Abstract:
A system and method for tracking and reporting days and visits to an online transaction is described. A web analytic system receives web site visit tracking information from a client computer as a user navigates the web site. The system updates a reporting database with visit information. The system may receive data in the form of a report message sent from a site, where the data has been calculated to give the metric or where the message provides the raw data required to derive the metric. The system generates a variety of reports showing time between visits and transactions, such as time between visits, orders, downloads, form completion or other such transactions.

Description:
[0001]    This application claims the benefit of U.S. Provisional Application No. 60/946,047 filed 25 Jun. 2007, entitled “Days and Visits to an Order System and Method,” which is incorporated herein by reference. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The present invention relates to web page statistical reporting. In particular, it relates to data gathering and reporting techniques for web sites. 
       BACKGROUND OF THE INVENTION 
       [0003]    The World Wide Web (web) has rapidly become an invaluable tool to individuals and businesses. Not only can an individual or business post information on the web, but it can also use the web to transact business. Because the public is acutely aware of the web&#39;s business and personal benefits, millions of web pages are being added to the web each year. 
         [0004]    Typically, a web page is defined by a document containing Hyper Text Markup Language (HTML) code. An HTML document suitable for posting on the internet includes both “content” and “markup.” The content is information which describes a web page&#39;s text or other information for display or playback on a computer&#39;s monitor, speakers, etc. The markup is information which describes the web page&#39;s behavioral characteristics, such as how the content is displayed and how other information can be accessed via the web page. 
         [0005]    In order to provide web-based information and services over the internet, the web employs “client” computers, “browser” software, and “server” computers. A client computer is a computer used by an individual to connect to the internet and access web pages. A browser is a software application, located on a client computer, which requests, via the internet, a web page from a server computer. After receiving the web page, the browser displays the web page on the client computer&#39;s monitor. A server computer is a computer which stores web page information, retrieves that information in response to a browser&#39;s request, and sends the information, via the internet, to the client computer. Thus, after a web page is created, the page should be “posted” to a particular server computer which “hosts” the page, so that the page can be accessed over the internet. 
         [0006]    One web-based service that has seen steady growth in the past decade is e-commerce. The percentage of sales made over the internet continues to grow by double-digits annually. With an adjusted retail sales value of over $36 billion dollars in the fourth quarter of 2007, the percentage of retail sales conducted over the internet increased nearly 5% over the same period the previous year, and accounted for 3.5% of total retail sales in 2007. 
         [0007]    With this kind of opportunity for online sales, web merchants are anxious to learn how to leverage the benefits of e-commerce to maximize their own sales. Many web merchants utilize a web analytic system in an effort to gain some understanding of their visitor&#39;s behavior. The majority of the functionality offered by these systems is session-related visitor behavior. However, understanding how the visitors behave over a period of time or across sessions can provide valuable information and insight to the merchant. 
         [0008]    The present invention provides a solution to these needs and other problems, and offers other advantages over the prior art. 
       BRIEF SUMMARY OF THE INVENTION 
       [0009]    In a preferred embodiment of the contemplated invention, a web analytic tracking system with reporting module that tracks and reports user/customer visits before a transaction and number of days since the last transaction is described. In this embodiment, client logic in scripts downloaded to the customer&#39;s computing device on his first visit to a site calculates visits and days since the last order. These values are set in a persistent cookie planted by the e-commerce system the first time the customer visits the site. The actual calculated visits and days since last order are sent to the web analytic system in report message fields and parameters whenever an order is placed. The data is then available for reporting, use in module or functionality available in the web analytic system, and export to other systems. 
         [0010]    Additional advantages and features of the invention will be set forth in part in the description which follows, and in part, will become apparent to those skilled in the art upon examination of the following or may be learned by practice of the invention. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]      FIG. 1  is an illustration of process flow for a preferred embodiment of the described invention. 
           [0012]      FIG. 2  is a diagram of a web analytics system designed to collect and report web analytics for web sites. 
           [0013]      FIG. 3  is diagram of exemplary report messages sent and received by an end-user/client&#39;s system. 
           [0014]      FIG. 4 . is an exemplary report message structure for a client message. 
           [0015]      FIG. 5  is an exemplary report message structure for a hint server message segment. 
           [0016]      FIG. 6  is an exemplary report message structure for a prediction engine message segment. 
           [0017]      FIG. 7  is a screenshot of an exemplary visits to order report. 
           [0018]      FIG. 8  is a screenshot of an exemplary days to order report. 
       
    
    
     DETAILED DESCRIPTION 
       [0019]    One indicator of the success of the online merchants e-commerce system is the number of visits or days it takes before the user performs an action (such as making a purchase) and how long it takes, if at all, before the customer comes back and performs another action. Tracking this information gives the web site owner insight into the behavior of users/visitors to and at the site and helps to understand what actually leads the visitor to perform the desired transaction. These metrics can indicate how many or what portion of customers buy on the first visit, or how many or what portion need several visits in order to transact. The metrics may also indicate how long it takes for a customer to come back for another transaction; or, when used in combination with additional purchase data, which products might lead to a future purchase of other products. Although the following description refers to e-commerce purchase tracking, it will be apparent to those skilled in the art that these metrics may apply equally as well to any type of measurable activity, such as a download or a form completion or registration. 
         [0020]    In a preferred embodiment of the contemplated invention, a web analytic system with an e-commerce tracking module and reporting manager tracks user behavior at a target web site (i.e., a visit metric) including, among other things, number of visits to order and number of days to order,  FIG. 1  illustrates the process contemplated for a preferred embodiment of this invention. When a user enters the target site  102 , the click initiates a download of scripts  104  that plant session and persistent cookies  106  on the user&#39;s computer related to the target&#39;s web site. A session cookie is used for storage of state between page views within a session, and a persistent cookie is used for keeping user state between visits to a merchant&#39;s web site. User behavior data is collected as the user navigates the site and performs transactions  108 . As the user moves through the site, the cookies send the user data to the web analytic system  110 . The data is parsed, processed and written to a database  112 . Merchants may view the data by accessing the reporting module  114 . Additionally, data may be exported  116  to other systems for use in marketing campaigns. For instance, a merchant may export the data to an e-mail marketing system and use it in segmenting data for use in configuring a new marketing campaign  118 . As the user continues to visit the site  120 , new statistics are calculated and returned to the analytic system, allowing the merchant to view reports showing the behavior of the individual user across multiple sessions. 
         [0021]      FIG. 2  illustrates an exemplary web analytics system. The web analytics system  208  uses software code operating on the merchant web site  204  or content server  206  to load scripts  203 ,  205  that plant cookies designed to collect information and keep state about the end-user. This information is transmitted in a report message  304  from session and persistent cookies written to the end-user/client&#39;s system  202  to the web analytics hint servers  210  when the user moves from page to page. The client-side (e.g., client  202 ) generates a session ID on entry to a site such as web site  204 . The client-side collects and stores page attributes, such as URL, referrer and title, and computes page timing statistics, such as display time, read time, and connection type (depending on the browser used). Additional functionality on the client side includes computation of session-level attributes, gathering end-user system information, collecting e-commerce actions, gathering custom data from cookies or URL parameters, or custom javascript variables, and performing form tracking. Computations may include frequency values, such as visits to order and days to order 
         [0022]    The information gleaned from the client side is contained in a report message  304 ,  400 , an indexed string of delimited data that is sent from the client side  202  to the analytic system at point  207  in  FIG. 2 . An example of a client portion of a report message structure  400  showing the segments delivering this information  402 ,  404 ,  406 ,  408  is displayed in  FIG. 4 . The visits to order segment  402  displays the number of user visits that have passed before an order was made. If a user has never purchased in the past, visits is calculated from first visit to the site. If the user is a repeat purchaser, then the number of visits is based on last order placed. Days to order  404  displays the number of days that have passed before an order was made. If a user has never purchased in the past, days is calculated from first visit to the site. If the user is a repeat purchaser, then the number of days is based on last order placed. The report message is passed on to the hint server  210 . Although a preferred embodiment of this invention may perform calculations on the client side, those skilled in the art will recognize that it is also possible to gather the data on the server-side by a content provider such as a merchant, and the data may be sent in either raw or derived form. 
         [0023]    As the report message  404  passes through the hint server  210 , the hint server  210  appends additional fields to the report message  500  (shown in  FIG. 5 ) and passes the amended report message to the PE  212 . The PE  212  adds its own set of values  600  as shown in  FIG. 6  after processing, and the entire message is archived in a log file in the NFS  213 ,  214  and written to the reporting database  215 ,  216 ,  112 . An exemplary final message is shown in Table 1 below. 
         [0000]    
       
         
               
             
           
               
                 TABLE 
               
               
                   
               
             
             
               
                 !1162411200900′3/u/}1}http://www.hotels.com/promotion. 
               
               
                 jsp?id=1105}http://www.hotels.com/promotion.jsp?id=354 
               
               
                 8}}C1850307181R3}11}tSan Francisco, CA hotels - Hotel 
               
               
                 Reservations &amp; Discounts for Luxury and Budget }1}15}} 
               
               
                 }}}}}}}}}2}}2}8}2}1}vis=m53z0#m55z0#m42z0#m52z1#m53z1# 
               
               
                 m54z1#m51z2#137#m41z1#m54z2#m36z1#m56z2#m55z2#m40z1#15 
               
               
                 2#117#131#m42z1#e125482z#m11z1#m36z0#g440958#m52z2#m53 
               
               
                 z2#m35z0#g435236#g405989#m11z0#m40z0#g440959#g405992#g 
               
               
                 40590#115}true}}}16}1024×768}32}1}}1}8′Mozilla/4.0 
               
               
                 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 
               
               
                 1.1.432) }198.189.184.127}hotelsfbmn}115}http: //www.ho 
               
               
                 tels.com/promotion.jsp?id=1105}false′}}701, 704, 128, 239, 
               
               
                 5852}405989, 405992, 435236, 409590, 125482}0}3}5}}}}}} 
               
               
                   
               
             
          
         
       
     
         [0024]    In a preferred embodiment, days and visits to order data contained in the report are calculated on the client side, and reach the analytic system with no need for further processing. To accomplish this, a preferred embodiment of the invention utilizes functions contained in scripts downloaded  104 ,  106  to the client when the client first visits the site  102 . If a user has never purchased in the past, visits and days are calculated from the first visit to the site. If the user is a repeat purchaser, then the number of visits/days may be based on last order placed. For example, Joe started visiting a merchant&#39;s specialty store on May 2, but didn&#39;t buy anything. He visited again on May 5 and on May 12 he purchased a bottle of wine. He visited the site again on May 16, May 18 and May 20. Finally, on May 20 he bought some caviar. The days to order for the May 12 order is 10, and the visits to order is 2. The days to order for the May 20 order is 8, and the visits to order is 3. The values are set in a persistent cookie and will be used next time the order comes in. The system stores the sequential visit number in which the last order was placed and it also stores the timestamp of the last order. The actual calculated or derived visits and days since last order are sent in report message fields and parameters whenever a new order is placed. It will be appreciated by those skilled in the art that a server-side content system (e.g., a merchant web site) may be configured to generate the tracking information message and sent to the analytic system. In addition, the analytic system could retrieve previous visit data from a data store and associate the previous visit data with the received tracking information message when the received information message includes transaction data but incomplete data related to the previous target web site visit. 
         [0025]    The reports generated from this data provide merchants with invaluable information. With a days to order or visits to order report, the merchant can measure the return generated from specific types of content or offers posted to the site or between types of campaigns (e.g. pay per click, direct traffic, affiliate marketing traffic) and determine the best time to initiate further campaigns.  FIGS. 7 and 8  (designated  700  and  800 , respectively) are screenshots of exemplary transaction reports. These reports give the merchant invaluable insight into user or customer behavior. For instance, referring to  FIG. 7   700 , the report may indicate to the merchant that 76% of customers purchase on their first visit, but the remaining 24% will purchase on their next or later visit. Three percent of those will purchase after visiting more than 15 times. The merchant can then segment the data or drill down to determine valuable insights, such as who belongs to each group, what products are purchased only after more thoughtful decision making, or whether there is seasonal variation.  FIG. 8  illustrates an exemplary days to order  800  report. 
         [0026]    It is to be understood that even though numerous characteristics and advantages of various embodiments of the present invention have been set forth in the foregoing description, together with details of the structure and function of various embodiments of the invention, this disclosure is illustrative only, and changes may be made in detail, especially in matters of structure and arrangement of parts within the principles of the present invention to the full extent indicated by the broad general meaning of the terms in which the appended claims are expressed. For example, the particular elements may vary depending on the particular application for the web interface such that different dialog boxes are presented to a user that are organized or designed differently while maintaining substantially the same functionality without departing from the scope and spirit of the present invention.