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Modeling and forecasting

RFM Segmentation - Introduction Slides

RFM Segmentation – Introduction Slides

RFM Segmentation from Kamil Bartocha RFM Segmentation is the easiest and most frequently used form of database segmentation. It is based on three key metrics: Recency, Frequency and Monetary Value of customer activity. RFM is often used with transactional history in e-commerce, but can also work for Social Media interactions, online gaming or discussion boards. […]

Linear Regression vs Logistic Regression vs Poisson Regression

Linear Regression vs Logistic Regression vs Poisson Regression

Generalized Linear Models (GLMs) extend the ordinary Linear Regression and allow the response variable y to have an error distribution other than the normal distribution. GLMs are great because: They are easy to understand. Most statistical packages contain functions to fit and interpret the resulting model. Linear regression or logistic regression is sufficient for a lot […]

impulse response function

Modelling responses to market shocks

One of the frequently asked questions by marketers is what shall we expect from any market turbulences. This can be an increase in competitors’ spend on advertising, beginning of pricing war or any outlier of current market conditions. Let us address this issue on an example of a competitors high discount price using impulse response […]

Bayesian Modeling of Click-through Rate for Small Data

Bayesian Modeling of Click-through Rate for Small Data

After a long break we get back to the topic of Small Data problems (read the original article HERE). This time we evaluate a modelling framework for metrics like Click-through Rate and Conversion Rate. In most business scenarios these are estimated with a fraction of Clicks to Impressions and Orders to Visitors. Most reporting suites […]