Every customer has his or her own individual needs, preferences, and desires. When face-to-face with a customer, it is easy for a good salesman to get a sense of who the customer is and adapt their sales approach for them. However, when interacting with customers through an eCommerce platform and through mass marketing strategies, this natural ability to gauge a customer is lost. This is where customer segmentation comes in.
What is Customer Segmentation?
Customer segmentation is the use of statistics and analytics to divide a large set of customers into smaller subcategories in order to better target their needs. Subcategories can be based on geographic criteria, demographic criteria, behavioral trends, lifestyle identification (also known as psychographic segmentation), cultural origins, desired benefits, or, in multi-variable account segmentation, a combination of criteria. If you are running a B2B business, customer segmentation is a little more complex, but it is typical to segment based on what industry a business is, the size of the company, a company’s location, and the company’s behavioral patterns. No matter the criteria, the bottom line is that with customer segmentation, your goal is to use information to know who a customer is, what they might want from your business’ catalog, and how you can best cater to them as an individual. This ensures that you are getting the most out of your marketing strategy.
An Example for eCommerce
The advantages of customer segmentation make the most sense when we move out of the abstract and into concrete examples of how it can be used. Let’s say that you run a eCommerce clothing store. You could segment your customers with a variety of these subcategory criteria in order to market more effectively:
1) Geographic segmentation: By splitting up your customers by region, you can send out promotions for clothing that is appropriate to the weather experienced in a customer’s own region.
2) Demographic segmentation: Here, you can split up customers based on their age and gender, sending promotions to customers only for clothing that matches who they are.
3) Behavioral segmentation: You can notice which customers like to buy a specific type of clothing, and send marketing about that type of clothing towards them.
4) Psycographic segmentation: You can look at which holidays a customer is likely to celebrate, and send them promotions for the clothes that celebrate or are appropriate for those holidays.
5) Cultural segmentation: You can look at a customer’s cultural origins and send them marketing for clothing that their culture has shown a history of buying.
6) Benefits segmentation: You can look at data on what a customer might want out of the clothing (for instance, a teacher would be looking for back-to-school clothes) and send promotions that highlight those benefits.
Though of course this is only a hypothetical set of ideas, consider how you can apply this type of thinking to your own business.
Using Analytics for eCommerce
This is where good CRM integration can really help your eCommerce business, because it provides you with the customer data necessary to build subcategories, gauge a specific customer’s activity to determine which subcategory he or she belongs to, and then use statistics to project which marketing strategy is best for each subcategory. Pairing your CRM analytics with big data is an extremely powerful, particularly if you wish to implement behavioral segmentation. The more data you have stored about your customers, the more effectively you can group them, and the better you can understand the way each subcategory makes purchases, and which marketing strategies have a history of being effective for that subcategory.
Clarity Can Help
To build an eCommerce platform with customer segmentation that is right for you, or if you need assistance with implementing customer segmentation, contact us for a free quote today!