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<HTML> <HEAD> <!--SCRIPT LANGUAGE="JavaScript" SRC="http://a1835.g.akamai.net/f/1835/276/3h/www.netlibrary.com/include/js/dictionary_library.js"></SCRIPT> <SCRIPT LANGUAGE="JavaScript"> if (!opener){document.onkeyup=parent.turnBookPage;} </SCRIPT!--> <META HTTP-EQUIV="Cache-Control" CONTENT="no-cache"> <META HTTP-EQUIV="Pragma" CONTENT="no-cache"> <META HTTP-EQUIV="Expires" CONTENT="-1"><META http-equiv="Content-Type" content="text/html; charset=windows-1252"><SCRIPT>var PrevPage="Page_280";var NextPage="Page_282";var CurPage="Page_281";var PageOrder="289";</SCRIPT> <TITLE>Document</TITLE> </HEAD> <BODY BGCOLOR="#FFFFFF"><CENTER><TABLE BORDER=0 WIDTH=100% CELLPADDING=0><TR><TD ALIGN=CENTER> <TABLE BORDER=0 CELLPADDING=2 CELLSPACING=0 WIDTH=100%> <TR> <TD ALIGN=LEFT><A HREF='Page_280.html'>Previous</A></TD> <TD ALIGN=RIGHT><A HREF='Page_282.html'>Next</A></TD> </TR> </TABLE></TD></TR><TR><TD ALIGN=LEFT><P><A NAME='JUMPDEST_Page_281'/><A NAME='{970}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0 WIDTH='100%'><TR><TD ALIGN=RIGHT><FONT FACE='Times New Roman, Times, Serif' SIZE=2 COLOR=#FF0000>Page 281</FONT></TD></TR></TABLE><A NAME='{971}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>likes and dislikes of the targeted consumer. If consumer tastes vary greatly, as can be the case with such products as software or books, then these products benefit from being highly differentiated. In traditional marketplaces this used to be done in part through warranty cards and market surveys. However, in today's digitized marketplace, the consumer information is hardwired to the retailer since not only does the buyer reveal the methods of distribution they require but also the type of products they want, the rate they want them at, and how much they are willing to pay for them. All are values that can be mined for the refinement and delivery of products and services by retailer.</FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{972}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>Consider your customers and the data, which you are mining as the basis for the evolution and development of your website. Solicit feedback via e-mail from first-time buyers. Did they find what they wanted? How long did it take? What else should you be doing at your website in order to get your first-time buyers to return and buy again and again. How do you transform first-time buyers into loyal customers? Asking them is one way; another is doing an analysis of your website data. Use data mining tools such as decision trees and rule generators to segment your visitors and develop profiles of your existing customers. Use these analyses to find out what your visitor information requirements are. How did they arrive at your site? Are they looking for a leisurely browsing experience or the fastest path to a specific product or service at your site?</FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{973}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>Your data mining analysis may identify several different market segments that are attracted to your website, which may impact how you organize your site. For example, a travel site may find that it is attracting travel agent professionals, people who do not travel much, die-hard travelers, and investors. This may point out the need to design different website sections in the home page targeted to these four different types of visitors. Data mining may also uncover what visitors are browsing for by analyzing the keywords they are using in their quest for product information. Poring over log files, registration forms, and e-mail can uncover some hints; however, using a data mining tool can accelerate this process and point out hidden patterns manual inspection may not detect, especially for a heavily visited site with thousands of daily visitors.</FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{974}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>Electronic retailing is really about linking your back-end inventory database to the browsers of your visitors and customers. In the process, however, you have the opportunity to observe the interactions and patterns which can evolve over time. Data mining can assist you in uncovering these patterns and assist you in improving your retailing efforts and your relationship with your customers. With so</FONT><FONT FACE='Times New Roman, Times, Serif' SIZE=3 COLOR=#FFFF00><!-- continue --></FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{975}'/></FORM></P></TD></TR></TABLE><P><FONT SIZE=0 COLOR=WHITE></CENTER><A NAME="bottom"> </A><!-- netLibrary.com Copyright Notice --> </BODY></HTML>⌨️ 快捷键说明
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