Nikolay is an industry veteran with 20 years experience in contact center technologies, author of numerous patents, technical and research papers.
Before Bright Pattern Nikolay worked for Genesys Telecommunication Labs, Alcatel-Lucent, FrontRange Solutions, Five9.
Nikolay was a Head of Laboratory at Institute for Automation and Control Processes, Russian Academy of Sciences for 19 years.
Here at Bright Pattern Nikolay is in charge of intellectual property portfolio. He conducts research in contact center technologies including outbound dialing, natural language processing and machine learning, multimedia channels.
In a modern multi-channel contact center agents should have the ability to handle several customer interactions simultaneously. Indeed, some interactions do not fully occupy the agent’s capacity and leave some room for other activities. Let’s consider a situation where an agent is handling an email message from a customer.
A retrospective look at the evolution of communications technology in contact centers. Overview of the evolution of communication means between customers and businesses, the associated technologies, and the demands this change is placing on people and resources.
Agent capacity model will help you to route several multichannel interactions to one agent. In this article we will answer all of these questions and introduce a logical mechanism known in the contact center industry as Agent Capacity Model, enabling us to solve all of these problems.
Overview of the evolution of communication means between customers and businesses, the associated technologies, and the demands this change is placing on people and resources.
An agent capacity model will help you to route several multichannel interactions to one agent. Guess how many customer interactions a contact center agent can handle simultaneously?
The WFM Calculator evaluates the number of agents needed to handle customer calls in an inbound call center. The key advantage of the calculator is accounting for abandonment rate. This feature works when traditional Erlang-C calculators will not help.
I present a visual simulation model of Erlang A. The model describes a basic process and could be served as starting point for more sophisticated call center models such as multi-campaign environment, outbound dialing, multi-skilled agents, etc. Moreover it can be adopted for more realistic distribution functions where no analytical solution exists.
United States 8,699,699
Issued April 15, 2014
A method for determining a number of calls to generate for a specific outbound campaign in an automated contact center based upon a prediction of agent occupancy in a future time period, wherein the automated contact center processes one or more outbound campaigns. The estimates a total number of outbound agents available to the one or more outbound campaigns.
United States 8,654,963
Issued February 18, 2014
In a contact center, a system for processing communication events has an interaction server for managing events waiting to be routed, a routing server for routing the events, a rules engine, and a gateway server executing rules invocation logic and interacting with the rules engine.
United States 8,582,752
Issued November 12, 2013
A method for determining a number of calls to generate in an automated contact center based upon a prediction of agent occupancy in a future time period. The automated contact center comprises a dialer for dialing generated calls, a queue where successfully connected dialed calls await agent handling, and an agent pool where calls are handled by agents.
United States 8,411,844
Issued April 2, 2013
A method for controlling and correcting abandonment rate in an automated contact center that uses a predictive dialing method for determining a number of calls to generate for dialing. When abandonment rate is close to zero, the method determines a mean agent occupancy that is used by the predictive dialing method.
United States 8,345,856
Issued January 1, 2013
A method for determining a number of calls to generate in an automated contact center, wherein the automated contact center comprises a dialer for dialing generated calls and an agent pool where successfully connected dialed calls are handled by agents. The method collects empirical data on durations in which calls spend in the dialer and agent handling times.