The RFM model is probably one of the best known and most widely used customer segmentation models by data driven marketers. It’s used for both measuring customer value and predicting...
One of the problems with search engine optimisation or SEO is that search engine algorithms are essentially black boxes. They analyse so many on-page and off-page factors, and use multiple...
After work, when I’m not learning about data science, practising data science, or writing about data science, I like to browse classic car auction sites looking for cars I can’t...
A growing proportion of what we buy regularly is purchased via a subscription, or some other kind of contract. Most people have contracts for their internet, mobile phone, car insurance,...
One issue with the more sophisticated algorithms, such as Extreme Gradient Boosting, is that they can overfit to the data. This basically means that the model picks up the idiosyncrasies...
Customer segmentation, and the similar and related field of market segmentation, are particularly relevant to the field of business-to-business (B2B) e-commerce. B2B customers often have a higher Customer Lifetime Value...
There are some great anomaly detection models available for Python, which let you examine complex data for a wide range of different anomaly types. In this project, I’ll show you...
In ecommerce, customer service staff are often among the busiest people in the organisation, handling hundreds of tasks every day, often simultaneously. However, CS managers often get so bogged down...
There’s often a great deal of repetition in machine learning projects. A typical machine learning workflow involves a number of common processes designed to clean, prepare, and transform data, so...
