2. The method of claim 1 , wherein the programmable maximum acceptable response time can be cost effectively set to a value proximate to zero seconds.
2. The method of claim 1 , wherein the programmable maximum acceptable response time can be cost effectively set to a value proximate to zero seconds. 3. The method of claim 2 , wherein predictively scheduling agents to respond to exercised help requests within a programmable maximum acceptable response time after the help request is exercised, comprises: identifying a time unit, wherein the time unit is used to express a lapse of time in finite increments of one time unit; identifying a time range consisting of a finite number of time units; for each current user of a plurality of current users navigating the navigable structure during a current time unit, wherein the current user is positioned at a current node, expressing in time units, a time relative to the current time when the current user may exercise the option to request help from a live agent at some subsequent node; for each time unit of the time range, computing for said each current user of a plurality of current users a statistical probability that the current user will exercise the help request during the time unit while visiting the subsequent node, based at least on accumulated navigational data for past users and the navigational data for the current user; associating the statistical probability with said each current user, said subsequent node, and said time unit; for each node in the navigable structure and for each time unit of the time range, computing a sum of the statistical probabilities associated with each current user of said plurality of current users navigating the navigable structure; associating with each agent a non-empty set of nodes of the network for which the agent is qualified to respond to a help request; based at least on the navigational data accumulated for past users and said sum of statistical probabilities, computing a forward looking agent demand matrix over the time range of agents necessary to respond to help requests from said each current user versus node and time unit, wherein the forward looking agent demand matrix comprises an expected minimum and an expected maximum number of agents, taking into consideration that each agent may be qualified in more than one node; identifying an update interval of time for updating the agent demand matrix, as users move from node to node while navigating the navigable structure; updating the forward looking agent demand matrix of agents at the expiration of each update interval of time; identifying a set of agent scheduling time segments; and for each time segment of the set of agent scheduling time segments, providing at least two types of agents to respond to help requests in compliance with the demand matrix, wherein the at least two types of agents comprise: scheduled agents, wherein scheduled agents work during a predefined work schedule and wherein the number of scheduled agents associated with each node is based upon the expected minimum number of agents needed; and demand agents, wherein demand agents are on call and work only when necessary to fulfill a demand representing a difference between the actual number of agents needed and the expected minimum number of agents needed and wherein the number of demand agents on call is based at least on the difference between the expected maximum and the expected minimum number of agents needed.