When we talk about the customer clustering method, it visualizes an algorithm known as the scientific segmentation. It signifies the cluster that results in better customer modeling and predictive analytics. 

Such type of analytics usually targets customers to serve them according to their demands. It does not signify any of the pre-existing rules but shows the customer’s prototypes within the existing community. 

To be precise, “Customer clustering is the process of discovering similarities in customers and divide them into groups, and therefore segmented. They might look similar but are not almost the same”. 

The motto of cluster analysis is to segment the customers to yield more efficient customer marketing accurately. Thus, the cluster leads to better customer modeling and predictive analytics and targets the right customers with personalized desires and needs.

Usage of Customer Cluster Analysis over sending Emails 

Most professionals depend on the email system as one of the most significant sources of communication. They act as formal messages sent in the form of official documents to communicate with others.  

Marketers should understand that segmenting email marketing lists can prosper marketing goals and improve click-through rates. It shows active vs. inactive users while executing customer clustering analysis. 

Cluster analysis is a tool for classifying clients and potential clients when sending emails. It helps plan a specialized campaign to re-engage inactive users (one who hasn’t opened your emails in the last three months).

Meanwhile, the analysis also looks for subscribers who are active users for engagement, and targeting them ensures retention. For instance, one can send an email informing the customer base about the latest sale, and the one who clicks the link refers to be “interested.” 

A specialized campaign can be drafted to target them so that they become customers of the sale. Also, sometimes surveys or quizzes are conducted to gather data about the customers and their desires, and emails are sent accordingly. 

It gives you insight into individual needs and preferences and offers incentives if you want to respond to a survey from audiences. 

Advantages of Clustering

The main advantages of customer analysis are- 

• Homogeneity- As differences in the resulting groups are negligible, that ensures homogeneity among your consumers. Unlike other variant groups that are much more different from one another
• Dynamic nature- The definition of cluster analysis changes every time for the customers according to the algorithm, which assures that the targeted groups always reflect the latest state of data
• Practicality – It would be practically impossible to execute rules that can correctly segment customers seeking many parameters

As customer behavior and mindset change frequently, that implies cluster analysis only once is not enough. Yes, it works better with the latest and relevant customer behavioral data. 

To decide emails to send to most online businesses implies identifying millions of people targeted by marketers. 

Expectedly, this is not something that can be accomplished manually; instead, one would need an automated system that yields an accurate customer base each day. 

Do custom-made platforms help in predictive modeling?

Today, marketers are aware that segmenting email marketing lists can improve click-through rates. Let’s make the process easier to follow.  

Read below customer cluster strategies that are helpful to send emails with NextBee’s automated platform. 

1. Last Purchases

A simple way of cluster analysis is to segment customers by their past purchases. It’s a way of optimizing targeting and an easy method to send emails for the same items in which buyers take more interest. 

If a customer buys something that needs replacement, then emails should go according to the demands. After that, you can segment by the item purchased, category of that product, and also a combination of both.

2. Expenditure on Last Purchases

The categorization of customers can take place by the amount they usually spend on their purchases. When you sell a range of high and low dollar items, the expenditure becomes more relevant. 

It is good to analyze customers’ spending history to know which customers are likely to buy from you and in which amount. 

Also, it will let you know the segment that shows more interest in affordable and less-expensive items. In this way, you can send emails featuring products that are actually in each person’s price range.

3. Demographics

The customer clustering also considers demographics as a marketing analysis tool. Details like age, company position, and income can tell a lot about a person’s desire to launch a marketing campaign. 

The more details you have about your audience in the registration process, the more the options are present for demographic segmentation. 

Also, cluster analysis by demographic information is the easiest way in an email marketing platform that allows you to customize the sign-up questions.  

4. Position in the Sales Funnel

Segmenting takes place by analyzing whether your audience is in the sales funnel. It can help to customize your messaging through emails. At the top of the funnel, targeting becomes easier for different emails to those at the bottom. 

For instance, for a group of new consumers, emails should be more general. It should give details of products or features you offer; it can be welcome emails introducing them to the brand. 

The information comes in handy to determine what they desire and send more emails on that product or service.

Conclusion

Email marketing segmentation is not just a modern marketing automation software. With NextBee’s unique AI-driven automated technology, brands can leverage several benefits to run various campaigns to support their business goals.

 To know in detail, contact our marketing experts and take a free demo about the software.