Since their introduction in the 1990s, call optimisation techniques (previously referred to as “best time to call”) have evolved into integrated solutions that analyse a wide spectrum of input factors, then build and execute automated, repeatable strategies based on the analysis’ results, says Ebrahim Dinat, chief operating officer of specialist contact centre solutions and services provider, Ocular Technologies.
In order to achieve faster list penetration and higher right party contact rates, today’s call optimisation solutions utilise a special heuristic scheduling algorithm to achieve the greatest increase in productivity possible within an individual contact centre environment.
These call optimisation solutions dynamically learn from the feedback generated from call activities and continually optimise and fine-tune calling strategies. The net result of improved performance can benefit every type of customer service, collections, or telemarketing contact centre – whether the staff complement is large or small, or the accounts number in the thousands or the hundreds of thousands.
In order for the solution’s algorithm to execute effectively, it needs to operate off several internal data sets that work in conjunction with user-defined rules to increase the probability of a successful contact on each dialling attempt.
The internal data that is used within the call centre optimisation solution includes the accounts’ phone numbers to be processed for calling and internal probability variables that have been calculated based on historical trends.
These inputs work in co-operation with the user-defined rules, parameters and filters to create dialling strategies, tailor-made for the business’ process flow and goals, that enable users to reach the right person at the right time at the right number.
While user defined priority parameters prioritise accounts within their best times to call, some call optimisation solutions also allow for the simultaneous use of multiple, weighted parameters to adjust strategies. In addition to priority parameters, filters can be applied to certain data fields, which can include or exclude accounts from being dialled, in order to build a call list for the business’ current needs.
The user can also configure how they want accounts to be redialled. However, if there is a scheduled call-back that goes unanswered, the call optimisation solution identifies the failed recall and evaluates the record to determine the next best time and number to call.
Management tools within call centre optimisations solutions allow contact centre management to specify staffing levels for the day, even by the hour, which enables the solution to effectively calculate the workload and the number of records required to be delivered each hour to each consultant.
During the day, if the staff levels change, these inputs can be modified and a re-optimisation can be run, allowing management to react to intraday changes and still optimise productivity.
Finally, sophisticated call optimisation solutions also employ demographics-based behaviour models, which come online when an unfamiliar account appears. When there is no internal data or user defined rules to fall back on, these models improve the chance of determining the best time to call an account versus relying solely on an algorithm.
Call optimisation solutions are nothing new. They are proven techniques and strategies that are working well in “best of class” call centre operations around the globe. They form part of the strategies needed to optimise a call centre’s workforce today in these tough economic times, and to position the call centre for continued success in the good times that are ahead.
In order to achieve faster list penetration and higher right party contact rates, today’s call optimisation solutions utilise a special heuristic scheduling algorithm to achieve the greatest increase in productivity possible within an individual contact centre environment.
These call optimisation solutions dynamically learn from the feedback generated from call activities and continually optimise and fine-tune calling strategies. The net result of improved performance can benefit every type of customer service, collections, or telemarketing contact centre – whether the staff complement is large or small, or the accounts number in the thousands or the hundreds of thousands.
In order for the solution’s algorithm to execute effectively, it needs to operate off several internal data sets that work in conjunction with user-defined rules to increase the probability of a successful contact on each dialling attempt.
The internal data that is used within the call centre optimisation solution includes the accounts’ phone numbers to be processed for calling and internal probability variables that have been calculated based on historical trends.
These inputs work in co-operation with the user-defined rules, parameters and filters to create dialling strategies, tailor-made for the business’ process flow and goals, that enable users to reach the right person at the right time at the right number.
While user defined priority parameters prioritise accounts within their best times to call, some call optimisation solutions also allow for the simultaneous use of multiple, weighted parameters to adjust strategies. In addition to priority parameters, filters can be applied to certain data fields, which can include or exclude accounts from being dialled, in order to build a call list for the business’ current needs.
The user can also configure how they want accounts to be redialled. However, if there is a scheduled call-back that goes unanswered, the call optimisation solution identifies the failed recall and evaluates the record to determine the next best time and number to call.
Management tools within call centre optimisations solutions allow contact centre management to specify staffing levels for the day, even by the hour, which enables the solution to effectively calculate the workload and the number of records required to be delivered each hour to each consultant.
During the day, if the staff levels change, these inputs can be modified and a re-optimisation can be run, allowing management to react to intraday changes and still optimise productivity.
Finally, sophisticated call optimisation solutions also employ demographics-based behaviour models, which come online when an unfamiliar account appears. When there is no internal data or user defined rules to fall back on, these models improve the chance of determining the best time to call an account versus relying solely on an algorithm.
Call optimisation solutions are nothing new. They are proven techniques and strategies that are working well in “best of class” call centre operations around the globe. They form part of the strategies needed to optimise a call centre’s workforce today in these tough economic times, and to position the call centre for continued success in the good times that are ahead.