Global Certificate in Retention Data Analysis Framework

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The Global Certificate in Retention Data Analysis Framework is a comprehensive course designed to equip learners with essential skills in data analysis for customer retention. This certification is crucial in today's data-driven world, where businesses rely heavily on customer retention for growth and sustainability.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

The course is in high demand across various industries, including marketing, sales, and customer service. It provides learners with the knowledge and tools to analyze customer behavior, identify retention strategies, and make data-driven decisions. By the end of the course, learners will be able to construct and implement a retention data analysis framework, thereby improving their organization's customer retention rates. This course is an excellent opportunity for career advancement. It provides learners with a competitive edge in the job market by validating their skills in data analysis and customer retention. Whether you're a professional looking to upskill or a student entering the job market, this course is a valuable addition to your resume.

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ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Data Collection Techniques: Understanding the various methods for gathering and measuring data, including surveys, interviews, and secondary sources.
โ€ข Data Analysis Tools: Introduction to popular data analysis tools and software, such as Excel, SPSS, and R.
โ€ข Data Cleaning and Preparation: Techniques for cleaning and preparing data for analysis, including handling missing values, outliers, and data transformations.
โ€ข Descriptive and Inferential Statistics: Overview of statistical methods, including measures of central tendency, dispersion, and correlation, as well as hypothesis testing.
โ€ข Predictive Analytics: Introduction to predictive modeling, including regression analysis, decision trees, and machine learning algorithms.
โ€ข Retention Metrics and KPIs: Understanding the key performance indicators used to measure customer retention, such as churn rate, customer lifetime value, and net promoter score.
โ€ข Segmentation and Customer Analysis: Techniques for segmenting customers and analyzing customer behavior, including RFM analysis and cohort analysis.
โ€ข Data Visualization and Reporting: Best practices for presenting data insights and recommendations, including data visualization tools and creating data dashboards.
โ€ข Ethics in Data Analysis: Discussion of ethical considerations in data analysis, including data privacy, security, and informed consent.

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ใ‚ณใƒผใ‚นใ‚’ๅฎŒไบ†ใ™ใ‚‹ใฎใซใฉใ‚Œใใ‚‰ใ„ๆ™‚้–“ใŒใ‹ใ‹ใ‚Šใพใ™ใ‹๏ผŸ

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ใ„ใคใ‚ณใƒผใ‚นใ‚’้–‹ๅง‹ใงใใพใ™ใ‹๏ผŸ

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ใ“ใฎใ‚ณใƒผใ‚นใฎๆ”ฏๆ‰•ใ„ใฎใŸใ‚ใซไผš็คพ็”จใฎ่ซ‹ๆฑ‚ๆ›ธใ‚’ใƒชใ‚ฏใ‚จใ‚นใƒˆใ—ใฆใใ ใ•ใ„ใ€‚

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ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
GLOBAL CERTIFICATE IN RETENTION DATA ANALYSIS FRAMEWORK
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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