Customer segmentation

Articles tagged Customer segmentation

A quick guide to the RFM model for data scientists

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...

A quick guide to customer segmentation for B2B e-commerce

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...

How to analyse Google Analytics demographics and interests with GAPandas

The demographics and interests data provided in Google Analytics can be a useful way to understand who is visiting your site or purchasing your products, without the need to perform...

A quick guide to lead scoring for B2B e-commerce sites

Lead scoring is a Customer Relationship Management (CRM) process that involves segmenting CRM contacts based on their likelihood to make a purchase. Lead scoring is applied to both existing customers...

A quick guide to customer segmentation for data scientists

Customer segmentation is the process of using data science techniques to create discrete groups of customers which share common characteristics or attributes. For example, a company might segment customers into...

How to segment your customers using EcommerceTools

Customer segmentation can give you huge insights into your business and identify a whole range of different things about your customers, allowing you to change your marketing and improve results....

How to use k means clustering for customer segmentation

K means is one of the most widely used algorithms for clustering data and falls into the unsupervised learning group of machine learning models. It’s ideal for many forms of...

How to segment customers using RFM and ABC

While the Recency, Frequency, Monetary value or RFM model for customer segmentation might be old, it’s based on sound science, so no matter what customer model you’re building, it’s generally...

How to perform a customer cohort analysis in Pandas

Cohort analysis is unlike most other customer segmentation techniques in that it typically uses a time-based element. It’s typically used to segment customers into groups, or cohorts, based on their...

How to calculate CLV using BG/NBD and Gamma-Gamma

Calculating Customer Lifetime Value or CLV is considered a really important thing in marketing and ecommerce, yet most companies can’t do it properly. This clever metric tells you the predicted...

How to assign RFM scores with quantile-based discretization

RFM segmentation is one of the oldest and most effective ways to segment customers. RFM models are based on three simple values - recency, frequency, and monetary value - which...

How to engineer customer purchase latency features

Purchase latency or customer latency is a measure of the number of days between a customer’s orders and is one of the most powerful features in many propensity and churn...

How to create targeted B2B company sector datasets

As I explained in my previous post, many B2B ecommerce businesses spend huge amounts on procuring third-party data for companies they wish to target. However, with some data science skills...

How to create a dataset containing all UK companies

In B2B ecommerce, there are two main approaches to new customer acquisition: you either rely on your website to acquire customers for you, or you target specific customers through sales...

How to bin or bucket customer data using Pandas

Data binning, bucketing, or discrete binning, is a very useful technique for both preprocessing and understanding or visualising complex data, especially during the customer segmentation process. It’s applied to continuous...