How to Segment Your Direct Mail Database to Achieve Better Response Rate / Engagement

There are a lot of levers that need to be kept in mind when it comes to successful direct mail marketing campaigns. But few are more instrumental than making sure that you've effectively segmented your database.

Making sure you correctly segment your database of customers is something that, in principle, sounds simple. But in actuality, it requires some strategic thinking and work to ensure you send the right direct mail communications to the right customers.

With a variety of ways and methods that can be employed to properly segment your direct mail database, it's important to consider them all. Then, make a decision based on the merits of each method and how they will best suit your market segments.

We're going to take a look at direct mail database segmentation and explore the different ways it can be done to achieve better business results, as compared to, not segmenting the data.

Introduction

Direct mail is, and will remain, one of the most effective means of driving conversion. Now that it competes with the new email, social, and web data targeting, customer database segmentation is now more important than ever.

All the customers that you have in your direct mail database will be worth a different value to you in terms of their spend and how they interact with your brand. With this in mind, properly segmenting them in the first place will help ensure that they remain as profitable and engaged as possible.

Tackling this segmentation method should be the chief objective when undertaking your direct mail marketing campaigns. The hints and tips below will be beneficial for your segmentation success.

Build a Customer Profile

The most important part of segmenting your direct mail database is to build an accurate visual picture of your core customers. Then, assign them a certain profile based upon key characteristics that are important for your business. This will narrow your focus and help “seek" customers that best fit to your products and brand.

Segmenting Your Database to Find Your Ideal Customers

When creating customer profiles, key questions that may be helpful to ask yourself include:

What group of products do your customers purchase? What's their average order value?

This is one of the most fundamental questions when it comes to ROI and segmenting your database of direct mail customers. Once you've established the answer to these questions, you will be able to group customers together based on their product families and spend amounts.

What is unique about their location? Where do they make their purchases?

Breaking your database down into geographical areas may be helpful for a number of reasons - as examples, delivery area may differ from pick-up location, walk-in traffic will impact store location. Plot your current customer patterns on a local map around your business to see if there are any logical trends and patterns.

What stage of life are your customers in?

Another key piece of data when segmenting a database is, of course, the age of your various customers. Group them into age ranges. You will be more likely to effectively determine the right message, tone, and offer based on their life stage and past product purchases.

Demographic and age data can be important criteria for a marketer to use to help dial in the right direct mail creative, visuals clues, fonts, offer tone, and message sequence.

What are your customer's hobbies and interests?

Understanding basic customer behaviors can lead to insightful observations. Look for customers' patterns and interest signals that may be helpful for you to fully understand what makes them tick.

Getting Started - Types of Segmentation

Once you've established the main characteristics of your target customer groups, you can then begin to refine your segmentation and narrow the focus. Narrow is better. If you narrow in on the audience, the intensity and understanding of your appeal will be greater.

Narrow targeting can happen in a number of ways. Examples include:

Demographic Segmentation - This type of segmentation refers to demographic and geographical data such as age, gender, and location and remains one of the most valued forms of segmentation that any brand can utilize in their marketing strategies.

Attitudinal Segmentation - When segmenting your direct mail database attitudinally, you will be looking at things like psychographics, which is the study of attitudes, values, and interests. By understanding these characteristics and successfully grouping like-minded people together, it becomes much easier to make sure your direct mail campaigns hit the right note, thereby more likely to convert.

Behavioral Segmentation - This type of segmentation is focused on lifestyle related attributes and focuses on things like a typical customer's buying cycle. By looking for patterns in the way they choose to buy products (seasonal, pay-day etc), you can determine the perfect times to market to them with direct mail.

Share of Wallet Segmentation - An interesting concept and one that is routinely used to segment databases today is based on “customer spend." This essentially refers to segmenting customers based on their loyalty to your brand by cross-analyzing a customer's current amount of loyalty, or spend, on your products based on what they would spend overall on similar products and services. This form of data segmentation is often used in the food retail industry, for example, for a dine out restaurant. If a target customer typically spends $60 a week eating out, and you capture $15, you effectively have a 25% share of the weekly wallet spend.

Segmentation Tactics - Diving Deeper

Segmentation is all about better understanding your target customer. Several helpful segmentation tactics include:

Recency, Frequency and Monetary (RFM) Segmentation

In simple terms, this is segmenting your database based on recency (how recently a purchase was made), frequency (how often purchases are made), and monetary (what is the average order value of the customer).

You can assess this data and then assign each customer a simple attractiveness index/score based on for findings. There are various pros and cons to this type of data segmentation which include:

Strengths of RFM Segmentation:

Simple - RFM is simple to initiate and makes it much easier to make decisions of who and when to market from your direct mail database of customers.

Affordable - Little to no investment will be required to carry out this form of data segmentation.

Insightful - It provides at least some form of segmentation of your database and is better than mass marketing to customers using a broad appeal. Broad appeals tend to be weaker and less effective offers, as the market knows how to tune these out.

Weaknesses of RFM Segmentation:

Limited - It doesn't take into account other important segmenting factors that will help you target your message and offer.

Historical perspective - It can only be used with existing customers and cannot be used as a prospecting tool, while other segmentation characteristics can.

Advanced Segmentation Techniques - Even Deeper

Some companies just scratch the surface when it comes to their segmentation, whereas, others will delve deep into their database and really make sure they are understanding their target customer as accurately as possible. Here are several more advanced segmentation techniques that might be a fit for your business.

Lifecycle segmentation - This follows the accepted principle that most consumers will transition through four life cycles when it comes to their purchasing habits: transition, early, expansion and mature. The job of marketers is to correctly identify which stages their consumers are most likely to make purchases and time the messages and offers accordingly.

Predictive Segmentation - This type of segmentation of a database will delve deep into your client list and take into account many more variables than most other forms of segmentation that you're likely to encounter. Generally speaking, predictive segmentation will aim to provide marketing teams with predictive variables that will be most important to understand the future patterns of the customer interest and buying cycles.

Attitudinal Segmentation - Mentioned previously, this is possibly the most important form of segmentation and one that aims to engage the consumer on a personal level and compel them into making a purchase or taking a specific action. This form of segmentation aims to produce marketing campaigns that “speak" to the consumer on a personal level and is relevant to them. Personalized direct mail can be effective at creating a “one-to-one" marketing experience.

Conclusion

Segmentation works. Without it, you may be blindly attempting to sell to your consumers without thought to their tendencies, interest, needs, and natural buying triggers. Segmentation is not always straightforward, but once you've mastered it, you will begin to truly understand what your customers need and what motivates them to take action.

Direct mail marketing done correctly can grab attention and create positive engagement with your customers. Variable digital press technology now provides the ability to create campaigns that use personalized content, relevant and unique offers, and true “one-to-one" marketing communications that was not possible several years ago. By segmenting your database accurately, you can take advantage of this new print technology and tailor the right offer, design, and message that best match your list segmentation criteria.