What is Customer Analytics?
Posted: Tue Jan 07, 2025 5:57 am
Customer Analytics is defined as the process in which the company's customer behavior data is used to help make key decisions , through market segmentation and predictive analysis .
The important thing in this customer analysis process is that the indicators collected must come from the actions of the customers themselves or from their attitudes. This implies that the data analyzed comes from a source that has collected customer behavior or data related to the customer. Source: Customer Analytics For Dummies.
In many cases, this information is already available to businesses as more and more customer data is being collected.
The source of all this information can be as diverse as: CRMs or commercial and marketing databases, KPIs or metrics collected in online surveys , purchase receipts; product return rates, direct customer observation, web analytics, measurement of in-store behavior using Wi-Fi or Bluetooth devices or, for example, iBeacon, etc.
The difficulty in all this is that this information remains unused norway phone number unconnected under the tutelage of the various departments, areas and people who create and safeguard it.
The challenge of analyzing all this data is important to achieve the following:
Integrate and analyze the information collected from all these disparate sources.
To define the behavioral patterns that customers follow.
Develop the Customer Journey .
Detect problems in the customer's experience with the product or service in order to improve it.
Segment customers based on their purchasing behaviors.
Ultimately, data must be used to describe, explain and predict customer behavior .
The benefit of customer analysis is making decisions based on data , which leads to a series of concrete results : campaigns targeted at a particular segment and allowing for cost reductions as well as offering different prices based on demand, personalizing the offer of products and services, anticipating drop-outs and recovering dissatisfied customers, increasing customer loyalty and satisfaction, among many other advantages.
All this analytical task can be simplified by a more precise and integrated information collection system, which will result in faster: measuring, analyzing, taking action, and obtaining benefits for the client and the company.
The important thing in this customer analysis process is that the indicators collected must come from the actions of the customers themselves or from their attitudes. This implies that the data analyzed comes from a source that has collected customer behavior or data related to the customer. Source: Customer Analytics For Dummies.
In many cases, this information is already available to businesses as more and more customer data is being collected.
The source of all this information can be as diverse as: CRMs or commercial and marketing databases, KPIs or metrics collected in online surveys , purchase receipts; product return rates, direct customer observation, web analytics, measurement of in-store behavior using Wi-Fi or Bluetooth devices or, for example, iBeacon, etc.
The difficulty in all this is that this information remains unused norway phone number unconnected under the tutelage of the various departments, areas and people who create and safeguard it.
The challenge of analyzing all this data is important to achieve the following:
Integrate and analyze the information collected from all these disparate sources.
To define the behavioral patterns that customers follow.
Develop the Customer Journey .
Detect problems in the customer's experience with the product or service in order to improve it.
Segment customers based on their purchasing behaviors.
Ultimately, data must be used to describe, explain and predict customer behavior .
The benefit of customer analysis is making decisions based on data , which leads to a series of concrete results : campaigns targeted at a particular segment and allowing for cost reductions as well as offering different prices based on demand, personalizing the offer of products and services, anticipating drop-outs and recovering dissatisfied customers, increasing customer loyalty and satisfaction, among many other advantages.
All this analytical task can be simplified by a more precise and integrated information collection system, which will result in faster: measuring, analyzing, taking action, and obtaining benefits for the client and the company.