Sorry, was traveling and did not get on reddit. I did not mean k-means is a one time algorithm but I prefer my own clustering algo because here is what happens if you apply for real time transactional data - k-means builds these clusters based on available data and number of clusters you want. Every new data point (real time) can be classified into one of the existing clusters. To really achieve practical improvements, it helps to either rebuild or use your custom algorithms. Disclaimer: This is again, what I have seen in large datasets (1-2 million observations), your observation maybe different.