For a campaign to succeed, you need a comprehensive understanding of your customers. Caroline Kimber, head of data planning at Stephens Francis Whitson, helps you define your target audience with precision.

Setting objectives

A medium as precise and measurable as direct mail demands that you set correspondingly precise and measurable objectives.

Tip When producing analysis to define your target market, ask yourself the following:

Which customers do I need to know about?

Be specific. If your campaign is to acquire new customers for Brand Y using a 20%-off offer via direct mail, analyse this sub-segment of customers, not all customers

What information do I need to learn about them or their behaviour and over which time period?

Detail exactly what information you need, for example, demographics, lifestyle, media consumption patterns, purchasing patterns over time, response rates…

Against which base should this information be compared?

A base of all adults or households in GB is typically used, but your customer profile may be very skewed so it may be more appropriate to compare your target segment against for example, all females or all customers as a whole.

How will you apply and use this insight?

Ensure that the output of the analysis suits the application to which it will be put. For example, if you need the analysis to optimise the targeting for a direct mail campaign, the best output is probably a mathematical propensity model. Conversely, if you're using the information to shape a creative message, bar charts will be more useful.

Formulate your objective by pulling together detailed answers from the above questions. You may need to modify this objective further to ensure it passes the SMART test:

S – Specific
M – Measurable
A – Action-oriented
R – Realistic
T – Time-boxed

Tip Define your target customers at an appropriate level of granularity. Be specific, but be realistic too – a tightly defined segment that is too small will not yield statistically significant results.

Variables

Having defined your objectives, the next stage is to decide which variables to profile on to help you understand your customers or prospects.

Here are some of the most commonly used variables:

Demographic

• Age, gender, marital status, social grade, geo-demographic code, lifestage, area lived in, SIC code, size of business and income.

Transactional

• Number of orders, value of orders, date of orders, category of purchase, channel, payment method, offer type and multiple purchase.

Campaign

• Type of campaign or offer responded to - cold /warm, channel, timing and so on.

Lifestyle

• Interests, hobbies, purchasing patterns and competitive products bought.

Attitudes

• Green issues, online usage, satisfaction and loyalty.

It's an overwhelming choice of variables, so it's crucial that you understand objectives and applications. After all, a comprehensive view of your customers is invaluable, but you could end up with so much information that you are unable to see the bigger picture.

Tip Always focus on the information that is specifically required to achieve your direct mail or campaign objectives.

Profiling methods

Once you have defined your objectives and selected the variables, how do you view the results? Here are some of the common options:

Cross-tabulation reports

These reports compare one variable with another. Examples could include product type by age or SIC code by channel. They are a simple and easy way of understanding your customers, but are quite one-dimensional as they don’t take all customer characteristics into account.

Commercial profiling reports

These reports are typically produced by data owners and lifestyle companies and compare your customers to a national base. Your customers are ranked and index and z scores produced to illustrate which variables are significant.

The reports are comprehensive, covering all or many of the variables outlined in Cleaning your data. They can be produced for the whole customer base or for sub-segments of it – for example, lapsed customers, internet only purchasers or direct mail responders. One additional benefit of commercial profiling is that the results of the analysis can be used to select lookalike prospects from the lifestyle organisation’s database.

Recency, frequency and monetary value (RFV or RFM) analysis

RFV or RFM analysis is simple and effective and tends to be used extensively in sectors like mail order. It enables you to understand the most valuable customers and put in place strategies for developing newer and less valuable customers.

Segmentation

This technique clusters together similar sorts of customers according to their personal characteristics and purchasing patterns.

Tip When selecting a profiling method, think about your audience and the application to which the analysis will be put. A technical audience will appreciate z scores, while a marketing audience will prefer simple, visual insights.

Tip Similarly, it’s overkill to go through an extensive segmentation of different customers and channels if your analysis results are to be applied to a mass market campaign, for example, identifying postal sectors for a door-drop.

And finally...

An old idiom states that there are many ways to skin a cat. Understanding and defining your target market is direct mail’s version of the cat-skinning conundrum.

If you focus carefully on the key information you need and how you intend to apply the results of the analysis, you will have an ideal starting point to plan your campaign. And once you've done that, it's time to move on to the next stages... making sure your audience is out there by checking all their contact details.