Customer segmentation involves defining customer segments and assessing behaviours by tapping into external market research and analysing existing business insights to ensure a deeper understanding of all aspects of your existing and target customers. Intricately understanding customer segments, and their related behaviours and needs, will enable your business to optimise current business offerings and inform strategic business decisions such new client targeting and acquisition strategies.
Fuel growth through Customer Segmentation
Customer Segmentation equips your management team with the ability to holistically understand your business’s customer base and establishes a foundation
for analysing existing offerings and informing strategic business decisions, such as expansion into new products, channels and markets.
There are two varying approaches to Customer Segmentation:
PUBLICLY AVAILABLE MARKET DATA
Segmentation based on publicly available market data focuses on the industry in which your business operates and seeks to create or refine distinct clusters within the market. This analysis is based on indicated characteristics, needs and behaviours for the products or solutions being offered.
Propensity modelling is a method of sizing and prioritising a target market by integrating data from various divisions within your business, across the existing customer base. This segmentation approach helps to identify customer behaviours that are key drivers for your business over the determined period.
Both approaches are extremely valuable, especially when conducted in tandem. Since segmentation assists in the identification of how to acquire, retain and grow certain groups of customers at a detailed level, it is informed by behavioural and product data analytics.
By tapping into Step Advisory’s insightful analysis you and your business will gain a focused single view of your customer and a deeper understanding of their characteristics and behaviour. This information is often difficult to discern through an analysis of company data, but we shine a light on the gems hidden in these datasets by applying an efficient process that unearths value from complex data relationships.