Customer segmentation

We are not all the same and neither are our customers! So it should come as no surprise that customer segmentation is key to ensuring you market successfully to your customers; right message at the right time. At the heart of direct marketing is data analysis, customer insight and segmentation. Using this valuable resource ensures you send appropriate propositions to the right customers segments. Sometimes organisations think they need to buy in external lifestyle or business demographics in order to better understand their customers. Whilst there may be benefits from these data resources, the value of in-house data should not be overlooked. 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 3
• 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 000 (lowest worth).

Managing direct marketing performance

Not only are customer 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.

Campaign examples:

• Are all high value customers regular clients? What was the effect of the campaign to encourage more orders?
• Are frequent low value purchasers harming your margin? What was the effect of encouraging less but bigger orders?
• Running a campaign to encourage "One time only" customers to shop again? Did it have the desired effect?
• Did the customer discounting policy encourage more frequent shopping? How did this effect the overall value of customers?

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.

Free guide to customer segmentation

Customers expect suppliers to know who they are, what and when they buy. This information provides the basis for understanding customer purchasing behaviours. Used effectively, successful retention strategies can be developed to influence future purchases.

• Are you seeking ways to segment your customers?
• Are you differentiating your customer propositions?

This guide describes our proven system for segmenting customers.

View our free guide to customer segmentation