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The history of call centers, or how technology has changed the way operators work with customers

It is generally accepted that call centers are simply rooms where operators sit at computers and communicate with customers over the telephone. This is partly true,  call center technology but agents of modern contact centers use a larger number of channels for interacting with users (for example, instant messengers and social networks). Moreover, they are increasingly being helped by modern technologies, including machine learning and data analysis algorithms.

When the first contact centers appeared, what has changed since they first appeared and what artificial intelligence (AI) systems have to do with the “evolution of call centers” are described below.

How call centers came about

The first automatic call distribution (ACD) systems appeared in the 50s of the last century. They were used by operators of several large telephone companies. However, it is believed that the first “real” contact center appeared in 1965 in Britain. Then the telephone company The Birmingham Press and Mail established the telephone exchange GEC PABX 4 . The station automatically distributed incoming and outgoing calls.

The first contact center in America was organized advanced call center technologies llc. Continental Airlines became its first customer by organizing a ticket reservation service for passengers.

In the Soviet Union, call centers appeared in the 70s. One of the first Contact centers in the USSR became the reference service of the Kiev telephone network. It was possible to call her at number “09” and find out the desired phone. Part of the communication center was responsible for the telephone numbers of enterprises, while the other “specialized” in the apartments of Kiev residents.

Until the 80s, call centers were “connected” to telephone networks by analog lines. But later, digital technology began to influence the industry. The first wave of digitalization was the emergence of the DASS II protocol (Digital Access Signalling System). It was developed in the telecommunications company British Telecom. DASS II systems allowed to exchange data at a speed of 2 Mbit / s and manage 30 calls simultaneously (64 Kbit / s for each).

With the development of technology, IP-telephony has appeared. The first Internet phone for a wide consumer was created by the Israeli company VocalTec . Users could call each other using special software. They communicated using speakers and a computer microphone. But already in 1998, VocalTec implemented VoIP functions for computer-to-telephone and telephone-to-telephone connections.

At the beginning of the “zero” companies involved in the production of telephone and telecommunications equipment, realized all the advantages that IP-telephony provides. They began to add VoIP functions to switches, software, etc. By 2003, 25% of all calls were made using IP.

Thanks to this technology, software solutions appeared that allowed call center operators to integrate with third-party business systems: service desk, CRM, and billing. This made it possible to display on the monitor screen all the information about the client, his profile, at the time of receiving the call. This approach improved the quality and reduced the time of service in contact centers, and also opened new channels for them to work with customers.

How technology development has impacted call centers

Since, with the development of the Internet, communication for the most part goes into virtual space, new channels for working with clients appear. As noted , for example, in the Yota provider, 89% of calls to their support center are from a mobile application, chat on the site, SMS chat, social networks, and email.

This is due to the fact that people began to use digital channels more actively. Moreover, it is natural that chats and instant messengers are used not only for communication, but also for teamwork and professional self-development.

For example, on the network you can find special chats for developers who exchange knowledge and experience. In particular, Python IRC channels on FreeNode: python and python-dev . Another option is the servers in the Discord messenger: The Programmer’s Hangout and Reactiflux . The first is devoted to general programming issues, the last is React JS, Redux, GraphQL, etc.

The popularity of text messaging services, as expected, has led contact centers to embed chats in their business processes. This made it possible to “speak the same language with customers” and solve problems, without forcing people to wait on line waiting for a free operator. It also made it possible to use one of the obvious advantages of instant messengers – chat bots. They “learned” to independently solve frequently arising problems and involve operators only in difficult cases.

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As for other methods of communication, social networks are another channel of communication with customers. In social media, companies get the opportunity to collect feedback about their work. For example, a few years ago, Apple launched A tech support Twitter account so users can access them directly and publicly.

True, in Russia the practice of working with social networks is less common than abroad. From our own experience, we see that most calls are still received in voice. But the industry is gradually realizing the importance of providing many service channels in call centers, because companies are moving to the so-called omnichannel model of work.

The essence of the omnichannel approach is to create a single environment for all channels (calls, social networks, instant messengers, etc.) and save the history of communication with the client. A person can start talking on the phone, then continue chatting and so on. Changing operators will know all the information received from the user in the previous steps.

An example of such a platform is the Naumen Omni-Channel . The system works with phone calls, web chats and instant messengers (Viber, Telegram, etc.), as well as social networks Facebook and VK. Calls from all channels are arranged in a single queue, inside which a certain number of “mini-queues” are created.

From these queues, tasks are automatically distributed between operators according to predefined rules. For example, the busyness of operators, the presence of the required skills, the speed of processing instant messages, and the topic of treatment can be taken into account. The latter is established by analyzing keywords.

As an example omnikanalnoy model of work can lead case of the construction trading house “Petrovich”. At the end of last year, they took second place in revenue in Russia, losing only to Leroy Merlin. To contact the company’s call center, customers can use several channels: allow by phone, send an e-mail or request a call back. At the same time, the history of work with the subscriber is saved by the system for analyzing customer experience.

Aggregation and analysis of a wide variety of information related to the rules of operators, their skills, statistics, etc., allowed to develop the capabilities of call centers in terms of integration with WFM systems. Forecasting and planning the workload of staff in an automated form have also become important tools for managing a modern contact center. For example, the possibility of omnikanalnyh systems and WFM-function uses one of Russia’s largest outsourcing contact centers GRAND . The company is included in the top 5 ACCs in terms of the volume of services provided and has five sites with 1,700 operators.

In general, omnichannelism is a promising direction. Therefore, contact centers of the future should not only be able to work with all existing channels, but also be ready to “accept” new ones.

It is expected that assistants like Siri, Cortana, Alexa will become another new channel. In this case, the call center will have to process information not from the client, but from his robotic assistant. Such a scenario is quite likely, given how actively this area is developing.

Google, for example, recently introduced the Duplex solution. It can call various organizations and carry out instructions, for example, book a table in a restaurant. At the presentation, Google Assistant called the real beauty salon and booked a time for a haircut. The salon administrator did not even suspect that he had a dialogue with the machine (you can find the video here ).

Actively moving in this direction is Yandex, which recently introduced its voice assistant and, accordingly, a column for it. We believe that such decisions will “conquer” the mass market in the next 5–10 years.

How robotic systems help respond to customer requests

One of the popular technologies that have found application in contact centers today are machine learning algorithms (MOs). They allow you to create robotic services, including complex chat bots that can act as a full-fledged first line of support.

In particular, a voice bot has been implemented for the Russian Post company, which uses natural speech recognition algorithms (NLP) to determine the subject of a client’s appeal. If earlier the client had to go to a large and confusing IVR-menu and, in essence, classify himself, now he is free to pronounce topics of interest to him, and then the robot redirects the call to the desired line. Thus, the possibility of free communication with the robot remains – there is no need to waste time and wander around the long and confusing IVR.

Moreover, if the client says: “Good afternoon, I would like to know where my package is now,” the robot will provide him with information about the status of the mail (or transfer the call to the appropriate service). The robot can recognize the track numbers of parcels pronounced in various ways. Including unusual. For example, he can recognize the RS250028 combination, even if it was called like this: “Roman, Sergey, twenty-five, two zeros, two, eight.”

As technology advances, the introduction of such systems ceases to be costly and cumbersome. Today, such systems are available not only for large organizations with huge client bases. Robotic solutions also benefit relatively small companies. For example, we at Naumen worked on a solution for OMSK RTS, a regional electric and heat energy company. Using a robotic service, its customers can transmit meter readings automatically by phone. The service successfully serves nearly 90% of users. The active phase of the project took only 1 month.

But although AI systems can improve the user experience, they are still not able to resolve conflicts. Therefore, today they are developing and so-called hybrid AI systems are being introduced. They receive all the necessary information from the client, and then imperceptibly and “seamlessly” transfer “control” to the call center operator.

An example of developments in this area is the LiveEngage platform, which works in conjunction with the IBM Watson supercomputer. Watson “communicates” with customers, collects data, and reports it to a human agent if the latter requires intervention. This system is already in use in more than 45 countries in 20 industries.

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