ANLY FPX 5510 Assessment 3 Comparison of Analytic Methods

Student Name

Capella University

ANLY-FPX 5510 Advanced Business Analytics

Prof. Name

Date

Marketing Budget Optimization

The marketing department of a large financial services organization recently experienced a budget reduction and is seeking assistance from the analytics department to maximize the use of their remaining budget. Specifically, the company wants to avoid repeatedly contacting potential customers who are not interested in opening an account, as this results in wasted time and money. The organization has tasked the analytics department with resolving this issue.

Comparison of Analytic Methods

In response, the analytics team has proposed two potential solutions to optimize marketing efforts. The first option involves conducting a cluster analysis, which focuses on understanding how advertisements are being utilized across various channels. These channels include the U.S. Postal Service, telephone, email, Facebook, Twitter, Yahoo, Instagram, and Google search. Cluster analysis identifies customer groups with similar behavior patterns, thereby enabling the organization to reduce the number of channels used for marketing. The analysis revealed that advertisements should continue through mail, Google, and phone while discontinuing all other channels.

The second option is a decision tree analysis. Similar to the cluster analysis, this method examines how customers are being reached via various channels (mail, telephone, email, Facebook, Twitter, Yahoo, and Google). Additionally, the decision tree analysis takes into account demographic data and total customer deposits from the previous year. The goal is to identify high-deposit customers and target them more effectively. This analysis recommended continuing Instagram marketing for customers aged 43, while advising against marketing to customers aged 56 to 80 due to their lower likelihood of making high deposits.

Evaluated Appropriateness of Analytic Methods

Cluster analysis is a technique used to group similar cases or objects into clusters. It can be helpful in identifying specific groups of buyers and determining the best way to market to them. The process involves defining the problem, selecting a measurement, applying a clustering procedure, determining the number of clusters, and assessing the results (Statistics Solutions, 2019). In this case, cluster analysis is appropriate as it identifies customer behavior patterns and tailors marketing efforts accordingly.

On the other hand, decision tree analysis offers a graphical representation of different possible solutions to a problem. This method helps management predict outcomes based on various decisions and is particularly useful for making data-driven choices (P., 2019). In the context of this financial services company, the decision tree effectively identifies high-deposit customers, allowing for targeted advertising. As a result, marketing on Instagram is recommended for high-profile customers, while older generations are excluded from targeted efforts.

Recommended Solution

Based on the data provided, I recommend implementing the cluster analysis. This method focuses on identifying the most effective communication channels while minimizing costs. By analyzing marketing channels such as the U.S. Postal Service, Twitter, Yahoo, Google, Facebook, email, and Instagram, cluster analysis determines which channels reach the intended audience at a lower cost. Additionally, this method is cost-effective, as it allows the company to gather data from randomly selected units, thus saving resources while ensuring accurate targeting.

Proposed Plan for Implementation

Implementing analytics is an ongoing process that can help the organization innovate and tailor its services to customer needs. To successfully implement the results from the cluster analysis and decision tree analysis, a centralized approach is recommended. This approach should integrate software, hardware, business relationships, skilled resources, and project management under one umbrella. Though this may seem like a large investment, it will bring several benefits, including shared knowledge, consistency, visibility, and streamlined communication. Shared software and communication tools will also save the company money.

The first step in the implementation plan is to introduce the process and train the team on the methods of cluster analysis. Following this, project management and development teams should engage to establish a framework before real projects begin (Sheikh, 2013). Finally, it is essential to implement the data and processes while continuously monitoring the effectiveness of the cluster analysis to ensure long-term success.

References

P., M. (2019). Decision Tree Analysis. Retrieved from https://www.toolshero.com/decisionmaking/decision-tree-analysis/

Sheikh, N. (2013). Implementing Analytics: A Blueprint for Design, Development, and Adoption. Waltham, MA.

ANLY FPX 5510 Assessment 3 Comparison of Analytic Methods

Statistics Solutions. (2019). Conduct and Interpret a Cluster Analysis. Retrieved from https://www.statisticsolutions.com/cluster-analysis-2/