What Is Customer Data Analysis?
Customer data analysis is the initiative of analyzing and gaining a deep understanding of various information regarding customers. Through customer data analysis, you can clarify aspects such as the following:
- Identifying target customers
- Understanding customer needs
- Confirming customer satisfaction with your products and services
Without a clear grasp of "who your customers are" and "what your customers want," it is impossible to have them choose your products or services or to build long-term, positive customer relationships. Therefore, it is essential to collect and analyze diverse data related to customers to obtain insights that contribute to business strategies, including sales, marketing, and product development.
What Is Customer Data?
Customer data is a collective term for all information regarding customers. It includes basic information such as name, age, gender, address, and contact details, as well as behavioral history, such as "what they have purchased in the past" and "what advertisements they have responded to."
In B2B, customer data becomes even more complex. It is necessary to collect, organize, and manage a vast amount of data, including information about the entire organization, the departments and individuals negotiating with your company, and the ultimate decision-makers.
Customer data can be collected through various media and opportunities, such as websites, POS registers, mobile apps, social media, marketing campaigns, and surveys. For example, having users register as members on an e-commerce site is a representative collection method. Various information entered during registration can be utilized as customer data.
Maintaining accurate customer data to leverage for marketing and sales is becoming increasingly important today, as customer needs and behaviors are prone to change. While collecting customer data, ensure you establish an appropriate management system using IT tools, which will be discussed later.
Types of Customer Data
While customer data is diverse, it can be broadly categorized into two types: "quantitative data" and "qualitative data."
Quantitative data is "information that can be quantified." It is used to perform statistical analysis or conduct detailed research backed by numerical values. A key advantage of quantitative data is that it is easy to add objectivity to analysis results, and as more data becomes available for reference, the results are less likely to be biased. Representative examples of quantitative customer data include purchase amount, purchase quantity, and purchase frequency.
Qualitative data is "information that cannot be quantified" and is generally expressed in words. In terms of customer data, "customer feedback" received through surveys or customer support is a prime example. Such qualitative data is effective for grasping customer thoughts that are not visible through numbers. Additionally, company names, locations, industries, and representative names are also utilized as qualitative information.
It is important to use quantitative and qualitative data appropriately depending on the purpose. For example, "which product has the highest sales" can be clarified through quantitative analysis, whereas clarifying "why customers prefer that product" is better suited for qualitative analysis, such as survey results or trends by location.
Tools for Managing and Analyzing Customer Data
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To effectively manage, analyze, and utilize customer data, we recommend leveraging IT tools. Representative tools include Excel, CRM, SFA, and MA. The characteristics of each tool are as follows.
- Excel
Excel is a tool used by a vast number of companies and can also be used for managing customer data. Many people are already familiar with Excel, and if it is already implemented, there are no additional introduction costs, which is a significant advantage. However, since it is not a solution specifically designed for customer data management or analysis, there are many inconveniences. If you wish to conduct full-scale customer data analysis, it is better to adopt a CRM or SFA.
- CRM
CRM is a solution specialized for customer data management. It can often be integrated with various other tools, including SFA and MA, which are described later, making it a strong choice when you want to utilize customer data across systems and departments throughout the entire company. It is particularly recommended when you want to strengthen relationships with existing customers.
- SFA
SFA is a solution known as a Sales Force Automation system. It is designed primarily for the automation and efficiency of sales activities and is generally introduced when a company wants to strengthen its sales department rather than its marketing department. In addition to sales support functions, it is equipped with features for managing and analyzing customer data. It is a recommended choice if you want to achieve overall efficiency in sales activities, such as automating the creation of quotes and daily reports, and managing individual sales representative cases, in addition to customer data analysis.
- MA
MA is a solution aimed at the automation and efficiency of marketing activities. With MA, you can automatically send information via email newsletters or social media based on the results of customer data analysis. MA is a tool primarily used for lead nurturing (cultivating prospective customers). By passing these results to a CRM or SFA, the sales department can efficiently approach promising customers. If MA and each system are properly integrated, you can establish an environment where the process from each lead or customer to a closed deal can be tracked as data.
All the tools introduced above have functions for managing and analyzing customer data, but they each focus on different areas. It is important to strive for a deeper understanding of your customers by using these tools selectively or in combination as needed.
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