How to Segment Customers in the Last MileCustomer segmentation is the key to successful last mile marketing 🔑
Customer segmentation is classically a core feature of marketing. This is no different on your website. We encourage you to segment your users, not just in analytics but in the user experience.
Many digital product designers and marketers use personas (or personae) to help with segmentation. To deliver customer journeys that meet the needs of each persona, you need to translate personas into quantifiable segments.
You don’t need to have personas to get started with segmentation. You can segment customers and think about the highest value journeys on your website without creating fictional representatives. While personas can help you focus on customer needs, they also contain assumptions about your customers and can be counter-productive. If you do use personas, make sure to use them in service of making your site more accessible, not in over-looking some users in favour of customers who are more like you.
What is customer segmentation in last mile marketing?
Think about the things you know about your web visitors. You might know where they’ve come from. Most analytics tools have traffic source. You might, if they have an account, know a few things about them as customers, like their email address or whether they are a free or a paying user for example.
Most importantly, there are a number of ways to find out a whole lot about how they use your website. You might, like 650,000 other sites, use Google Analytics and you can supplement that free service with other tools such as Kissmetrics, Mixpanel, Omniture and so on.
You can know things about who your customers are, where they’ve come from, and what they do on their site. You need to organise, visualise, and easily add to this data, so that you can use it to deliver better last mile customer journeys.
Dimensions and states
One way to conceptualise user data is the dimensions and states method. This method is best suited to customer segmentation, particularly in the last mile. You can also use it to form a single customer view.
You can think of the types of things you know about customers as dimensions. Think “traffic source”, “membership tier”, “time since last purchase”, “number of visits to the site”. You can even make dimensions out of simple things like “first name” or “email address”. Most of the time though dimensions are best for types of information that put users into groups, rather than store individual personal information.
This is a practical point, but it is also always worth considering how much individual, personally-identifying data you need to deliver better customer journeys. While it can be powerful to address customers by name, data anonymisation is always preferable whenever it’s possible. After all, personal data is kind of like toxic waste.
The information you know about each customer is their state within that dimension. If the dimension is “membership tier” some customers might have the state “free”, others “premium”, and the rest “non-members”.
The dimensions and states method shows its usefulness when you start to map customer journeys. You can think of it as something like a combination of the personas and “jobs-to-be-done” frameworks used in product design, with a more explicit marketing focus.
For a start, dimensions and states are an easy way to segment customers for better targeted journeys. Take for example a sale campaign on an ecommerce website. You might decide that it’s important for your journeys to know whether customers have come from somewhere advertising the sale or not and whether they have ever visited the site before.
In this example, you would start with two user dimensions:
- Previous visits
You could start by dividing each dimension into just two states:
|Previous visits||None||One or more|
You could combine states by plotting them like this:
|One or more|
With this table, you’ve created a maximum of four customer segments. Each is represented by one of the spaces in the table. You can run through and ask a few questions about each one. What do we want customers to do if they have never visited the site before and arrived from a sale ad? What about these customers is going to shape their particular customer journey? How can we make that journey better and easier?
You don’t need to make every space in the dimensions and states table its own segment.
You might decide for example that users who have visited before are already familiar with the site and the brand and therefore require less time getting to know you. You can design their customer journeys for simplicity, a shorter path to conversion, and more prompting around the sale meaning that now is the time to buy. And for these customers, you might simply decide that it doesn’t matter whether they arrived from a sale ad or not. You can define a segment simply from the “One or more” state in the “Previous visits” dimension.
For customers who have never visited the site before however, you might want to distinguish between whether they came from a sale ad or not. You might hypothesise that those coming from a sale ad are more focussed on getting a good deal and buying now. For these users, you will want to balance the extent to which they need to get to know your brand with consistent messaging throughout the journey that reflects what they initially saw in the ad.
The new visitors who haven’t come from the ad on the other hand don’t need the same treatment. You can optimise the site for the sale in general but you might even reduce the prominence of your promotions to give these new customers the opportunity to get to know your website without feeling bombarded by content.
In this example therefore, we have ended up with three customer segments from the four states that we have across two dimensions.
|None||🎯 S1||👋 S2|
|One or more||🤑 S3||🤑 S3|
You can go deeper with customer segmentation and will probably return to the dimensions and states method when you start specifying customer journeys in detail. The best next step therefore is to learn the basics of how to create last mile customer journeys.
In our latest breakfast, we addressed how theories of customer psychology can be harnessed in finance.read more
We invited a select group of travel marketers to breakfast to discuss the use of customer psychology to win the last mile.read more
For our first breakfast of 2018, we invited digital fundraisers to discuss the challenges and opportunities presented by marketing technology.read more