaboration and Deployment Services (C&DS) to a line of business user?

A) Automation and collaboration lead to enhanced productivity from analysts.
B) IT can monitor and control C&DS processes without having to know analytic details.
C) C&DS increases the reliability of analytical results.
D) C&DS integrates with the existing enterprise environment.


5. A customer wants to optimize their data for simpler, more accurate, and faster models. Which family of algorithms/techniques best meets their needs?

A) Association
B) Reduction
C) Segmentation
D) Classification


Solutions:

Question # 1
Answer: C
Question # 2
Answer: A
Question # 3
Answer: A
Question # 4
Answer: D
Question # 5
Answer: D

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