What is Analytics CRM?
Analytics to manage customer relationships (CRM) is the way companies discover and use customer information to help make business decisions. The information is collected and analyzed using special computer software. CRM analysts often relies on web mining and collect information. To analyze this information, it uses classic data mining parameters. Using this analysis, the company can learn what its customers really want, how to best adapt services and which customers are likely to bring the greatest profit for the company.
In a world where it is possible to shop and shop online without leaving home comfort, many companies use the Internet more about their customers. CRM Analytics has several goals. First, companies want to group customers according to interest in the target market with their specific needs. Second, companies want to know which customers are likely to achieve the most profit for the companyKzers know which Customers is worth targeting.
do it using web mining. Web mining is a system of technicians that allow companies to look for patterns in customer behavior; Three web mining techniques are commonly used in CRM analysts. The mining structure examines how shoppers use a website. This technique shows, for example, what customers or ads click on. Content mining uses data collected and the third technique called applications uses information from online forms and other customers' answers.
Once the information is collected using these techniques, it is entered in a multidimensional database. This type of database allows the data to be viewed and organized on the basis of different characteristics. For example, if a user asks for a multidimensional database: "What are the three best countries in the world?" This can allow the user to organize informationBased on population, gross domestic product or some other parameter.
In CRM Analytics, information in the database is analyzed using data mining techniques. Data mining is looking for patterns that could help companies to predict what customers want, most likely buying and what types of shops or promotional actions offer them. For example, when using data mining, the company could find out that people who buy video games often return to the web to buy sci books. The company then knows that if the customer buys a video game, the customer is likely to send a 10 percent of the SCI -FI coupon.