This disclosure generally relates to contact centers and, more particularly, to techniques for benchmarking pairing strategies in a contact center system.
A typical contact center algorithmically assigns contacts arriving at the contact center to agents available to handle those contacts. At times, the contact center may have agents available and waiting for assignment to inbound or outbound contacts (e.g., telephone calls, Internet chat sessions, email) or outbound contacts. At other times, the contact center may have contacts waiting in one or more queues for an agent to become available for assignment.
In some typical contact centers, contacts are assigned to agents ordered based on time of arrival, and agents receive contacts ordered based on the time when those agents became available. This strategy may be referred to as a “first-in, first-out”, “FIFO”, or “round-robin” strategy.
Some contact centers may use a “performance based routing” or “PBR” approach to ordering the queue of available agents or, occasionally, contacts. PBR ordering strategies attempt to maximize the expected outcome of each contact-agent interaction but do so typically without regard for utilizing agents in a contact center uniformly.
When a contact center changes from using one type of pairing strategy (e.g., FIFO) to another type of pairing strategy (e.g., PBR), overall contact center performance will continue to vary over time. It can be difficult to measure the amount of performance change attributable to using a new pairing strategy because there may be other factors that account for some of the increased or decreased performance over time.
In view of the foregoing, it may be understood that there is a need for a system that enables benchmarking of alternative routing strategies to measure changes in performance attributable to the alternative routing strategies.
Techniques for benchmarking pairing strategies in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for techniques for benchmarking pairing strategies in a contact center system comprising: cycling, by at least one processor, among at least two pairing strategies; and determining, by the at least one processor, a difference in performance between the at least two pairing strategies.
In accordance with other aspects of this particular embodiment, the method may further comprise: determining, by the at least one processor, an arrival time of a contact; selecting, by the at least one processor, a first pairing strategy of the at least two pairing strategies based on the arrival time; and pairing, by the at least one processor, the contact to an agent using the first pairing strategy.
In accordance with other aspects of this particular embodiment, the method may further comprise associating, by the at least one processor, an identifier of the first pairing strategy with a record of an interaction between the contact and the agent.
In accordance with other aspects of this particular embodiment, the at least two pairing strategies may be allocated equal proportions of a cycle time period, a duration of a cycle through each of the at least two pairing strategies may be less than an hour, a duration of a cycle through each of the at least two pairing strategies may be less than a day, or a duration of a cycle through each of the at least two pairing strategies may be less than a week.
In accordance with other aspects of this particular embodiment, the method may further comprise: determining, by the at least one processor, a prior pairing of a contact; selecting, by the at least one processor, a first pairing strategy of the at least two pairing strategies based on the prior pairing; and pairing, by the at least one processor, the contact to an agent using the first pairing strategy.
In accordance with other aspects of this particular embodiment, a second pairing strategy of the at least two pairing strategies may have been selected based on an arrival time of the contact in an absence of the prior pairing.
In accordance with other aspects of this particular embodiment, the method may further comprise determining, by the at least one processor, a differential in value attributable to at least one pairing strategy of the at least two pairing strategies.
In accordance with other aspects of this particular embodiment, the method may further comprise determining, by the at least one processor, compensation to a provider of the at least one pairing strategy of the at least two pairing strategies based on the differential value.
In accordance with other aspects of this particular embodiment, the at least one pairing strategy of the at least two pairing strategies may comprise at least one of: a behavioral pairing (BP) strategy, a first-in, first-out (FIFO) pairing strategy, a performance-based routing (PBR) strategy, a highest-performing-agent pairing strategy, a highest-performing-agent-for-contact-type pairing strategy, a longest-available-agent pairing strategy, a least-occupied-agent pairing strategy, a randomly-selected-agent pairing strategy, a randomly-selected-contact pairing strategy, a fewest-contacts-taken-by-agent pairing strategy, a sequentially-labeled-agent pairing strategy, a longest-waiting-contact pairing strategy, or a highest-priority-contact pairing strategy. In accordance with other aspects of this particular embodiment, a duration of a cycle through each of the at least two pairing strategies may align infrequently with changes to hours of a day.
In another particular embodiment, the techniques may be realized as a system for benchmarking pairing strategies in a contact center system comprising at least one processor, wherein the at least one processor is configured to perform the above-described method.
In another particular embodiment, the techniques may be realized as an article of manufacture for benchmarking pairing strategies in a contact center system comprising: a non-transitory processor readable medium; and instructions stored on the medium; wherein the instructions are configured to be readable from the medium by at least one processor and thereby cause the at least one processor to operate so as to perform the above-described method.
The present disclosure will now be described in more detail with reference to particular embodiments thereof as shown in the accompanying drawings. While the present disclosure is described below with reference to particular embodiments, it should be understood that the present disclosure is not limited thereto. Those of ordinary skill in the art having access to the teachings herein will recognize additional implementations, modifications, and embodiments, as well as other fields of use, which are within the scope of the present disclosure as described herein, and with respect to which the present disclosure may be of significant utility.
In order to facilitate a fuller understanding of the present disclosure, reference is now made to the accompanying drawings, in which like elements are referenced with like numerals. These drawings should not be construed as limiting the present disclosure, but are intended to be illustrative only.
A typical contact center algorithmically assigns contacts arriving at the contact center to agents available to handle those contacts. At times, the contact center may have agents available and waiting for assignment to inbound or outbound contacts (e.g., telephone calls, Internet chat sessions, email) or outbound contacts. At other times, the contact center may have contacts waiting in one or more queues for an agent to become available for assignment.
In some typical contact centers, contacts are assigned to agents ordered based on time of arrival, and agents receive contacts ordered based on the time when those agents became available. This strategy may be referred to as a “first-in, first-out”, “FIFO”, or “round-robin” strategy. For example, a longest-available agent pairing strategy preferably selects the available agent who has been available for the longest time.
Some contact centers may use a “performance based routing” or “PBR” approach to ordering the queue of available agents or, occasionally, contacts. PBR ordering strategies attempt to maximize the expected outcome of each contact-agent interaction but do so typically without regard for utilizing agents in a contact center uniformly. Some variants of PBR may include a highest-performing-agent pairing strategy, preferably selecting the available agent with the highest performance, or a highest-performing-agent-for-contact-type pairing strategy, preferably selecting the available agent with the highest performance for the type of contact being paired.
For yet another example, some contact centers may use a “behavioral pairing” or “BP” strategy, under which contacts and agents may be deliberately (preferentially) paired in a fashion that enables the assignment of subsequent contact-agent pairs such that when the benefits of all the assignments under a BP strategy are totaled they may exceed those of FIFO and PBR strategies. BP is designed to encourage balanced utilization of agents within a skill queue while nevertheless simultaneously improving overall contact center performance beyond what FIFO or PBR methods will allow. This is a remarkable achievement inasmuch as BP acts on the same calls and same agents as FIFO or PBR methods, utilizes agents approximately evenly as FIFO provides, and yet improves overall contact center performance. BP is described in, e.g., U.S. patent application Ser. No. 14/871,658, filed Sep. 30, 2015, which is incorporated by reference herein. Additional information about these and other features regarding the pairing or matching modules (sometimes also referred to as “SATMAP”, “routing system”, “routing engine”, etc.) is described in, for example, U.S. Pat. No. 8,879,715, which is incorporated herein by reference.
Some contact centers may use a variety of other possible pairing strategies. For example, in a longest-available agent pairing strategy, an agent may be selected who has been waiting (idle) the longest time since the agent's most recent contact interaction (e.g., call) has ended. In a least-occupied agent pairing strategy, an agent may be selected who has the lowest ratio of contact interaction time to waiting or idle time (e.g., time spent on calls versus time spent off calls). In a fewest-contact-interactions-taken-by-agent pairing strategy, an agent may be selected who has the fewest total contact interactions or calls. In a randomly-selected-agent pairing strategy, an available agent may be selected at random (e.g., using a pseudorandom number generator). In a sequentially-labeled-agent pairing strategy, agents may be labeled sequentially, and the available agent with the next label in sequence may be selected.
In situations where multiple contacts are waiting in a queue, and an agent becomes available for connection to one of the contacts in the queue, a variety of pairing strategies may be used. For example, in a FIFO or longest-waiting-contact pairing strategy, the agent may be preferably paired with the contact that has been waiting in queue the longest (e.g., the contact at the head of the queue). In a randomly-selected-contact pairing strategy, the agent may be paired with a contact selected at random from among all or a subset of the contacts in the queue. In a priority-based routing or highest-priority-contact pairing strategy, the agent may be paired with a higher-priority contact even if a lower-priority contact has been waiting in the queue longer.
Contact centers may measure performance based on a variety of metrics. For example, a contact center may measure performance based on one or more of sales revenue, sales conversion rates, customer retention rates, average handle time, customer satisfaction (based on, e.g., customer surveys), etc. Regardless of what metric or combination of metrics a contact center uses to measure performance, or what pairing strategy (e.g., FIFO, PBR, BP) a contact center uses, performance may vary over time. For example, year-over-year contact center performance may vary as a company shrinks or grows over time or introduces new products or contact center campaigns. Month-to-month contact center performance may vary as a company goes through sales cycles, such as a busy holiday season selling period, or a heavy period of technical support requests following a new product or upgrade rollout. Day-to-day contact center performance may vary if, for example, customers are more likely to call during a weekend than on a weekday, or more likely to call on a Monday than a Friday. Intraday contact center performance may also vary. For example, customers may be more likely to call at when a contact center first opens (e.g., 8:00 AM), or during a lunch break (e.g., 12:00 PM), or in the evening after typical business hours (e.g., 6:00 PM), than at other times during the day. Intra-hour contact center performance may also vary. For example, more urgent, high-value contacts may be more likely to arrive the minute the contact center opens (e.g., 9:00 or 9:01) than even a little later (e.g., 9:05). Contact center performance may also vary depending on the number and caliber of agents working at a given time. For example, the 9:00-5:00 PM shift of agents may perform, on average, better than the 5:00-9:00 AM shift of agents.
These examples of variability at certain times of day or over larger time periods can make it difficult to attribute changes in performance over a given time period to a particular pairing strategy. For example, if a contact center used FIFO routing for one year with an average performance of 20% sales conversion rate, then switched to PBR in the second year with an average performance of 30% sales conversion rate, the apparent change in performance is a 50% improvement. However, this contact center may not have a reliable way to know what the average performance in the second year would have been had it kept the contact center using FIFO routing instead of PBR. In real-world situations, at least some of the 50% gain in performance in the second year may be attributable to other factors or variables that were not controlled or measured. For example, the contact center may have retrained its agents or hired higher-performing agents, or the company may have introduced an improved product with better reception in the marketplace. Consequently, contact centers may struggle to analyze the internal rate of return or return on investment from switching to a different to a different pairing strategy due to challenges associated with measuring performance gain attributable to the new pairing strategy.
In some embodiments, a contact center may switch (or “cycle”) periodically among at least two different pairing strategies (e.g., between FIFO and PBR; between PBR and BP; among FIFO, PBR, and BP). Additionally, the outcome of each contact-agent interaction may be recorded along with an identification of which pairing strategy (e.g., FIFO, PBR, or BP) had been used to assign that particular contact-agent pair. By tracking which interactions produced which results, the contact center may measure the performance attributable to a first strategy (e.g., FIFO) and the performance attributable to a second strategy (e.g., PBR). In this way, the relative performance of one strategy may be benchmarked against the other. The contact center may, over many periods of switching between different pairing strategies, more reliably attribute performance gain to one strategy or the other.
Several benchmarking techniques may achieve precisely measurable performance gain by reducing noise from confounding variables and eliminating bias in favor of one pairing strategy or another. In some embodiments, benchmarking techniques may be time-based (“epoch benchmarking”). In other embodiments, benchmarking techniques may involve randomization or counting (“inline benchmarking”). In other embodiments, benchmarking techniques may be a hybrid of epoch and inline benchmarking.
In epoch benchmarking, as explained in detail below, the switching frequency (or period duration) can affect the accuracy and fairness (e.g., statistical purity) of the benchmark. For example, assume the period is two years, switching each year between two different strategies. In this case, the contact center may use FIFO in the first year at a 20% conversion rate and PBR in the second year at a 30% conversion rate, and measure the gain as 50%. However, this period is too large to eliminate or otherwise control for expected variability in performance. Even shorter periods such as two months, switching between strategies each month, may be susceptible to similar effects. For example, if FIFO is used in November, and PBR is used December, some performance improvement in December may be attributable to increased holiday sales in December rather than the PBR itself.
In some embodiments, to reduce or minimize the effects of performance variability over time, the period may be much shorter (e.g., less than a day, less than an hour, less than twenty minutes).
With short, intra-hour periods (10 minutes, 20 minutes, 30 minutes, etc.), the benchmark is less likely to be biased in favor of one pairing strategy or another based on long-term variability (e.g., year-over-year growth, month-to-month sales cycles). However, other factors of performance variability may persist. For example, if the contact center always applies the period shown in
In some embodiments, to reduce or minimize the effects of performance variability over even short periods of time, the order in which pairing strategies are used within each period may change. For example, as shown in
In some embodiments, to help ensure trust and fairness in the benchmarking system, the benchmarking schedule may be established and published or otherwise shared with contact center management ahead or other users of time. In some embodiments, contact center management or other users may be given direct, real-time control over the benchmarking schedule, such as using a computer program interface to control the cycle duration and the ordering of pairing strategies.
Embodiments of the present disclosure may use any of a variety of techniques for varying the order in which the pairing strategies are used within each period. For example, the contact center may alternate each hour (or each day or each month) between starting with the first ordering shown in
In the examples of
As shown in
In some embodiments, as in the example of
In some embodiments, as explained below with references to
As shown in
Table III below shows the sequence of days and times at which a new period begins at the top of the hour. For example, assuming five-day weeks Monday-Friday with eight-hour days from 9-5, the sequence would proceed from aligning on Monday at 9:00 AM, to Tuesday at 12:00 PM, to Wednesday at 3:00 PM (15:00), to Friday at 10:00 AM, and so on. As shown in Table III, it would take 2.2 weeks for a contact center that is open five days per week for eight hours per day to be aligned at the beginning of a day (e.g., Tuesday at 9:00 AM over two weeks later).
Table IV below shows the sequence of days of the week on which a new period begins at the top of that day of the week. In this example, assuming five-day weeks Monday-Friday with eight-hour days, the sequence would proceed from aligning with the beginning of the day on Monday in week 1, Tuesday in week 3, Wednesday in week 5, and so on. As shown in Table IV, it would take 11 weeks for this contact center to be aligned at the beginning of a Monday again.
Thus, as
In some embodiments, the contact center may determine which pairing strategy to use based on the time at which a pairing request is made for a contact. For example, assume a contact center is benchmarking BP and FIFO using the example of
In other embodiments, the contact center may determine which pairing strategy to use based on the time at which a contact arrives. For example, assume a contact center is benchmarking BP and FIFO as in the preceding example. If the first contact arrives at 9:04 AM, the time of arrival falls in the first half of a period, so the BP strategy may be used for the contact. Even if the first contact must wait in a queue for two minutes, and the pairing is not requested until 9:06 AM, the pairing may still be made using the BP strategy. Moreover, if a second contact arrives at 9:05 AM, while the first contact is still waiting in queue, the second contact may be designated for FIFO pairing. Consequently, at 9:06 AM, contact choice under behavioral pairing may be limited to only the contacts in queue who arrived during the BP portion of the period and, in this example, only the first contact to arrive would be available.
In embodiments for epoch-based benchmarking in which a contact arrives on a boundary between periods, or on a boundary between switching pairing strategies within a period, the system may have predetermined tie-breaking strategies. For example, the boundary may be defined as “at or before” an aforementioned time, or “on or after” an aforementioned time, etc. For example, if a period is defined to be associated with strategy “A” from 9:00-9:08 and strategy B from 9:08-9:10, it may mean that a contact must arrive on or after 9:00 but before 9:08 (e.g., 9:07.99) to be considered within the first part of the period. Alternatively, it may mean that a contact must arrive after 9:00 but at or before 9:08.00 to be considered within the first part of the period.
In some embodiments, inline benchmarking techniques may be used, in which pairing strategies may be selected on a contact-by-contact basis. For example, assume that approximately 50% of contacts arriving at a contact center should be paired using a first pairing method (e.g., FIFO), and the other 50% of contacts should be paired using a second pairing method (e.g., BP).
In some embodiments, each contact may be randomly designated for pairing using one method or the other with a 50% probability. In other embodiments, contacts may be sequentially designated according to a particular period. For example, the first five (or ten, or twenty, etc.) contacts may be designated for a FIFO strategy, and the next five (or ten, or twenty, etc.) may be designated for a BP strategy. Other percentages and proportions may also be used, such as 60% (or 80%, etc.) paired with a BP strategy and the other 40% (or 20%, etc.) paired with a FIFO strategy.
From time to time, a contact may return to a contact center (e.g., call back) multiple times. In particular, some contacts may require multiple “touches” (e.g., multiple interactions with one or more contact center agents) to resolve an issue. In these cases, it may be desirable to ensure that a contact is paired using the same pairing strategy each time the contact returns to the contact center. If the same pairing strategy is used for each touch, then the benchmarking technique will ensure that this single pairing strategy is associated with the final outcome (e.g., resolution) of the multiple contact-agent interactions. In other situations, it may be desirable to switch pairing strategies each time a contact returns to the contact center.
In some embodiments, the determination of whether a repeat contact should be designated for the same (or different) pairing strategy may depend on other factors. For example, there may be a time limit, such that the contact must return to the contact center within a specified time period for prior pairing strategies to be considered (e.g., within an hour, within a day, within a week). In other embodiments, the pairing strategy used in the first interaction may be considered regardless of how much time has passed since the first interaction.
For another example, repeat contact may be limited to specific skill queues or customer needs. Consider a contact who called a contact center and requested to speak to a customer service agent regarding the contact's bill. The contact hangs up and then calls back a few minutes later and requests to speak to a technical support agent regarding the contact's technical difficulties. In this case, the second call may be considered a new issue rather than a second “touch” regarding the billing issue. In this second call, it may be determined that the pairing strategy used in the first call is irrelevant to the second call. In other embodiments, the pairing strategy used in the first call may be considered regardless of why the contact has returned to the contact center.
One approach to considering prior pairing for inline benchmarking techniques is depicted in
At block 410, an identifier of a contact (e.g., caller) may be identified or otherwise determined. In this example, a caller's “Billing Telephone Number” or “BTN” may be identified. This example assumes that a caller uses the same BTN for each call. In other embodiments, other identifiers of the contact (e.g., a customer identification number, Internet Protocol (IP) address) may be used instead. Having identified the caller's BTN (or other contact identifier), benchmarking method 400 may proceed to block 420.
At block 420, a pseudorandom number generator (PRNG) may be seeded with the BTN (or other contact identifier). Having seeded the PRNG with the BTN, benchmarking method 400 may proceed to block 430.
At block 430, a pseudorandom number may be generated for the contact using the seeded PRNG. Because the seed will be the same for a given contact each time the contact returns to the contact center, the generated pseudorandom number will also be the same each time for the given contact. Having generated the pseudorandom number, benchmarking method 400 may proceed to block 440.
At block 440, a pairing strategy (e.g., BP or FIFO) may be selected for the given contact based on the generated pseudorandom number. For example, if 50% of contacts should be paired using BP, and the other 50% should be paired using FIFO, the PRNG may be configured to generate either a 1 or a 0. If the generated pseudorandom number is a 1, the contact may be designated for BP pairing. If the generated pseudorandom number is 0, the contact may be designated for FIFO pairing.
In this way, the contact will always be paired using the same strategy each time the contact returns to the contact center. The PRNG will be seeded with the same seed (e.g., the contact's BTN) each time, so the PRNG will generate the same pseudorandom number for the contact each time. Thus, benchmarking method 400 may select the same pairing strategy for the contact each time. In this way, it is possible to account for prior pairings without relying on a database or other storage means to determine whether or how a contact has been previously paired. In this way, benchmarking method 400 is stateless with respect to whether or how a contact has been previously paired. Having selected a pairing strategy for the contact, benchmarking method 400 may proceed to block 450.
At block 450, the contact may be paired to an available agent using the selected pairing strategy. When a contact has been paired with an available agent, components of the contact center system (e.g., switches, routers) may connect the contact to the agent. Following (or during) the contact-agent interaction, the agent may create a record of the outcome of the interaction. For example, in a sales queue, the agent may create an order for the contact. In a technical support queue, the agent may create or modify a service ticket. The contact center system may also record information about the interaction, such as the time and duration of a call, the BTN or other identifier of the contact, the agent identifier, and other data. At this point, benchmarking method may proceed to block 460.
At block 460, an identifier of the selected pairing strategy may be associated with the record of the contact-agent interaction created at block 450. In some embodiments, this may happen simultaneously with the creation of the record. For example, when the contact center system records the time and duration of a call, it may also record whether the call had been paired using a BP or FIFO pairing strategy. In other embodiments, another module may create a separate record of the pairing. This module may record the time of the pairing, the contact and agent identifiers, the pairing strategy used (e.g., BP or FIFO), and any other data that may be helpful for later matching the pairing record with the record of the caller-agent interaction outcome. At some later time, the pairing records may be matched with the caller-agent interaction records so that the pairing strategy information may be associated with the outcome in one record or the other (or both). Following block 460, benchmarking method 400 may end. In some embodiments, benchmarking method 400 may return to block 410, waiting for another contact to arrive.
Another approach to considering prior pairing in combination with epoch benchmarking techniques is depicted in
At block 510, a contact (e.g., “contact n”) arrives at the contact center at a particular time t. Benchmarking method 500 may proceed to block 520.
At block 520, it may be determined whether the contact has been previously paired; i.e., whether this contact is returning to the contact center for a subsequent touch or interaction. This decision may be made using a variety of techniques. For example, the benchmarking system may look up the contact's records using a contact identifier (e.g., BTN or customer ID) in a database to determine whether and when the contact had previously contacted the contact center. Using a suitable technique, the benchmarking system may determine that the contact had been previously paired and, in some embodiments, whether and how the prior pairing should influence the current pairing.
In some embodiments, the benchmarking system may preferably pair a contact using the same pairing strategy every time the contact returns to the contact center. Thus, if contact n was previously paired using pairing strategy “A” (e.g., BP), benchmarking method 500 may proceed to block 560 for subsequent pairing using pairing strategy A again. Similarly, if contact n was previously paired using pairing strategy “B”) (e.g., FIFO), benchmarking method 500 may proceed to block 570 for subsequent pairing using pairing strategy B again.
However, if it is determined at block 520 that contact n has not been previously paired (or, in some embodiments, any prior pairing should not influence the current pairing), benchmarking method 500 may proceed to using epoch benchmarking at block 550.
At block 550, time may be used to determine which pairing strategy to use for contact n. In this example, arrival time t may be used. If contact n arrived during a time period when the benchmarking system is pairing using strategy A, benchmarking method 500 may proceed to block 560 for subsequent pairing using strategy A. Similarly, if contact n arrived during a time period when the benchmarking system is pairing using strategy B, benchmarking method 500 may proceed to block 570 for subsequent pairing using strategy B.
At blocks 560 and 570, contacts may be paired to available agents using pairing strategies A and B, respectively. In some embodiments, more than two pairing strategies may be used (e.g., prior pairings using A, B, C, etc. or epoch benchmarking within time periods using A, B, C, etc.). Once paired, the contact may be routed or otherwise connected to the available agent within the contact center system. As described above with respect to benchmarking method 400 (
At block 580, an identifier to the selected pairing strategy (e.g., A or B) may be associated with the record created at block 560 or 570. As described above with respect to benchmarking method 400, this association may occur simultaneously with the creation of the contact-agent interaction record, or it may be matched at a later time with other records created by a benchmarking module or other module. Following block 580, benchmarking method 500 may end. In some embodiments, benchmarking method 500 may return to block 510, waiting for another contact to arrive.
By associating the pairing strategy with the outcome as in, for example, benchmarking methods 400 and 500, the outcomes associated with each pairing strategy may be measured (e.g., averaged, accumulated), and the relative performance of each pairing strategy may be measured (e.g., the relative overall performance gain attributable to pairing using BP instead of pairing using FIFO). This benchmarking data may be used for a variety of purposes. For example, the data may be used to assess the strength of one pairing module over another. For another example, the data may be used to improve the strength of a BP module by providing “BP on” and “BP off” (e.g., FIFO) contact-agent interaction records to enhance the artificial intelligence in the system. For another example, the data may be used for billing. Because the value added by one pairing strategy over another may be measured accurately and fairly, this benchmarking data may be used in a pay-for-performance business model, in which a client pays a pairing strategy vendor a percentage of the actual measured value added by using the vendor's pairing strategy (e.g., when BP is on as opposed to when BP is off).
Specifically, in some embodiments, associated outcome data may be used to determine an economic value or gain associated with using one pairing strategy instead of another. In some embodiments, the economic value or gain may be used to determine compensation for a vendor or other service provider providing a module or modules for the higher-performing pairing strategy creating the economic value. For example, if a contact center benchmarks BP against FIFO and determines that, for a given time period (e.g., a day, a week, a month, etc.), that BP performed 5% better than FIFO on average over the time period, the BP vendor may receive compensation corresponding to the 5% value added by BP (e.g., a percentage of the 5% additional sales revenue, or a percentage of the 5% additional cost savings, etc.). Under such a business model, a contact center owner may forgo capital expenditure or vendor fees, only paying a vendor for periods of time in which the vendor demonstrates value added to the contact center's performance.
As shown in
The central switch 610 may not be necessary if there is only one contact center, or if there is only one PBX/ACD routing component, in the contact center system 600. If more than one contact center is part of the contact center system 600, each contact center may include at least one contact center switch (e.g., contact center switches 620A and 620B). The contact center switches 620A and 620B may be communicatively coupled to the central switch 610.
Each contact center switch for each contact center may be communicatively coupled to a plurality (or “pool”) of agents. Each contact center switch may support a certain number of agents (or “seats”) to be logged in at one time. At any given time, a logged-in agent may be available and waiting to be connected to a contact, or the logged-in agent may be unavailable for any of a number of reasons, such as being connected to another contact, performing certain post-call functions such as logging information about the call, or taking a break.
In the example of
The contact center system 600 may also be communicatively coupled to an integrated service from, for example, a third party vendor. In the example of
A contact center may include multiple pairing modules (e.g., a BP module and a FIFO module) (not shown), and one or more pairing modules may be provided by one or more different vendors. In some embodiments, one or more pairing modules may be components of benchmarking module 640 or one or more switches such as central switch 610 or contact center switches 620A and 620B. In some embodiments, a benchmarking module may determine which pairing module may handle pairing for a particular contact. For example, the benchmarking module may alternate between enabling pairing via the BP module and enabling pairing with the FIFO module. In other embodiments, one pairing module (e.g., the BP module) may be configured to emulate other pairing strategies. For example, a benchmarking module, or a benchmarking component integrated with BP components in the BP module, may determine whether the BP module may use BP pairing or emulated FIFO pairing for a particular contact. In this case, “BP on” may refer to times when the BP module is applying the BP pairing strategy, and “BP off” may refer to other times when the BP module is applying a different pairing strategy (e.g., FIFO).
In some embodiments, regardless of whether pairing strategies are handled by separate modules, or if some pairing strategies are emulated within a single pairing module, the single pairing module may be configured to monitor and store information about pairings made under any or all pairing strategies. For example, a BP module may observe and record data about FIFO pairings made by a FIFO module, or the BP module may observe and record data about emulated FIFO pairings made by a BP module operating in FIFO emulation mode.
Embodiments of the present disclosure are not limited to benchmarking only two pairing strategies. Instead, benchmarking may be performed for two or more pairing strategies.
In some embodiments, contact center management or other users may prefer a “stabilization period” or other neutral zone. For example, consider a contact center benchmarking BP and FIFO pairing strategies. When the system transitions from BP to FIFO (or vice versa), contact center management may be concerned that the effects of one pairing strategy may somehow influence the performance of another pairing strategy. To alleviate these concerns about fairness, a stabilization period may be added.
One technique for implementing a stabilization period may be to exclude contact-agent interaction outcomes for the first portion of contacts after switching pairing strategies. For example, assume a contact center is benchmarking BP and FIFO with a 50% duty cycle over 30-minute periods. In the aforementioned embodiments (e.g.,
This pattern is illustrated in
In some embodiments, the stabilization period may be longer or shorter. In some embodiments, a stabilization period may be used in a FIFO-to-BP transition instead of, or in addition to, a BP-to-FIFO transition (or any transition between two different pairing strategies).
At this point it should be noted that behavioral pairing in a contact center system in accordance with the present disclosure as described above may involve the processing of input data and the generation of output data to some extent. This input data processing and output data generation may be implemented in hardware or software. For example, specific electronic components may be employed in a behavioral pairing module or similar or related circuitry for implementing the functions associated with behavioral pairing in a contact center system in accordance with the present disclosure as described above. Alternatively, one or more processors operating in accordance with instructions may implement the functions associated with behavioral pairing in a contact center system in accordance with the present disclosure as described above. If such is the case, it is within the scope of the present disclosure that such instructions may be stored on one or more non-transitory processor readable storage media (e.g., a magnetic disk or other storage medium), or transmitted to one or more processors via one or more signals embodied in one or more carrier waves.
The present disclosure is not to be limited in scope by the specific embodiments described herein. Indeed, other various embodiments of and modifications to the present disclosure, in addition to those described herein, will be apparent to those of ordinary skill in the art from the foregoing description and accompanying drawings. Thus, such other embodiments and modifications are intended to fall within the scope of the present disclosure. Further, although the present disclosure has been described herein in the context of at least one particular implementation in at least one particular environment for at least one particular purpose, those of ordinary skill in the art will recognize that its usefulness is not limited thereto and that the present disclosure may be beneficially implemented in any number of environments for any number of purposes. Accordingly, the claims set forth below should be construed in view of the full breadth and spirit of the present disclosure as described herein.
This application is a continuation of U.S. patent application Ser. No. 15/608,718, filed May 30, 2017, which is a continuation of U.S. patent application Ser. No. 15/131,915, filed Apr. 18, 2016, now U.S. Pat. No. 9,712,676, which is a continuation-in-part of U.S. patent application Ser. No. 12/021,251, filed Jan. 28, 2008, now U.S. Pat. No. 9,712,679, and is also a continuation-in-part of U.S. patent application Ser. No. 14/727,271, filed Jun. 1, 2015, which is a continuation of U.S. patent application Ser. No. 14/472,998, filed Aug. 29, 2014, now U.S. Pat. No. 9,215,323, which is a continuation of U.S. patent application Ser. No. 12/266,446, filed Nov. 6, 2008, now U.S. Pat. No. 8,824,658, each of which is hereby incorporated by reference in their entirety as if fully set forth herein.
Number | Name | Date | Kind |
---|---|---|---|
5155763 | Bigus et al. | Oct 1992 | A |
5206903 | Kohler et al. | Apr 1993 | A |
5327490 | Cave | Jul 1994 | A |
5537470 | Lee | Jul 1996 | A |
5702253 | Bryce et al. | Dec 1997 | A |
5825869 | Brooks et al. | Oct 1998 | A |
5903641 | Tonisson | May 1999 | A |
5907601 | David et al. | May 1999 | A |
5926538 | Deryugin et al. | Jul 1999 | A |
6049603 | Schwartz et al. | Apr 2000 | A |
6052460 | Fisher et al. | Apr 2000 | A |
6064731 | Flockhart et al. | May 2000 | A |
6088444 | Walker et al. | Jul 2000 | A |
6163607 | Bogart et al. | Dec 2000 | A |
6222919 | Hollatz et al. | Apr 2001 | B1 |
6292555 | Okamoto | Sep 2001 | B1 |
6324282 | McIllwaine et al. | Nov 2001 | B1 |
6333979 | Bondi et al. | Dec 2001 | B1 |
6389132 | Price | May 2002 | B1 |
6389400 | Bushey et al. | May 2002 | B1 |
6408066 | Andruska et al. | Jun 2002 | B1 |
6411687 | Bohacek et al. | Jun 2002 | B1 |
6424709 | Doyle et al. | Jul 2002 | B1 |
6434230 | Gabriel | Aug 2002 | B1 |
6496580 | Chack | Dec 2002 | B1 |
6504920 | Okon et al. | Jan 2003 | B1 |
6519335 | Bushnell | Feb 2003 | B1 |
6526135 | Paxson | Feb 2003 | B1 |
6535600 | Fisher et al. | Mar 2003 | B1 |
6535601 | Flockhart et al. | Mar 2003 | B1 |
6570980 | Baruch | May 2003 | B1 |
6587556 | Judkins et al. | Jul 2003 | B1 |
6603854 | Judkins et al. | Aug 2003 | B1 |
6639976 | Shellum et al. | Oct 2003 | B1 |
6661889 | Flockhart et al. | Dec 2003 | B1 |
6704410 | McFarlane et al. | Mar 2004 | B1 |
6707904 | Judkins et al. | Mar 2004 | B1 |
6714643 | Gargeya et al. | Mar 2004 | B1 |
6744878 | Komissarchik et al. | Jun 2004 | B1 |
6763104 | Judkins et al. | Jul 2004 | B1 |
6774932 | Ewing et al. | Aug 2004 | B1 |
6775378 | Villena et al. | Aug 2004 | B1 |
6798876 | Bala | Sep 2004 | B1 |
6829348 | Schroeder et al. | Dec 2004 | B1 |
6832203 | Villena et al. | Dec 2004 | B1 |
6859529 | Duncan et al. | Feb 2005 | B2 |
6922466 | Peterson et al. | Jul 2005 | B1 |
6937715 | Delaney | Aug 2005 | B2 |
6956941 | Duncan et al. | Oct 2005 | B1 |
6970821 | Shambaugh et al. | Nov 2005 | B1 |
6978006 | Polcyn | Dec 2005 | B1 |
7023979 | Wu et al. | Apr 2006 | B1 |
7039166 | Peterson et al. | May 2006 | B1 |
7050566 | Becerra et al. | May 2006 | B2 |
7050567 | Jensen | May 2006 | B1 |
7062031 | Becerra et al. | Jun 2006 | B2 |
7068775 | Lee | Jun 2006 | B1 |
7092509 | Mears et al. | Aug 2006 | B1 |
7103172 | Brown et al. | Sep 2006 | B2 |
7158628 | McConnell et al. | Jan 2007 | B2 |
7184540 | Dezonno et al. | Feb 2007 | B2 |
7209549 | Reynolds et al. | Apr 2007 | B2 |
7231032 | Nevman et al. | Jun 2007 | B2 |
7231034 | Rikhy et al. | Jun 2007 | B1 |
7236584 | Torba | Jun 2007 | B2 |
7245716 | Brown et al. | Jul 2007 | B2 |
7245719 | Kawada et al. | Jul 2007 | B2 |
7266251 | Rowe | Sep 2007 | B2 |
7269253 | Wu et al. | Sep 2007 | B1 |
7353388 | Gilman et al. | Apr 2008 | B1 |
7398224 | Cooper | Jul 2008 | B2 |
7593521 | Becerra et al. | Sep 2009 | B2 |
7676034 | Wu et al. | Mar 2010 | B1 |
7725339 | Aykin | May 2010 | B1 |
7734032 | Kiefhaber et al. | Jun 2010 | B1 |
7798876 | Mix | Sep 2010 | B2 |
7826597 | Berner et al. | Nov 2010 | B2 |
7864944 | Khouri et al. | Jan 2011 | B2 |
7899177 | Bruening et al. | Mar 2011 | B1 |
7916858 | Heller et al. | Mar 2011 | B1 |
7940917 | Lauridsen et al. | May 2011 | B2 |
7961866 | Boutcher et al. | Jun 2011 | B1 |
7995717 | Conway et al. | Aug 2011 | B2 |
8000989 | Kiefhaber et al. | Aug 2011 | B1 |
8010607 | McCormack et al. | Aug 2011 | B2 |
8094790 | Conway et al. | Jan 2012 | B2 |
8126133 | Everingham et al. | Feb 2012 | B1 |
8140441 | Cases et al. | Mar 2012 | B2 |
8175253 | Knott et al. | May 2012 | B2 |
8229102 | Knott et al. | Jul 2012 | B2 |
8249245 | Jay et al. | Aug 2012 | B2 |
8295471 | Spottiswoode et al. | Oct 2012 | B2 |
8300798 | Wu et al. | Oct 2012 | B1 |
8359219 | Chishti et al. | Jan 2013 | B2 |
8433597 | Chishti et al. | Apr 2013 | B2 |
8472611 | Chishti | Jun 2013 | B2 |
8565410 | Chishti et al. | Oct 2013 | B2 |
8634542 | Spottiswoode et al. | Jan 2014 | B2 |
8644490 | Stewart | Feb 2014 | B2 |
8670548 | Xie et al. | Mar 2014 | B2 |
8699694 | Chishti et al. | Apr 2014 | B2 |
8712821 | Spottiswoode | Apr 2014 | B2 |
8718271 | Spottiswoode | May 2014 | B2 |
8724797 | Chishti et al. | May 2014 | B2 |
8731178 | Chishti et al. | May 2014 | B2 |
8737595 | Chishti et al. | May 2014 | B2 |
8750488 | Spottiswoode et al. | Jun 2014 | B2 |
8761380 | Kohler et al. | Jun 2014 | B2 |
8781100 | Spottiswoode et al. | Jul 2014 | B2 |
8781106 | Afzal | Jul 2014 | B2 |
8792630 | Chishti et al. | Jul 2014 | B2 |
8824658 | Chishti | Sep 2014 | B2 |
8831207 | Agarwal | Sep 2014 | B1 |
8879715 | Spottiswoode et al. | Nov 2014 | B2 |
8903079 | Xie et al. | Dec 2014 | B2 |
8913736 | Kohler et al. | Dec 2014 | B2 |
8929537 | Chishti et al. | Jan 2015 | B2 |
8938063 | Hackbarth et al. | Jan 2015 | B1 |
8995647 | Li et al. | Mar 2015 | B2 |
9020137 | Chishti et al. | Apr 2015 | B2 |
9025757 | Spottiswoode et al. | May 2015 | B2 |
9215323 | Chishti | Dec 2015 | B2 |
9277055 | Spottiswoode et al. | Mar 2016 | B2 |
9300802 | Chishti | Mar 2016 | B1 |
9426296 | Chishti et al. | Aug 2016 | B2 |
9712676 | Chishti | Jul 2017 | B1 |
9712679 | Chishti et al. | Jul 2017 | B2 |
20010032120 | Stuart et al. | Oct 2001 | A1 |
20020018554 | Jensen et al. | Feb 2002 | A1 |
20020046030 | Haritsa et al. | Apr 2002 | A1 |
20020059164 | Shtivelman | May 2002 | A1 |
20020082736 | Lech et al. | Jun 2002 | A1 |
20020110234 | Walker et al. | Aug 2002 | A1 |
20020111172 | DeWolf et al. | Aug 2002 | A1 |
20020131399 | Philonenko | Sep 2002 | A1 |
20020138285 | DeCotiis et al. | Sep 2002 | A1 |
20020143599 | Nourbakhsh et al. | Oct 2002 | A1 |
20020161765 | Kundrot et al. | Oct 2002 | A1 |
20020184069 | Kosiba et al. | Dec 2002 | A1 |
20020196845 | Richards et al. | Dec 2002 | A1 |
20030002653 | Uckun | Jan 2003 | A1 |
20030081757 | Mengshoel et al. | May 2003 | A1 |
20030095652 | Mengshoel et al. | May 2003 | A1 |
20030169870 | Stanford | Sep 2003 | A1 |
20030174830 | Boyer et al. | Sep 2003 | A1 |
20030217016 | Pericle | Nov 2003 | A1 |
20040028211 | Culp et al. | Feb 2004 | A1 |
20040057416 | McCormack | Mar 2004 | A1 |
20040096050 | Das et al. | May 2004 | A1 |
20040098274 | Dezonno et al. | May 2004 | A1 |
20040101127 | Dezonno et al. | May 2004 | A1 |
20040109555 | Williams | Jun 2004 | A1 |
20040133434 | Szlam et al. | Jul 2004 | A1 |
20040210475 | Starnes et al. | Oct 2004 | A1 |
20040230438 | Pasquale et al. | Nov 2004 | A1 |
20040267816 | Russek | Dec 2004 | A1 |
20050013428 | Walters | Jan 2005 | A1 |
20050043986 | McConnell et al. | Feb 2005 | A1 |
20050047581 | Shaffer et al. | Mar 2005 | A1 |
20050047582 | Shaffer et al. | Mar 2005 | A1 |
20050071223 | Jain et al. | Mar 2005 | A1 |
20050129212 | Parker | Jun 2005 | A1 |
20050135593 | Becerra et al. | Jun 2005 | A1 |
20050135596 | Zhao | Jun 2005 | A1 |
20050187802 | Koeppel | Aug 2005 | A1 |
20050195960 | Shaffer et al. | Sep 2005 | A1 |
20050286709 | Horton et al. | Dec 2005 | A1 |
20060098803 | Bushey et al. | May 2006 | A1 |
20060110052 | Finlayson | May 2006 | A1 |
20060124113 | Roberts | Jun 2006 | A1 |
20060184040 | Keller et al. | Aug 2006 | A1 |
20060222164 | Contractor et al. | Oct 2006 | A1 |
20060233346 | McIlwaine et al. | Oct 2006 | A1 |
20060262918 | Karnalkar et al. | Nov 2006 | A1 |
20060262922 | Margulies et al. | Nov 2006 | A1 |
20070036323 | Travis | Feb 2007 | A1 |
20070071222 | Flockhart et al. | Mar 2007 | A1 |
20070116240 | Foley et al. | May 2007 | A1 |
20070121602 | Sin et al. | May 2007 | A1 |
20070121829 | Tal et al. | May 2007 | A1 |
20070136342 | Singhai et al. | Jun 2007 | A1 |
20070154007 | Bernhard | Jul 2007 | A1 |
20070174111 | Anderson et al. | Jul 2007 | A1 |
20070198322 | Bourne et al. | Aug 2007 | A1 |
20070219816 | Van Luchene et al. | Sep 2007 | A1 |
20070274502 | Brown | Nov 2007 | A1 |
20080002823 | Fama et al. | Jan 2008 | A1 |
20080008309 | Dezonno et al. | Jan 2008 | A1 |
20080046386 | Pieraccinii et al. | Feb 2008 | A1 |
20080065476 | Klein et al. | Mar 2008 | A1 |
20080118052 | Houmaidi et al. | May 2008 | A1 |
20080144803 | Jaiswal et al. | Jun 2008 | A1 |
20080152122 | Idan et al. | Jun 2008 | A1 |
20080181389 | Bourne et al. | Jul 2008 | A1 |
20080199000 | Su et al. | Aug 2008 | A1 |
20080205611 | Jordan et al. | Aug 2008 | A1 |
20080267386 | Cooper | Oct 2008 | A1 |
20080273687 | Knott et al. | Nov 2008 | A1 |
20090043670 | Johansson et al. | Feb 2009 | A1 |
20090086933 | Patel et al. | Apr 2009 | A1 |
20090190740 | Chishti et al. | Jul 2009 | A1 |
20090190743 | Spottiswoode | Jul 2009 | A1 |
20090190744 | Xie et al. | Jul 2009 | A1 |
20090190745 | Xie et al. | Jul 2009 | A1 |
20090190746 | Chishti et al. | Jul 2009 | A1 |
20090190747 | Spottiswoode | Jul 2009 | A1 |
20090190748 | Chishti et al. | Jul 2009 | A1 |
20090190749 | Xie et al. | Jul 2009 | A1 |
20090190750 | Xie et al. | Jul 2009 | A1 |
20090232294 | Xie et al. | Sep 2009 | A1 |
20090234710 | Belgaied Hassine et al. | Sep 2009 | A1 |
20090245493 | Chen et al. | Oct 2009 | A1 |
20090304172 | Becerra et al. | Dec 2009 | A1 |
20090305172 | Tanaka et al. | Dec 2009 | A1 |
20090318111 | Desai et al. | Dec 2009 | A1 |
20090323921 | Spottiswoode et al. | Dec 2009 | A1 |
20100020959 | Spottiswoode | Jan 2010 | A1 |
20100020961 | Spottiswoode | Jan 2010 | A1 |
20100054431 | Jaiswal et al. | Mar 2010 | A1 |
20100054452 | Afzal | Mar 2010 | A1 |
20100054453 | Stewart | Mar 2010 | A1 |
20100086120 | Brussat et al. | Apr 2010 | A1 |
20100111285 | Chishti | May 2010 | A1 |
20100111286 | Chishti | May 2010 | A1 |
20100111287 | Xie et al. | May 2010 | A1 |
20100111288 | Afzal et al. | May 2010 | A1 |
20100142698 | Spottiswoode et al. | Jun 2010 | A1 |
20100158238 | Saushkin | Jun 2010 | A1 |
20100183138 | Spottiswoode et al. | Jul 2010 | A1 |
20110022357 | Vock et al. | Jan 2011 | A1 |
20110031112 | Birang et al. | Feb 2011 | A1 |
20110069821 | Korolev et al. | Mar 2011 | A1 |
20110125048 | Causevic et al. | May 2011 | A1 |
20120051536 | Chishti et al. | Mar 2012 | A1 |
20120051537 | Chishti et al. | Mar 2012 | A1 |
20120224680 | Spottiswoode et al. | Sep 2012 | A1 |
20120278136 | Flockhart et al. | Nov 2012 | A1 |
20130003959 | Nishikawa et al. | Jan 2013 | A1 |
20130051545 | Ross et al. | Feb 2013 | A1 |
20130251137 | Chishti et al. | Sep 2013 | A1 |
20130287202 | Flockhart et al. | Oct 2013 | A1 |
20140044246 | Klemm et al. | Feb 2014 | A1 |
20140079210 | Kohler et al. | Mar 2014 | A1 |
20140119531 | Tuchman et al. | May 2014 | A1 |
20140119533 | Spottiswoode et al. | May 2014 | A1 |
20140341370 | Li et al. | Nov 2014 | A1 |
20150055772 | Klemm et al. | Feb 2015 | A1 |
20150281448 | Putra et al. | Oct 2015 | A1 |
20160080573 | Chishti | Mar 2016 | A1 |
Number | Date | Country |
---|---|---|
2008349500 | May 2014 | AU |
2009209317 | May 2014 | AU |
2009311534 | Aug 2014 | AU |
102164073 | Aug 2011 | CN |
102301688 | May 2014 | CN |
102017591 | Nov 2014 | CN |
0 493 292 | Jul 1992 | EP |
0 949 793 | Oct 1999 | EP |
1 032 188 | Aug 2000 | EP |
1335572 | Aug 2003 | EP |
11-098252 | Apr 1999 | JP |
2000-069168 | Mar 2000 | JP |
2000-078291 | Mar 2000 | JP |
2000-078292 | Mar 2000 | JP |
2000-092213 | Mar 2000 | JP |
2000-507420 | Jun 2000 | JP |
2000-236393 | Aug 2000 | JP |
2000-253154 | Sep 2000 | JP |
2001-292236 | Oct 2001 | JP |
2001-518753 | Oct 2001 | JP |
2002-297900 | Oct 2002 | JP |
3366565 | Jan 2003 | JP |
2003-187061 | Jul 2003 | JP |
2004-056517 | Feb 2004 | JP |
2004-227228 | Aug 2004 | JP |
2006-345132 | Dec 2006 | JP |
2007-324708 | Dec 2007 | JP |
2009-081627 | Apr 2009 | JP |
2011-511533 | Apr 2011 | JP |
2011-511536 | Apr 2011 | JP |
2012-075146 | Apr 2012 | JP |
5421928 | Feb 2014 | JP |
5631326 | Nov 2014 | JP |
5649575 | Jan 2015 | JP |
2015-514371 | May 2015 | JP |
316118 | Dec 2013 | MX |
322251 | Jul 2014 | MX |
587100 | Oct 2013 | NZ |
587101 | Oct 2013 | NZ |
591486 | Jan 2014 | NZ |
592781 | Mar 2014 | NZ |
1-2010-501704 | Feb 2014 | PH |
1-2010-501705 | Feb 2015 | PH |
WO-1999017517 | Apr 1999 | WO |
WO-2001063894 | Aug 2001 | WO |
WO-2006124113 | Nov 2006 | WO |
WO-2009097018 | Aug 2009 | WO |
WO-2010053701 | May 2010 | WO |
WO-2011081514 | Jul 2011 | WO |
Entry |
---|
Afiniti, “Afiniti® Enterprise Behavioral Pairing™ Improves Contact Center Performance,” White Paper, retreived online from URL: <http://www.afiniti.com/wp-content/uploads/2016/04/Afiniti_White-Paper_Web-Email.pdf> 11 pages (2016). |
Anonymous. (2006) “Performance Based Routing in Profit Call Centers,” The Decision Makers' Direct, located at www.decisioncraft.com, Issue Jun. 2002 (3 pages). |
Canadian Office Action issued in Canadian Patent Application No. 2713526, dated Oct. 25, 2016, 7 pages. |
Cleveland, William S., “Robust Locally Weighted Regression and Smoothing Scatterplots,” Journal of the American Statistical Association, vol. 74, No. 368, pp. 829-836 (Dec. 1979). |
Extended European Search Report issued by the European Patent Office for European Application No. 17154781.3 dated May 4, 2017 (7 pages). |
Extended European Search Report issued by the European Patent Office for European Application No. 17171761.4 dated Aug. 30, 2017 (8 pages). |
Gans, N. et al. (2003), “Telephone Call Centers: Tutorial, Review and Research Prospects,” Manufacturing & Service Operations Management, vol. 5, No. 2, pp. 79-141, 84 pages. |
International Preliminary Report on Patentability issued in connection with PCT Application No. PCT/US2009/066254 dated Jun. 14, 2011 (6 pages). |
International Search Report and Written Opinion issued by the European Patent Office as International Searching Authority for International Application No. PCT/IB2016/001762 dated Feb. 20, 2017 (15 pages). |
International Search Report and Written Opinion issued by the European Patent Office as International Searching Authority for International Application No. PCT/IB2016/001776 dated Mar. 3, 2017 (16 pages). |
International Search Report and Written Opinion issued by the European Patent Office as International Searching Authority for International Application No. PCT/IB2017/000570 dated Jun. 30, 2017 (13 pages). |
International Search Report issued in connection with International Application No. PCT/US13/33268 dated May 31, 2013 (2 pages). |
International Search Report issued in connection with PCT Application No. PCT/US/2009/054352 dated Mar. 12, 2010, 5 pages. |
International Search Report issued in connection with PCT Application No. PCT/US2008/077042 dated Mar. 13, 2009 (3 pages). |
International Search Report issued in connection with PCT Application No. PCT/US2009/031611 dated Jun. 3, 2009 (5 pages). |
International Search Report issued in connection with PCT Application No. PCT/US2009/066254 dated Feb. 24, 2010 (4 pages). |
International Search Report issued in connection with PCT/US2009/061537 dated Jun. 7, 2010 (5 pages). |
International Search Report issued in connection with PCT/US2013/033261 dated Jun. 14, 2013 (3 pages). |
International Search Report issued in connection with PCT/US2013/33265 dated Jul. 9, 2013 (2 pages). |
Japanese Office Action issued by the Japan Patent Office for Application No. 2015-503396 dated Jun. 29, 2016 (7 pages). |
Japanese Office Action issued by the Japanese Patent Office for Japanese Application No. 2016-159338 dated Oct. 11, 2017 (12 pages). |
Japanese Office Action issued by the Japanese Patent Office for Japanese Application No. 2016-189126 dated Oct. 19, 2017 (24 pages). |
Koole, G. (2004). “Performance Analysis and Optimization in Customer Contact Centers,” Proceedings of the Quantitative Evaluation of Systems, First International Conference, Sep. 27-30, 2004 (4 pages). |
Koole, G. et al. (Mar. 6, 2006). “An Overview of Routing and Staffing Algorithms in Multi-Skill Customer Contact Centers,” Manuscript, 42 pages. |
Ntzoufras, “Bayesian Modeling Using Winbugs”. Wiley Interscience, Chapter 5, Normal Regression Models, Oct. 18, 2007, pp. 155-220 (67 pages). |
Press, W. H. and Rybicki, G. B., “Fast Algorithm for Spectral Analysis of Unevenly Sampled Data,” The Astrophysical Journal, vol. 338, pp. 277-280 (Mar. 1, 1989). |
Riedmiller, M. et al. (1993). “A Direct Adaptive Method for Faster Back Propagation Learning: The RPROP Algorithm,” 1993 IEEE International Conference on Neural Networks, San Francisco, CA, Mar. 28-Apr. 1, 1993, 1:586-591. |
Stanley et al., “Improving call center operations using performance-based routing strategies,” Calif. Journal of Operations Management, 6(1), 24-32, Feb. 2008; retrieved from http://userwww.sfsu.edu/saltzman/Publist.html. |
Subsequent Substantive Examination Report issued in connection with Philippines Application No. 1-2010-501705 dated Jul. 14, 2014 (1 page). |
Substantive Examination Report issued in connection with Philippines Application No. 1/2011/500868 dated May 2, 2014 (1 page). |
Written Opinion of the International Searching Authority issued in connection with International Application No. PCT/US13/33268 dated May 31, 2013, 7 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT Application No. PCT/US/2009/054352 dated Mar. 12, 2010, 5 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT Application No. PCT/US2008/077042 dated Mar. 13, 2009, 6 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT Application No. PCT/US2009/031611 dated Jun. 3, 2009, 7 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT Application No. PCT/US2009/066254 dated Feb. 24, 2010, 5 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT/US2009/061537 dated Jun. 7, 2010, 10 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT/US2013/033261 dated Jun. 14, 2013, 7 pages. |
Written Opinion of the International Searching Authority issued in connection with PCT/US2013/33265 dated Jul. 9, 2013, 7 pages. |
Extended European Search Report issued by the European Patent Office for European Application No. 18168620.5 dated Jun. 12, 2018 (9 pages). |
Canadian Office Action issued by the Canada Intellectual Property Office for Canadian Application No. 2,993,380 dated Nov. 27, 2018 (5 pages). |
Notice of Reasons for Rejection issued by the Japan Patent Office for Japanese Application No. 2018-528305 dated Oct. 17, 2018 (6 pages). |
Notice of Reasons for Rejection issued by the Japan Patent Office for Japanese Application No. 2018-528314 dated Oct. 17, 2018 (5 pages). |
Notification of First Office Action issued by the China National Intellectual Property Administration for Chinese Application No. 201680070038.3 dated Nov. 26, 2018 (26 pages). |
Notice of Reasons for Rejection issued by the Japan Patent Office for Japanese Application No. 2017-514350 dated Dec. 5, 2018 (12 pages). |
Extended European Search Report dated Mar. 29, 2019 received in related European Patent Application No. 18212022.0 (10 pages). |
Extended European Search Report dated Mar. 21, 2019 received in related European Patent Application No. 18211783.8 (9 pages). |
Extended European Search Report dated Mar. 20, 2019 received in related European Patent Application No. 18211624.4 (9 pages). |
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