The activities of market research, product design and positioning or customer acquisition rely on precise and thorough information about the market environment and customers. Presented examples of various data analysis services directly support such marketing activities.

Web-farming means performing a systematic content mining of World Wide Web to keep you informed about topics essential for your business. Web is used more and more as a huge data source of important business intelligence, namely getting the information about potential customers, suppliers or competitors, the information about the latest market opportunities, technology trends or development of global economics. Therefore every company that wants to stay competitive should exploit the web as valuable resource. Web-farming offers a way for such a continuous mining of the Internet. It covers the identification of the important business information on the web, its acquisition, linking it to internal company data warehouse and delivering processed information to appropriate persons or departments in the company. Major benefits of web-farming are continuous monitoring of strategic business information sources, exploiting the essential facts and smooth merging of the information within the company's data warehouse systems. All these operations can be done with help of advanced data-mining tools.

This is a marketing technique concerning selling complementary (cross selling) or additional (up selling) products to specific customers considering their past purchases. Cross/Up selling widens the customer's reliance on the company and lowers the chance that the customer switches to a competitor. That can lead to significant increase of the company incomes as well as it increases the customer loyalty. Data-mining model can assist you in choosing optimal targets for marketing campaigns, it can identify the best next cross/up selling offers for your customers that will match their current needs. Various advanced methods are utilized to identify the associations between products purchases. One of the cross/up selling methods is Market Basket Analysis. Well done analysis can define what service or products should be sold together in packages and what package to offer to what client. Other practical approach is to use classification models in order to select the clients most likely to respond on given offer. This allows well targeted marketing, that reduces the campaign cost while maintaining the highest effectiveness.

By exploiting some of these intelligent data-mining techniques people are able to draw the highly beneficial outcomes from data concerning your customers, e.g. by using customer segmentation, by identifying potential cross/up selling offers for your customers, by modeling and testing various hypothesis, allowing you to create personal offer to your customer with high potential to fit his/her needs.

Each website visit provides a set of important data about visitor and his behavior. This constitutes a huge set of data that hide valuable business knowledge. To fully exploit this source of information, a support of special tools for web usage analysis is needed.

Standard analytical tools offer a set of simple low-level statistics of website visits. Data Mining offers more advanced form of analysis, for instance a preference identification of a visitor by using behavioral data such as visited links sequence, time spent on specific pages, webpage entry and exit points. Outcomes of the analysis provides a valuable knowledge about attractiveness of product or service offered on-line; they suggests a way to shape your services to fit customer's needs.