CWA15 - Merkle Guest Lecture

docx

School

Howard University *

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Course

315

Subject

Marketing

Date

Feb 20, 2024

Type

docx

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Uploaded by SuperBaboonPerson1014

Marketing Research CWA15 - Merkle Guest Speaker 2-3 Paragraphs - What you learned from the lecture that has improved your understanding about marketing research and predictive analysis in the real world. During the Merkle guest lecture on Monday, we were informed and educated about the marketing industry and how to successfully step into the environment. I learned that at Merkle, an Analytic Director manages hundreds of predictive model builds including leading predictive analytics engagements across high tech, financial services, automotive, and entertainment clients, as well as internal modeling for their data product and data source. A predictive model is a mathematical algorithm that predicts future behavior based on observed behaviors. They also engage in target models which are used to improve marketing performance by targeting those most likely to exhibit the desired behavior such as responses and purchasing more often. A key point that stuck with me but was already understood was that “Data Preparation is Key!” When analyzing data, it is essential to consider the level of the data. Is it residential, individual, email ID, website ID, or something else? It is also important to understand the different types of model applications. A model application is a model built to find a similar looking population from a base comparison universe to your population of interest. They are commonly used if actual campaign files are not available. There are three types of model applications: response, conversion, and net conversion models. A response model predicts the likelihood that a prospect will respond to a future campaign. A conversion model predicts the conditional likelihood that a prospect will convert to a customer, buyer, donor given they responded. FInally, the net conversion model directly predicts the net likelihood that a prospect will convert to a customer, buyer or donor. These few key points have significantly improved my understanding of marketing research. It has provided insight into the different types of model applications and how to potentially use them. It has thoroughly explained predictive modeling and how they are beneficial to marketing professionals.

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