There are two main ways you can grow the customer base of a business: you can either acquire more customers by increasing your customer acquisition rate, or you can improve...
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...
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...
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...
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...
Product attributes, such as size, weight, wattage, or colour, are critical in ecommerce as they help customers find and select the right product for their needs. However, obtaining, adding, and...
A Next-Product-To-Buy (or NPTB) model is designed to help retailers and marketers improve the effectiveness of cross-selling product recommendations by predicting the product each customer would be most likely to...
Machine learning (ML) is a branch of artificial intelligence (AI) in which models are created to predict an outcome by learning from patterns present in data. They can automatically improve...
Uplift modeling is a machine learning technique used in marketing and ecommerce to predict which customers are likely to respond to a particular marketing campaign. However, rather than simply predicting...
On-site search in ecommerce has improved massively in recent years, thanks to search systems such as Lucene, Solr, Algolia, and Elastic. Despite on-site search generating massive amounts of revenue for...
