B2C Call Center Technology Trends - Mobile, Cloud, AI and More ...

Will Artificial Intelligence ultimately replace human agents in the centers? Does crowdsourcing agents really work? How is mobile and clound impacting call center operations? In our blog we focus on the latest trending technologies and tools used by call centers around the world.

Artificial Intelligence Technologies in Call Center

Almost 50 years ago when IVR (Interactive Voice Response) was gaining popularity, people thought it was going to cut down labor force significantly in call centers. It did help increase the operational efficiency significantly but IVR in no way replaced or will replace human agent on the other end of the line. In the past 10 years, Artificial Intelligence, especially so called Deep Learning is reshaping how companies deal with the huge amount of data they collect from the interactions and transactions with customers. Below are a few examples how call centers are or will benefit from the advancement in new technologies.

Fraud Detection - Pindrop (https://www.pindrop.com)

Their technology identifies suspicious callers on the first call using a multi-factor analysis engine and adaptive machine-learning technology. Here is an excerpt from the webiste - "Pindrop provides enterprise solutions to secure phone and voice communications. Pindrop solutions reduce fraud losses and authentication expense for some of the largest call centers in the world. Pindrop’s patented Phoneprinting technology can identify, locate and authenticate phone devices uniquely just from the call audio thereby detecting fraudulent calls as well as verifying legitimate callers. Pindrop has been selected by the world’s largest banks, insurers, brokerages and retailers, detecting over 80% of fraud, even for attackers never seen before. Our solutions are allowing our customers to reduce call time and improve their customers experience even while reducing fraud losses. Pindrop is restoring confidence in the security of phone-based transactions.". 

Language Transation - Google

The latest Deep Learning technology has been applied to various areas, such as Autonomous Driving. NPL (Natural Language Processing) is another hot area where DL is applied. In 2016, Google published their results (https://research.googleblog.com/2016/09/a-neural-network-for-machine.html). Its accuracy and performance has significant improvements over the previous results. Imagine in the future, an agent speaking Japanese can assist customers speaking English. In-between the machine translate in real time in audio and both parties don't either notice they are talking to someone speaking a different language!

Emotion Analytics - BeyondVerbal (http://www.beyondverbal.com/)

"Your call is very important to us. Please wait". Who likes to call customer service and be put on hold for 30 minutes with the boring background music? I don't. Plus when a customer needs to talk to an agent, it is very likely about some trouble in the product or service. A few years ago there were companies starting offering solutions to analyze the voice recordings and identify pieces that the managers should pay close attention. By doing so, they may be able to save an unsatisfied customer from leaving and also identify the 'bad apples' in the agents. With the advancement of NLP and Deep Learning, this area is ready to benefit significantly. Imagine that the machine can actually 'understand' the conversation and notify the manager if attention is needed. 

Will Machine Replace Human Agents in Call Centers One Day?

The answer is YES. But when? If I have to guess, I'd say at least 50 years. Here is why -  Artificial Intelligence today can recognize patterns in a way that even human may not be capable of, but being able to reasoning is the key of true intelligence. Remember it took about 50 years for Neural Network to evolve into Deep Learning and gain popularity in industries. We are not there yet to make machines that can reason. Researchers have started working on this topic but so far the results are very limited. So for people who work in call centers, no need to worry about it.

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