Free guide to customer segmentation

Customer segmentation is at the heart of direct marketing. It is key to ensuring you market successfully to your customers; right message at the right time.

This guide is designed to help you build customer segmentation.

Audit and appraise your sales data

Review your sales data, auditing its content to establish is currency and value. The goal is to understand how customer orders are managed:

• How robust is the data? What business rules were applied at data entry?
• Are there duplicate customers? If so, some orders may be recorded against different customer records.
• Focusing on customer related data - where are the customers and orders?
• If customer details and sales orders are stored in separate systems, what keys could be used to join them together?
• Are fields consistently populated and where not, which have missing values?

Against each element of data, highlight any issues concerning data quality or integrity that may affect the use of the data for marketing or analytical purposes.

Data analysis

We find that many organisations focus segmentation on locations. When dealing with businesses, they may use establishment type, Thompson's or standard industry coded (SIC).

In isolation, these don't provide much insight into what makes a customer different when compared to another.

When combined with a measure of customer performance they become far more revealing.

The classic method for measuring customer performance is to score each customer based on recency, frequency and value (RFV). This is sometimes called RFM, where 'M' is for monetary value.

• How recent was the last order placed by this customer - Recency
• How many times has a customer ordered on average within the last ‘n’ months - Frequency
• What is their average order margin for the period - Value

How to score customers

For each customer run enquiries on your database to identify:

• Date of first and last order
• Number of orders
• Total gross margin (or other value such as sales - take cost into consideration)

From these calculate:

• RECENCY: Time since last order is current date minus date of last order (Days)
• FREQUENCY: Duration of custom: current date minus date of first order (Days) divided by number of orders
• VALUE: Total gross margin divided by number of orders

These give you absolute values for each customer, the next stage is to categorise these into segments. Identify ranges of values and then apply a corresponding score to each customer.

Taking each element in turn, the objective is to achieve categories that have broadly speaking similar numbers of customers in each. The number of categories will vary depending on your business.

For example a company selling office supplies might have:

RECENCY:

• 1 to 90 days - score 3
• 91 to 180 days - score 2
• 181 to 365 days - score 1
• Greater than 365 days - score 0

FREQUENCY:

• At least once per month - score 3
• At least once in two to three months - score 2
• At least once in four to six months - score 1
• Once time only purchase - score 0

VALUE :

Clearly this depends on the business in question. If Gross margin is not readily identifiable, then the sales value could be used, but consideration should be given to the distribution of margin across the products your organisation sells.

Assuming a similar ranges of scores are applied for value then your best customers would be those with scores of 333 (highest worth) down to 111 (lowest worth).

Managing direct marketing performance

Not only are customers different from each other, they also change their buying habits. It is best to develop an on-going scoring process to manage the effect of direct marketing.

Building customer segmentation with a time dimension provides customer insight and in-depth campaign analysis.

The diagram below shows customer changes between two periods. High worth customers in period 'A', lost from 333 less valuable segments: 332 and 331. Similarly, it demonstrates lower value customers 331 increasing to higher scores 332 and 333.

Considerations before implementation

Before implementing customer segmentation consider how will the results will be used:

• How robust are the customer records?
• How will the segmentation be used?
• What information will be needed for campaigns?

Taking action

We have found customer segmentation to be an invaluable tool to provide customer insight. These steps can make all the difference to the projects success.

Would you like some help with your project? If that's a yes, we are just a email or phone call away (contact details top right of this page).

Wishing you success in your project.