Marketing Campaign Optimization

Flashcards summarizing key concepts from the lecture on optimizing marketing campaigns.

Business Understanding

The process of identifying the objective to increase sales through targeted marketing campaigns.

Data Collection

Gathering data from past marketing campaigns, sales records, customer demographics, and purchasing behavior.

Exploratory Data Analysis (EDA)

Analyzing data to identify trends, such as customer demographics that have historically made the most purchases.

Cleaning Data

Removing records with missing demographic information or unclear sales outcomes.

Feature Selection

Choosing relevant features for analysis, such as age, gender, and past purchase history.

Data Transformation

Normalizing the data to ensure variables are appropriately scaled for analysis.

Model Selection

Choosing predictive models to test, like logistic regression and clustering algorithms.

Training and Testing

Splitting data into training and testing sets to evaluate model performance.

Performance Metrics

Methods to evaluate models using accuracy, precision, recall, and AUC-ROC curves.

Business Impact Assessment

Assessing if the selected model meets the business objective and its potential impact on sales.

Deployment Strategy

Implementing the model by creating targeted marketing lists based on predictions.

Monitoring and Maintenance

Tracking campaign performance and adjusting the model based on new data.

Simulating Deployment

Selecting a target group based on model predictions for marketing campaigns.