Build predictive machine learning and forecasting models in Excel to build customer decision and customer behavior
β±οΈ Length: 3.5 total hours
β 4.50/5 rating
π₯ 5,931 students
π September 2025 update
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- Course Overview
- Discover how to transform raw customer data into powerful strategic assets, unlocking deeper insights into customer behavior and market dynamics.
- Learn to proactively anticipate customer needs, predict trends, and identify potential attrition using practical, spreadsheet-based analytical techniques.
- Bridge the gap between data and decisive action by mastering methodologies to enhance customer satisfaction, loyalty, and overall business growth.
- This course emphasizes democratizing advanced analytics, enabling you to build sophisticated predictive models within Excel without requiring complex coding.
- Grasp the end-to-end process of customer analytics, from effective data preparation to the nuanced interpretation of predictive model results for strategic planning.
- Develop a keen eye for critical customer performance indicators that signal future engagement, purchasing patterns, or shifts in loyalty.
- Empower yourself to construct robust analytical frameworks that directly support informed decisions in marketing, sales, and service optimization.
- Requirements / Prerequisites
- A working familiarity with basic Excel functions, formulas, and data manipulation is recommended to ensure a smooth learning progression.
- No prior background in advanced statistics, machine learning, or programming is necessary; the course begins with fundamental concepts.
- An open mind for data exploration and a genuine interest in understanding and influencing customer journeys will be highly beneficial.
- Access to Microsoft Excel (2010 or a newer version) on a Windows operating system is essential for full functionality of all course exercises and add-ins.
- Basic business acumen, especially in areas like marketing, sales, or customer service, will provide valuable context for applying the analytical insights.
- Skills Covered / Tools Used
- Develop expertise in structuring and refining diverse customer datasets for accurate and reliable predictive modeling outcomes.
- Cultivate the ability to apply various statistical modeling techniques directly within Excel, transforming raw data into actionable forecasts.
- Master the integration of Excel’s powerful native features with specialized analytical add-ins for expanded predictive capabilities.
- Gain proficiency in automating repetitive data analysis tasks using Excel’s inherent functionality, streamlining your analytical workflow.
- Refine your capacity to translate complex quantitative results into clear, concise, and compelling narratives for diverse business stakeholders.
- Benefits / Outcomes
- Empower your organization with data-informed decision-making for more effective marketing campaigns, optimized sales efforts, and superior customer service.
- Significantly boost customer retention and lifetime value by predicting future behaviors and intervening strategically.
- Enhance overall business profitability through a deeper, predictive understanding of your customer base and their purchasing cycles.
- Position yourself as a data-savvy professional capable of driving growth and innovation through actionable customer intelligence.
- Acquire practical, transferable skills immediately applicable across a wide spectrum of industries and professional roles focusing on customer relationships.
- Foster a strategic mindset that leverages data to proactively solve business challenges and identify new opportunities for competitive advantage.
- PROS
- Provides an exceptionally accessible and quick pathway (3.5 hours) into the crucial field of predictive customer analytics.
- Leverages the ubiquitous Excel environment, eliminating the need for new software installations or programming language acquisition.
- Focuses heavily on practical, hands-on application, enabling immediate implementation of learned techniques in real-world scenarios.
- Ideal for business professionals and managers seeking to enhance their analytical capabilities without a steep technical learning curve.
- Cost-effective and time-efficient solution for developing valuable skills that directly impact business growth and customer engagement.
- CONS
- While powerful for its intended scope, Excel-based analytics may face limitations when handling extremely massive datasets or requiring highly customized, bespoke machine learning algorithms.
Learning Tracks: English,Business,Sales
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