Analytics Glossary

In this section we have provided a number of the key terms that you might come across on our website and also when considering our work. We have made them as easy to understand by providing an explanation of how they are used.

Analytics

Analytics, in its simplest terms, is looking at data and creating meaningful insight, or understanding. It is used, primarily by businesses - either themselves or using a third party or partner company…

Churn / Attrition and Retention / Loyalty Models

Churn and retention are major applications of data mining. Churn tends to be employed as a term because it refers to all types of customer attrition – voluntary or involuntary…

Clustering

Clustering is the task of segmenting a heterogeneous population into a number of homogeneous subgroups or clusters. Clustering does not rely on pre-defined classes…

Customer Analytics

Customer analytics is a process by which data from customer behaviour is aggregated and analysed to gain customer insight...

Customer Life-Cycle Analysis

Understanding the changes that customers, as people, undergo in their life helps companies to communicate with them and provide them with the products/services they are most likely to be interested in…

Customer Segmentation

Customer segmentation is a popular application of data mining when working with an established customer base…

Customer Value Models

A customer value model establishes what the value of a customer has been to an organisation using transactional data…

Data Analysis

Data analysis is a process of gathering, modelling, and transforming data with the goal of highlighting useful information...

Data Mining

Data mining is the process of extracting patterns from data sets. Its aim is to establish relationships where none had been identified previously.

Data Segmentation

Data segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing...

Decision Tees

Decision trees (sometimes known as CHAID analysis) are a popular means of data classification and prediction. Decision tress represent rules and are therefore easily understandable…

Market Analysis

Before undertaking market analysis, as with all analysis, it is important to be clear about what the expected outcomes are and what information specifically is being analysed.

Market Basket Analysis

Market basket analysis uses the information about what a customer purchases to provide insight into who they are and why they make certain purchases…

Predictive Modelling

Predictive modelling can help enhance customer communications, increase retention and improve returns for virtually any business...

Profiling

Profiling is a simple means of describing what is happening in a complex database in a way that increases our understanding...

Recency, Frequency, Value (RFV) Analysis

RFV analysis looks at the transactional behaviour of a customer and establishes levels of interaction according to how frequently, when and how much a customer has spent with a company…

Response Analysis and Models

Direct marketing campaigns use response models to improve response rates. They do this by identifying prospects who are more likely to respond to a direct solicitation - whatever the channel …