WatchingFour Videos
Downloadingthe Marketing Campaign datasets
Next,
Before working on the business case asks yourself (and write down the answers) to the following questions:
What Business Problem you are trying to solve?
Why solving this problem is important?
How did you solve this problem?
Why would I consider your solution?
Objectives
The goal of this study is to create a customer response model based on past responses to targeted marketing campaigns, in order to predict those customers that are likely to respond to and increase the exchange rate of new campaigns.
1.Step 1:Load and prepare data from past marketing campaigns, including recipient attributes (e.g. age, gender, and behavioral attributes such as the usage of products and services, website, etc).
2.Step 2:Determine which factors influence the response to market campaigns to improve prediction.
3.Step 3:Train and score the customer response model. You need to find the best model.
4.Step 4:Load data containing potential recipients for new campaigns. Apply the customer response model to identify and target those recipients that are the most likely to respond to the marketing the campaign in the desired way.
5. Outputs
ROC Comparisonbetween all models you used
Keep tuning these modelsto get a betterPrecision? Recall?
LIFT CHART:Create a lift chart to evaluate the ability to identify groups with a higher probability to respond to this marketing campaign.
Consider using aCross-validation operator.
Instructions.docx
3.Predict2HeartAttack_Scoring.xlsx
3Predict2HeartAttack__Training.xlsx
4.Past_Direct_Marketing.xlsx
1.ToExplainorPredict.pdf
4ModelEval-BookChapter.pdf
3.Howtoevaluateyourmodel.docx
3.LogisticRegressionExercise1.docx
SampleAssigment.pdf
4ModelEvaluation.pptx
