SYSTEM AND METHOD FOR IDENTIFYING AND APPROACHING BROWSERS MOST LIKELY TO TRANSACT BUSINESS BASED UPON REAL-TIME DATA MINING

摘要

The present invention is directed to a system and functionality that removes the guess work out of trying to determine which browsers on a web site are more likely to end up with a good disposition. One approach introduced by the present invention is to first make sure the sales server captures as much information about browsers as is possible with respect to their activity on the website/ecommerce server. Then the server enables the enterprise to use business rules to define the population of browsers that are eligible for chat invitations. Out of this population, the server, on behalf of individual agents, approaches browsers as randomly as possible. As agents are entering into engagements and recording their disposition codes, the server periodically determines if it can identify any patterns in behavior of those engagements that end up with a good disposition code. For example, the server may note that browsers who were invited to chat in the 8th minute of their session and those who had seen 2 product pages end up in good engagements four times more often than the average browser. Once a sufficient sample set of engagements is conducted to allow the server to develop a statistically valid profile/model of browsers who end up with good engagements, the server compares all new browsers against this model and provides a numeric number representing how close the new browser is to the model. This number, called a score, is then used by the system to sort the browsers in real time and used as the criteria as to who should be approached and in which order.