Conclusions

The explosive evolution of the information technology and the Internet has introduced enormous changes in the way marketing strategies are being implemented. This growth was followed by problems concerning effective and efficient methods and techniques for supporting consumers and providing them with tailored Web experiences.

Personalization has the potential to be the answer and e-marketing should further focus on it. This technique can be applied on different dimensions of a general Web site marketing strategy, including: sales, advertisement, communication, customer support, etc. In this way any e-business, i.e., information portal, e-commerce site, or e-learning system can improve its performance by addressing the individual needs and preferences of each user , increasing satisfaction, promoting loyalty, and establishing one-to-one relationships.

Many research approaches, initiatives and techniques, as well as commercial tools provide Web personalization based on business rules, Web site contents and structuring, user behavior and navigational history as recorded in Web server logs.

Customers expect to be able to interact with an e-commerce site, find information and make online purchases easily and effectively. On the other hand, e-businesses expect to sell as many products and services as possible easily and cost-effectively as well. Thus, an effective e-marketing strategy should be considered from both the perspective of the customer and the e-business owner.

Specifically, from the customer's point of view, the Web site should ensure that:

• Efficient recommendations about new products, product discounts , special offers, coupons , sweepstakes, etc., are produced and delivered.

• All second-time visitors receive personalized content to meet their needs and that this content is embedded into recommendations about additional relevant products to be purchased.

• Browsing through the products of the online catalogue is easy.

• Useful assistance is available during all steps of the shopping process.

• Customers' time is respected and irritation is minimized.

• Customers' individuality is respected.

• Customers are allowed to specify and modify their own profile settings.

As regards the standpoint of the e-business, the Web site should:

• Promote the products effectively.

• Maintain customer profiles. This means that the system should capture customer behavioral information from the login procedure, completed purchases, response to questionnaires, etc. The data should be updated (if not dynamically) at predefined time intervals.

• Generate consumer demographics .

• Manage navigation data.

• Analyze sales data.

• Gather statistical data.

• 'Remember' and analyze everything the store needs to 'know' about the customer.

• Encourage customers to 'leave something of themselves behind' by multiple and 'invisible' methods.

• Increase second-time purchases (in the sense that the customers should keep coming back and thus develop a sense of loyalty towards the e-store).

An open issue in the field relates to the fact that in order to fulfill its aims, personalization needs rich data about users (e.g., demographics, behaviors, structure, etc.). If the data are poor, the produced personalized output will be unsuccessful in understanding and satisfying user needs and goals.

In most cases, users are negative about revealing personal information and resist to the idea of being stereotyped. Therefore, another issue that must be taken into consideration when planning and implementing personalization is privacy (Earp & Baumer, 2003; Kobsa & Schreck, 2003; Markellos et al., 2004). Tracking users' behavior means collecting ( potentially sensitive) information about them. Many research and commercial tools are available ensuring to some degree that privacy is not jeopardized (Cingil et al., 2000). However, if customers resist doing so, they will not be able to join the personalized segment.

Finally, a relatively recent development that is foreseen to greatly affect Web personalization is the expansion of the semantic Web. Semantic Web mining combines the two fast-developing research areas of semantic Web and Web mining with the purpose of improving Web mining by exploiting the new semantic structures in the Web. Berendt et al. (2002) gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.

Summarizing, in this chapter we presented the importance of personalization for intelligent e-marketing Web site applications. We explored the different phases of the personalization process (data collection, data processing and personalization output), we demonstrated the close relation between personalization and Web mining and concluded by discussing some open issues in the field.