Digital Commerce is growing dynamically in most countries and industries, both new and established online retailers are constantly expanding their product ranges and revenues. Different digital and customer services are essential to increase the success of online shops, as a representative survey among 300 online shops indicates. More than the half of the e-shops offer free shipping and product reviews, and already one third provides personalized content or product offers. To increase sales, the majority of online shops provide discount codes and recommendation of complementary and alternative products. Surprisingly, every third online shop implemented an online configurator for mass customized products or services. Three quarters answered that digital analytics is important for analyzing and controlling digital business. Analyzing different success factors, this contribution shows that customer-, service-and data-driven online shops generate higher conversions rates and revenues. Product reviews, discount codes, personalization and the recommendation of alternative products lead to significant higher conversion rates. Most online retailers are selling on different distribution channels like e-mail, phone, digital marketplaces and pick-up stores. Finally, successful omnichannel vendors are using a variety of digital marketing channels such as search engine optimization and advertising, newsletter marketing, social media and influencer marketing.

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In the Internet economy and information society, it has become an essential task of electronic business to analyze, to monitor, and to optimize websites and Web offers. Therefore, this chapter addresses the issues of Web analytics, which is defined as the measurement, collection, analysis, and reporting of Internet data for the purposes of understanding and optimizing website usage. After a short introduction, the second section defines Web analytics, describes benefits and problems of Web analytics, as well as different software architectures and products. Third, a controlling loop is proposed for Web content and Web user controlling in order to analyze Key Performance Indicators (KPIs) and to take website- and e-business-related actions. Fourth, different Web metrics and KPIs of information, transaction and communication are defined. Fifth, a fuzzy Web analytics approach is proposed, which makes it possible to classify Web metrics precisely into more than one class at the same time. Considering real Web data of the Web metrics page views and bounce rate, it is shown that fuzzy classification allows exact and flexible segmentation of Web pages or other objects and gradual rankings within fuzzy sets. In addition, the fuzzy logic approach enables Computing with Words (CWW), i.e. the perception-based, linguistic consideration of Web data and Web metrics instead of measurement-based, numerical ones. Web usage mining with inductive fuzzy classification and Web Analytics with Words (WAW) allows intuitive, human-oriented analyses, description, and reporting of Web metrics values in natural language.

In the Internet economy, it has become a crucial task of electronic business to monitor and optimize websites, their usage and online marketing success. Web analytics, which is defined as the measurement, collection, analysis and reporting of Internet data, is an effective instrument of website management. First, this paper describes the technical functionality and use of web analytics and discusses different web metrics. Second, a fuzzy web analytics approach is proposed, which makes it possible to classify metrics precisely into more than one class at the same time. Third, a fuzzy web metrics index has been developed for multidimensional, intelligent web analysis. Fuzzy logic enables computing with words and more intuitive, human-oriented queries, segmentation and descriptions of metrics in natural language. Finally, a web analytics framework is suggested to analyze and control key performance indicators in a web controlling loop.