Customer Data Analytics with R
4.9 (6)
10 Days
·Cohort-based Course
Learn critical skills to build your confidence in analyzing customer data.
Customer Data Analytics with R
4.9 (6)
10 Days
·Cohort-based Course
Learn critical skills to build your confidence in analyzing customer data.
Previously at
Course overview
Unlock the Power of Customer Experience Analytics
Transform from Novice to Proficient in Elevating Your Ability to Decode Customer Insights and Unlock Data-Driven Success!
Value to Students
Gain hands-on R skills, master statistical inference, and become an expert in comparative analysis, regression, and real-world applications. Develop a portfolio showcasing your ability to derive actionable insights from customer data, empowering you to excel in data-driven roles and elevate your career in customer experience analytics.
Topic Overview
1. Basic Descriptive Statistics & Sample Sizing
2. Confidence Intervals
3. Hypothesis Testing
4. 2-Sample Statistics (A/B Testing)
5. ANOVA (Analysis of Variance) aka Multi-Sample Stats
6. Regression Modeling & Analysis
Who is this course for
01
The Career Pivoter
Operations pro eager to pivot into data analytics. Gain R skills for real-world applications and kickstart a new career!
02
The Application-Focused Learner
Tech-savvy data analyst who wants hands-on stats. Bridge theory and practice, master customer analytics.
03
The Refresher Seeker
Experienced ops manager seeking a stats refresher. Elevate strategic decisions with updated skills in CX data.
What you’ll get out of this course
Practical Skills in R and Descriptive Statistics
- Gain hands-on experience with RStudio, setting a strong foundation for all types of data analysis in R.
- Learn to summarize and visualize customer data effectively, making it easier to communicate findings to non-technical stakeholders.
In-Depth Understanding of Statistical Inference
- Master techniques in single-sample inference, including confidence intervals and sample size determination, crucial for accurate customer data analysis.
- Develop skills in hypothesis testing, enabling the validation of assumptions or claims about customer behavior and preferences
Expertise in Comparative Analysis
- Acquire the know-how to conduct A/B testing, essential for evaluating the impact of changes in products or services on customer experience.
- Understand the principles and applications of ANOVA, empowering you to analyze differences across multiple groups or variables.
Proficiency in Regression Analysis
- Learn how to use regression models to predict customer behaviors and preferences, an invaluable forecasting and strategy development skill.
- Understand how to interpret the results of these models in the context of customer experience.
Real-World Applications
- Engage in hands-on projects and case studies that simulate real-world customer experience scenarios, ensuring the skills learned directly apply to workplace challenges.
- Begin a portfolio of work that demonstrates your ability to analyze and derive insights from customer data
Critical Thinking and Problem-Solving
- Cultivate the ability to approach customer data critically by asking the right questions and choosing appropriate statistical methods to find answers.
- Enhance problem-solving skills for tackling complex business challenges related to customer experience and behavior.
This course includes
4 interactive live sessions
Lifetime access to course materials
7 in-depth lessons
Direct access to instructor
3 projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Customer Data Analytics with R
Course syllabus
Week 1
May
8
Live Session 2
Part 1 - The Basics
Part 2 - Hypothesis Testing
Week 2
May
13
Live Session 3
May
15
Live Session 4
Part 3 - Advanced Analytics
Post-course
Optional: 1-on-1 with the Instructor
4.9 (6 ratings)
What students are saying
Meet your instructor
Jasmine Motupalli
Founder + CEO | The Data Love Co.
- Results-driven analytics expert with extensive experience in teaching and AI-driven Customer Intelligence.
- Founder and CEO of The Data Love Co. - Where Data Meets Heart.
- Former Vice President of CX Data at Gusto.
- Former Data Scientist and Technical Program Manager at The Pentagon, overseeing analytics for a $10B+ modernization portfolio.
- Former Assistant Professor of Systems Engineering, directing Engineering Statistics and Business Analytics programs at West Point.
- Graduate of the Master Teacher Program at West Point.
- Former Associate Director of The Center for Leadership and Diversity in STEM, directing STEM workshops and earning recognition for substantial volunteer service.
- Holds an M.S. in Operations Research from GA Tech and a B.S. in Operations Research from West Point.
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Customer Data Analytics with R
Course schedule
7-8 hours
Monday - Friday
2:30pm - 4:00pm MT
This course will meet for 1.5 hours per day for 5 days.
Tuesdays and Thursdays
4:00pm - 6:00pm MT
This course will meet for four 2-hour sessions over 2 weeks.
A Simple Guide to Measuring Customer Sentiment
In the dynamic landscape of customer service, understanding and harnessing customer sentiment is paramount for success. The Data Love Co. has curated a comprehensive guide to empower your organization with actionable insights into customer satisfaction. Whether you're aiming to enhance your service offerings, streamline operations, or boost customer loyalty, our guide provides a roadmap to navigate the intricate world of customer sentiment data.
Want to learn more? Register for our Customer Analytics Course!
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Learning is better with cohorts
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
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