Three Separate Documents Are Required For This Assignment

Three Separate Documents Are Required For This Assignmentsubmit1 3

Three separate documents are required for this assignment: Submit: (1) 300 word Executive Overview (2) Individual Presentation (in PowerPoint format) (3) Speaker's notes in APA format with citations and references. The tasks include summarizing the generic components of an analytics plan and creating a proposed approach specific to a given scenario involving Yore Blends, an online company concerned about customer churn.

Part One: Summarize the generic components of an analytics plan that includes (a) discovery/business problem framed, (b) initial hypotheses, (c) data and scope, (d) model planning and analytic technique, (e) result and key findings, and (f) business impact.

Part Two: Create a proposed approach to an analytics plan specific to the given scenario. Include each area of an analytics plan but tailor it to the scenario, proposing an analytical method with rationale. Enhance your work with a visualization. You do not need to provide actual analytics or solutions, only the proposed approach. Where information is missing, make reasonable assumptions.

Scenario: Yore Blends (YB) is a fictional online company selling subscription spice blends and related products. They aim to grow via mergers and acquisitions, requiring a strong customer base and revenue. Currently, they are concerned about customer churn after several months of service, with a goal to reduce customer attrition by 16% based on analyzing customer account data from the past 24 months.

Paper For Above instruction

Introduction

Customer churn is a critical challenge for subscription-based businesses like Yore Blends (YB), impacting revenue growth and long-term sustainability. An effective analytics plan can provide insights into customer behavior, allowing the company to identify at-risk customers and implement targeted retention strategies. This paper summarizes the essential components of a generic analytics plan and proposes a tailored analytical approach for YB to reduce customer churn based on their specific context and available data.

Part One: Components of an Analytics Plan

Discovery/Business Problem Framed

The primary business problem is customer attrition occurring after several months of service. YB must understand the factors influencing churn and develop strategies to retain customers, thereby increasing lifetime value and revenue stability.

Initial Hypotheses

Potential hypotheses include: Customers who receive personalized engagement are less likely to churn; customers with higher engagement with complementary products are more loyal; and customers whose subscription renewal is close to expiration are at higher risk of leaving.

Data and Scope

The data encompasses customer account information collected over the past 24 months, including purchase history, engagement metrics, demographic data, and product preferences. The scope is limited to analyzing patterns leading to churn within this period, focusing on current and at-risk customers.

Model Planning and Analytic Technique

A predictive model, such as logistic regression or machine learning classifiers like random forests, will be planned to identify customers at risk of churn. These methods are chosen for their ability to handle multiple variables and provide interpretable insights into the factors influencing churn.

Results and Key Findings

The model is anticipated to reveal key predictors of churn, such as decreased purchase frequency, low engagement scores, or demographic factors. These insights enable targeted retention efforts, such as personalized offers or engagement campaigns.

Business Impact

Implementing the analytics plan can lead to a reduction in churn rate by approximately 16%, improving revenue predictability, customer lifetime value, and providing strategic advantages for growth and acquisitions.

Part Two: Proposed Analytics Approach for Yore Blends

The proposed approach involves a customer segmentation analysis combined with predictive modeling. Segmentation, using clustering techniques like K-means, will identify distinct customer groups based on purchasing and engagement behaviors. This classification helps tailor retention strategies to different segments, improving effectiveness.

For predictive modeling, a random forest classifier is recommended due to its robustness and ability to handle nonlinear relationships. This model will incorporate variables such as purchase frequency, recency, engagement levels, and product preferences to predict churn risk with high accuracy.

A visualization such as a customer journey map or a risk stratification dashboard will support stakeholders in monitoring customer status and implementing timely interventions. Assumptions include consistent data collection and accurate capture of engagement metrics.

Conclusion

By systematically applying these analytical techniques, Yore Blends can proactively identify at-risk customers and implement tailored retention strategies. The integration of segmentation and predictive models, supported by visual dashboards, will facilitate data-driven decision-making, ultimately reducing churn by targeted efforts.

References

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• Verhoef, P. C., et al. (2010). Customer engagement as a new perspective on customer management. Journal of Service Research, 13(3), 247-262.
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• Zhao, Y., et al. (2020). Visual analytics for customer churn prediction: A survey and future directions. IEEE Transactions on Services Computing, 13(1), 87-100.