Web analytics

Web analytics is the process of analyzing the behavior of visitors to a Web site. Web analytics provides information about the number of visitors to a website and the number of page views. The objective is to promote specific products to those customers most likely to buy them, and to determine which products a specific customer is most likely to purchase. In addition to these features, Web analytics may include tracking the click through and drilldown behavior of customers within the Web site, determining the sites from which customers most often arrive and the results of Web analytics are provided in the form of tables, charts, and graphs. Web analytics is the measurement, collection, analysis and reporting of web data for purposes of understanding and optimizing web usage. However, Web analytics is not just a process for measuring web traffic but can be used as a tool for business and market research, and to assess and improve the effectiveness of a website.
Web analytics applications can also help companies measure the results of traditional print or broadcast advertising campaigns. It helps one to estimate how to traffic of the Website changes after the launch of a new advertising campaign. It helps gauge traffic and popularity trends which is useful for market research. The use of Web analytics is said to enable a business to attract more visitors, retain or attract new customers for goods or services, or to increase the dollar volume each customer spends.


Communicating with browsers to track and analyze online behavior. Web analytics is often used as part of customer relationship management analytics. The analysis can include determining the likelihood that a given customer will repurchase a product after having purchased it in the past, personalizing the site to customers who visit it repeatedly, monitoring the dollar volume of purchases made by individual customers or by specific groups of customers. The geographic regions from which the most and the least customers visit the site and purchase specific products, and predicting which products customers are most and least likely to buy in the future. This can help to improve the ratio of revenue to marketing costs.

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