Publications by Jack Han
Data Analysis for Marketing Research with R Language (1)
Data Analysis technologies such as t-test, ANOVA, regression, conjoint analysis, and factor analysis are widely used in the marketing research areas of A/B Testing, consumer preference analysis, market segmentation, product pricing, sales driver analysis, and sales forecast etc. Traditionally the analysis tools are mainly SPSS and SAS, however, t...
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Investment Portfolio Analysis with R Language
[Please note that this article is for studying R programming purpose only rather than for advices of investment] R has a wide application in finance analysis areas such as time series analysis, portfolio management, and risk management, with its basic functions and many professional packages in Finance. In this article, we will demonstrate how to...
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Uncertain Demand Forecasting and Inventory Optimizing for Short-life-cycle Products
For short-life-cycle products such as newspapers and fashion, it is important to match the supply with the demand. However, sometimes we order too little from supplier and sometimes we order too much due to the uncertain demand. We would lose sales and customers would be unsatisfied if ordering too little or we would let the inventory left over a...
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RFM Customer Analysis with R Language
For database marketing or direct marketing people, they are always concerned about two questions before they send out mails or make calls to their customers:- How can they segment the customers in the database to find out who are more likely to response to their mails or buy their products? Which type of customers they should send the mails to s...
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Identifying Potential Customers with Classification Techniques in R Language
Data mining techniques and algorithms such as Decision Tree, Naïve Bayes, Support Vector Machine, Random Forest, and Logistic Regression are “most commonly used for predicting a specific outcome such as response / no-response, high / medium / low-value customer, likely to buy / not buy.”1 In this article, we will demonstrate how to use R to ...
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Increasing Repeat Purchase Rate by Analyzing Customer Latency
For online businesses, Repeat Purchase Rate is one of the critical metrics of the business performance. Higher repeat purchase rate means more active members, and thus leads to higher profit. “Customer Latency refers to the average time between customer activity events, for example, making a purchase, calling the help desk, or visiting a web si...
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Calculating Customer Lifetime Value with Recency, Frequency, and Monetary (RFM)
Introducing Customer Lifetime Value (CLV) Customer Lifetime Value is “the present value of the future cash flows attributed to the customer during his/her entire relationship with the company.”1 There are different kinds of formulas, from simplified to advanced, to calculate CLV. But the following one might be the one being used most common...
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