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The increasing availability and granularity of customer data in the modern age has forced a shift in focus toward customers as the most critical unit of analysis in business strategy. While this makes sense, as customers are the true source of revenue for any business, it requires that a number of additional factors are quantified, managed, and leveraged effectively for that strategic shift to be successful.

In this course, you will explore customer lifetime value (CLV) as an objective metric with which customers can be managed more effectively, evaluating the ways in which it can be quantified and improved. You will go from learning what a customer is and performing the calculations necessary to quantify their value from an organization's perspective to determining how the various levers contributing to that value can be managed for a real-world business in the course project. Along the way, you will review some of the challenges and limitations of this approach, finding ways to facilitate the management and allocation of resources such that business success can be achieved.

Evolution of the consumer market is an ongoing and inevitable process, driven to new heights in recent decades by the strategic shift in focus toward customers as the most critical unit of analysis. To spur innovation and growth in this increasingly tumultuous environment, a test-and-learn culture must be fostered to understand customers and harness the power of new ideas.

In this course, you will explore testing as a means of adapting to that evolution, analyzing and leveraging data to inform business and marketing decisions. You will go from learning what testing is and how it can be applied at a basic level to designing and conducting tests in RStudio to understand how to target customers. Along the way, you will evaluate the efficacy of a variety of approaches, finding ways to enhance your analytics and communicate results to better inform business decisions.

The following courses are required to be completed before taking this course:

  • Leveraging Customers for Growth

Improvements in marketing practices in recent decades have had a significant impact on productivity, driven by the increasing efficiency and relevance of customer data collection. Leveraging that data effectively, however, requires that marketing efforts are directed only toward those who are likely to respond, rather than casting as wide a net as possible. Yet to target the right customers, you have to know who they are, which requires that customer data is leveraged such that relevant behaviors can be identified, differentiated, and understood at a granular level. Only then can the value they provide be classified and segmented, allowing for productive management of customers based on those characteristics.

In this course, you will explore RFM (recency, frequency, and monetary value) analysis as a means to classify customer purchase behavior characteristics indicative of a likely response to marketing efforts. You will go from identifying the implicit purpose and value of RFM metrics and workflow to developing and assessing the performance of response models with respect to profitability. Along the way, you will evaluate the pros and cons of RFM analysis in the real world.

The following courses are required to be completed before taking this course:

  • Leveraging Customers for Growth
  • A/B Testing and Analytics

The success of any targeting strategy is dependent on the validity of the models used to select customers, which requires that value distinctions are optimized within the constraints of a marketing budget. While there are a variety of methods available to identify and assess likely drivers of customer response, their ability to differentiate and approximate relative influence on purchase behavior can be limited in scope.

In this course, you will explore logistic regression as a means to enhance the predictive specificity and granularity of response likelihood, estimating and iterating on logistic models to maximize expected profitability. You will go from identifying and leveraging categorical response data common to real-world business interactions to evaluating the probabilistic relevance of associated predictor variables to optimize customer selection for targeting. Along the way, you will compare the relative efficacy of a variety of approaches in their ability to improve return on investment, recognizing the potential implications of those differences with regard to marketing success.

The following courses are required to be completed before taking this course:

  • Leveraging Customers for Growth
  • A/B Testing and Analytics
  • Customer Behavior Segmentation Analysis

While the centricity of business strategy may ebb and flow with time, the rapid escalation of data availability in recent decades has driven a shift in focus toward customers that is likely permanent. Success in the current environment is increasingly dependent on the strategic and contextual relevance of customer management strategies, both of which depend on a highly granular characterization and utilization of customer value.

In this course, you will explore customer centricity from a holistic perspective, reviewing and aligning various strategies to consolidate your approach to customer management. You will go from identifying and contextualizing value derivation as it pertains to customer portfolios to developing and applying a comprehensive framework to efficiently diagnose, predict, and resolve potential obstacles to customer lifetime value for a real-world business in the course project. Along the way, you will review tactics for the acquisition, retention, and development of customers, aligning their deployment with value considerations and predictions to achieve overarching business goals and drive profitable growth.

The following courses are required to be completed before taking this course:

  • Leveraging Customers for Growth
  • A/B Testing and Analytics
  • Customer Behavior Segmentation Analysis
  • Predicting Customer Response

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