When evaluated thoroughly and carefully with the optimal technology, customer data can help you transform the way buyers interact with your business. However, know that an enhanced segmentation strategy is only as good as the system you use to organize your data sets and analyze the results.
Extensive analysis of each customer segment results in detailed insights about your customers‘ buying patterns. It also provides other data that can help you pinpoint and address any marketing pain points.
Furthermore, gauging your target segments and examining the refined customer data has become the premier way to comprehend better and serve your audience’s needs.
Let’s explore customer segmentation data analysis and ways to enhance it for your business.
What Is Customer Segmentation Data Analysis And Why Is It Important?
Customer analytics, also known as customer segmentation data analysis, is the process of garnering and evaluating customer information to gain insightful data on customer patterns and behavior. It requires various tools to collect and organize different data types and a methodological framework to analyze and understand it.
Companies leverage analytics to make important decisions related to product development, sales, marketing, and more. Customer analytics also allows you to figure out the advertising platforms that work best and give you positive ROI.
Moreover, you can also map out the entire customer journey and build out tailored marketing campaigns. Customer segmentation data analytics go beyond merely making smart and informed marketing decisions. It can also have a considerable impact on your company’s bottom line.
According to a McKinsey survey, companies that extensively leverage customer analytics have reported 93% higher profits and 115% higher ROI.
With customer analytics, you can deliver more customized and timely marketing campaigns and implement email segmentation to send out customized messages to your respective customers.
This, in turn, helps your sales team to comprehend the buying process of your customers. Similarly, your product team can use customer analytics insights to enhance the product by adding features.
How To Perform Customer Segmentation Data Analysis?
With an understanding of customer segmentation data analysis’s advantages, you can begin to look at how to carry out a proper analysis within your organization.
Before you dive into creating different segments for your customers, consider the following tips to help you plan efficiently.
Outline Your Segments And Sub-Segments
This might sound obvious. However, if you have various customer segments, it is quite normal to overlook some. Specifically, if you haven’t organized the details in your CRM properly, or there is constantly an addition of the new ones.
So, it is imperative to outline your customer segments accurately to conduct the customer data analysis. It will also help people from different departments to access and use the insights.
Define Your Analysis Criteria
It is vital to define your analysis criteria which can help you manage and maintain consistency when comparing results over time. Here are a few factors that you can consider.
Segment Growth
The segment growth factor is crucial. If your segments aren’t growing, it indicates that you didn’t cluster your customers properly, or your message is too generic to reach a certain segment. It also means that your segmentation is too general, which makes the messaging ineffective. Therefore, it is essential to split your customers into segments and sub-segments.
Customer Lifetime Value
Customer Lifetime Value (CLV) is the total amount your customers are going to spend on your offerings. If your Customer Acquisition Cost is higher, then you need to figure out the reason.
Customer Churn Rate
Churn rate refers to the period your customers from every segment stay loyal to the brand and don’t shift. A higher churn rate indicates that you might not be targeting the right audience or that your customers are unsatisfied with your products/services.
Net Promoter Score
Net Promoter Score surveys effectively help you measure your customer’s satisfaction rate. If your segments have a mainly low or high NPS? High NPS segments mean that this group of customers is a valuable segment you need to focus on.
Analyze Results
To classify well-performing segments, it is imperative to know and set your KPIs. What is a high or low segment growth? What is the acceptable churn rate for your company? To have precise answers to these questions, KPIs are critical to drive your analysis and help you with decision-making regarding different segments.
Right tools are paramount to having an effective customer segmentation data analysis. It can help you gauge data related to sales growth, churn rate, etc. Having a robust CRM system is to gather all your data related to your customers.
Take an Action
Once you have an effective strategy and tools in place, decide how you want to implement and run your analysis. Remember, consistency is key. Map out your action plan and decide on the following:
-
How do you plan to deal with a low-performing segment discard it or revive it?
-
How much time do you require to modify a segment or get rid of it?
Wrapping Up
The bottom line is that customer segmentation data analysis is critical to companies. It helps them create reports to optimize their corporate decisions derived from in-depth customer analysis.
Furthermore, it helps you improve your competitiveness, and your important decisions are grounded on a deep customer behavior understanding. Above all, it enables you to adjust your messaging strategy to specific segments that is as crucial.