4 Inspiring Customer Segmentation Examples
How well you can get to know your clients well depends on how much data you’re able to gather about them. The more data you have, the more developed segments you can build. But the data itself is not enough.
It is important to know not only how to leverage it, which segments are the most important for your business and how to analyze them. Here are some customer segmentation examples that will amplify your campaigns.
Optimize customer groups
Groups of clients that share similar demographic or behavioral characteristics, called segments, should be analyzed closely to learn more about how they can be targeted. Valuable insights can be gained from careful examination of the data that distinguishes one group from another.
A big challenge is the use of simple segmentation, but also dynamic segmentation based on customer behavior. Taking simple groups (like men or women) into account is fine, but you can go much deeper than that. More sophisticated use of your data can paint a better picture of their motivations and needs.
Demographic segmentation
Segment your clients using demographic data, including place of residence, age, gender, marital status, etc. Create customer groups by region, city size, population density, gender, occupation, education and more.
Customer segmentation examples
Information on customer geolocation will allow you to send offers and promotions for a specific store, region, province. What’s more, you’ll also be able to send relevant messages to people who have changed their place of residence or are on holiday.
Information about customer professions will allow you to adjust and send the appropriate content to each user, e.g. ebooks for marketers, events for management staff etc.
Demographic information will also allow you to match other products such as: cosmetics designed for specific age groups, bank account offers suited to different ages, etc.
Segmentation by transactions
Segment and create customer groups based on budget or purchase value. A very interesting solution is also to consider the frequency of orders among a given group of clients in order to build various retention scenarios.
Customer segmentation examples
Send special offers to people who buy the most or spend the most on your products. Send premium offers to customers with a higher potential lifetime value. Send information about discounted products to people who only buy discounted products.
Segmentation based on technographic data
Technographic data involves the characteristics of devices and methods used to interact with your brand online, such as:
- operating system
- device model
- device type (mobile/desktop)
- number of devices owned
- system version
- resolution
- language used
- browser
This allows you to define the most-used devices and the technical standardsthat deliver the largest number of conversions, what type of products the customer buys depending on the device’s brand.
You can also analyze the likelihood to make a purchase and customer loyalty regarding various devices and platforms.
Customer segmentation examples
This kind of data is especially useful in the field of electronics and appliances. Information about what kind of equipment particular customers use can be useful to companies that sell these items, giving them the ability to inform potential clients about new models and complementary items.
Fans of particular brands, like Apple products, can be informed about new releases, updates and other relevant information that might get them into a store, whether physical or virtual.
Segmentation by customer behavior
Assign attributes to specific clients. This is a solution that allows you to assign a selected attribute in the customer profiles, including: client visits to a specific category more than 3 times, frequency of purchases, banner clicks and other signals of interest, etc.
This allows you to expand the ability to personalize communication with every client to the greatest degree possible.
Customer segmentation examples
Send personalized messages to customers based on their behavior. Target customers who have demonstrated an interest in a particular product or category with the appropriate content.
If a site visitor views the same product multiple times but doesn’t make a purchase, send a targeted discount after a certain amount of time to encourage the customer to close the sale.
Analyze conversion paths of particular segments
Constant analysis of traffic in any e-commerce store means tracking multiple customer segments. As mentioned before, these include segments based on behavioral and demographic information.
There are, however, three primary customer segments that are fundamental to online success:
- Returning customers – those who buy most often
- High-volume customers – those who buy the most products
- VIP customers – those who spend the most in the store
The frequency and amount of purchases has to be defined individually in terms of the branch, types of products and price level. An analysis of past sales can be useful—average cart value, purchase frequency and number of products in cart per customer, etc.
Values above the average can be used to build the three segments above.
These three segments represent the most important and profitable customers, both in terms of money spent and loyalty. It’s obviously worth knowing more about who they are, what they buy and why.
Having identied these segments, it’s necessary to examine their conversion paths and purhcasing habits, including:
- How many times they visited the store before making their first purchase
- The dates and times when they make the most purchases
- Whether they buy online or offline
- How much time they spend on the site before making a purchase
All of this allows you to optimize your communications along with when and how you send them. Decisions about offering discounts and in what form are also easier when you have a more precise picture of who your customers are and what they respond to.
Wrapping up
When creating a segment, you need a plan for how you are going to use it. Be sure that the information that defines the segment is properly collected and stored in your database. If, for example, a segment needs information about a customer’s education but that information is not often collected or shared, it’s better to choose another basis for the segment.
Remember that more segments aren’t necessarily always better. Start small and expand when you can see a real benefit to getting into smaller, more precise groups.