ANLY FPX 5510 Assessment 4 Presenting Advanced Analytics to Executives

Student Name

Capella University

ANLY-FPX 5510 Advanced Business Analytics

Prof. Name

Date

Introduction

The marketing department of a large financial organization recently faced a budget reduction. As a result, the department sought assistance from the analytics team to optimize the available budget by avoiding unnecessary contact with repeat customers who may not have an interest in the company’s services. To achieve this goal, data-driven methods were employed to ensure the efficient allocation of resources and prevent wasteful spending on ineffective marketing channels.

Cluster Analysis

One of the primary solutions involved conducting a cluster analysis using data that detailed how customers were targeted through various communication channels, such as telephone, email, Facebook, Twitter, Instagram, Pinterest, Yahoo, Google search, and U.S. Postal Service mail. This analysis aimed to group customers based on their behaviors and preferences, which would help reduce the number of marketing channels in use. By understanding customer preferences for communication, the organization could prioritize the most effective platforms. The analysis recommended continuing marketing efforts through telephone, mail, and Google while discontinuing other channels, thereby optimizing the budget and improving targeting accuracy.

Decision Tree Analysis

Another approach involved a decision tree analysis, which, like the cluster analysis, examined the same set of customer data from various communication channels. However, this analysis also incorporated demographic data and information on total deposits made by each customer in the previous year. The objective was to identify the characteristics of high-deposit customers, enabling the marketing team to focus on this profitable segment. Findings from the decision tree analysis suggested that marketing via Instagram should be maintained for customers under 43 years old. On the other hand, customers aged 56 to 80 should not be targeted as they had lower deposit amounts in the previous year, thus making them a less desirable group for the organization’s marketing efforts.

Recommended Solution

Of the two solutions, the first option, cluster analysis, is recommended to address the business problem. Cluster analysis focuses on optimizing communication channels based on customer preferences, providing the company with insights into which advertising platforms—such as telephone, email, Facebook, Twitter, Instagram, Pinterest, Yahoo, Google search, and U.S. Postal Service mail—are most effective. This approach is cost-effective and saves the company money by identifying inefficient channels that can be eliminated. While the decision tree analysis centers on excluding certain age groups from advertising campaigns, cluster sampling offers a broader, more flexible approach by grouping customers based on their behavior rather than specific demographic characteristics. This makes it easier to manage large sample sizes and gather relevant information efficiently (Money, 2019).

Implementation

The implementation of cluster analysis within the organization will not be a one-time event but rather an ongoing process as the company evolves. Analytics-driven insights will become crucial in meeting the changing demands of customers, products, and operations. The process will begin with a centralized approach where all relevant assets—software, hardware, skilled personnel, metadata, and project management capabilities—are managed by a single department. This ensures knowledge sharing, consistency in execution, and cost reductions due to shared resources (Sheikh, 2013). Initially, the focus will be on introducing the cluster analysis process and data to the team, followed by extensive training. Afterward, the necessary project management, engagement, and development frameworks will be established before moving on to real projects that deliver measurable results. Continuous monitoring will be essential to ensure the effectiveness of the cluster analysis.

Benefits

The proposed solution emphasizes the importance of reducing unnecessary communication by identifying customer-preferred communication methods. Key factors in selecting appropriate advertising channels include the target audience, the product or service, and associated costs. A fundamental principle of advertising is the elimination of waste, which means choosing media that reach the highest percentage of potential customers. Allocating resources to a broader audience that may not be interested in the product is counterproductive. Reducing excess advertising efforts saves money by focusing on communication methods that effectively reach interested customers. Poor advertising choices can deplete the company’s reduced budget and drain valuable resources, so making informed decisions helps the organization stay financially efficient (The Inc., 2018).

References

Money Matters (2019). Cluster sampling | Definition | Advantages & Disadvantages. Retrieved from https://accountlearning.com/cluster-sampling-definition-advantages-disadvantages/

Sheikh, N. (2013). Implementing analytics: A blueprint for design, development, and adoption. Waltham, MA: Morgan Kaufmann.

ANLY FPX 5510 Assessment 4 Presenting Advanced Analytics to Executives

The Inc. (2018). Advertising Budget: Tips on budgeting and negotiating, plus promotional tools for advertising. Retrieved from https://www.inc.com/encyclopedia/advertising-budget.html