The modern contact centre: how AI is shaping customer service

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Customer service is changing beyond recognition. Traditional call centres are losing value and appeal for consumers forced to endure long waits, hold times and insufficient service. Now, new and improved corporate communication solutions are changing the face of modern customer service.

In fact, more organisations are placing digitally-enabled solutions, such as AI-powered chatbots, at the core of their communications strategy. According to recent Oracle research, more than three quarters of brands are expected to leverage AI capabilities for customer service by 2020. Accenture has estimated that the introduction of AI will increase business productivity by up to 80% by 2035.

And it’s easy to see why. Through implementation of AI solutions, organisations can not only build more personalised, immediate and intuitive communication experiences, they can also dramatically boost the efficiency of their contact centres by providing their agents with more insightful direction. Further, the information gained about customers as well as agents in the process, provides powerful insight into chosen strategies and the performance of a company.

As the advantages of implementing modern solutions are simply too powerful to ignore, cloud communication providers are constantly working on improving cloud-scale programmable solutions; and the sophistication of features is already showing why customer service is one of the business functions expected to benefit most from AI.

Voice bots as a first point of contact

Modern contact centres need to properly address the increasing demands of their customers. From avoiding long hold and wait times, to directing customers to the appropriate representative without having to speak to several agents, customer expectations are constantly evolving.

Thanks to natural language processing and rules-based systems, AI can detect certain words to determine what exactly is needed. Voice-enabled bots can provide real-time data to provide contextually relevant answers, and subsequently transfer the customer to the most qualified live agent. Not only can voice bots provide customers with sufficient self-service options to handle less complicated requests, they also free up resources, providing agents with more time to handle complex issues.

Simply put, bots are great at executing simple requests and carrying out programmed tasks, but their abilities decrease with the increasing complexity of requests. After all, some questions simply cannot be resolved without the help of an agent. On top of that, we’re still human and crave advice and help when making a decision; the personal touch of talking to someone on the phone can’t be replaced by texting, messaging or voice-enabled bots.

While voice-bot technology can provide an excellent first point of contact as well as handling simpler requests, some customers will be reluctant to adopt modern technologies and prefer the convenience speaking directly to a representative of the customer care team. Some may prefer to wait in a queue than having to deal with impersonal voice bot technology. Thus, contact centres should always offer their customers a way to directly connect to a representative of their service team at any point of the call.

Sentiment analysis to address emotion

The best customer service starts with an understanding of a customer’s request, and then providing the very best guidance. However, in noisy and fast-paced contact centre environments, the subtle clues of a customer’s dissatisfaction can easily be misheard or misunderstood. On top of that, customers’ expectations are constantly increasing as they’re looking for faster and more efficient solutions to handle requests.

To help contact centres properly tackle this challenge, real-time sentiment analysis can be a powerful tool to prevent deterioration of customer-agent relationships. This programmable feature provides agents with real-time insight on their customer’s experience, indicating how satisfied or unsatisfied the customer is throughout the conversation. Based on this insight, agents can rapidly change their approach, and adjust their tone and messaging.

Most importantly, the integration can be used to notify a superior if a certain thresholds are crossed, allowing them to intervene when necessary and save time and energy for both the agent and customer.

Split recording to avoid audio ambiguity

By implementing split recording, businesses can make a significant step towards better understanding the requests of their customers, as well as making sure new information is actionable. When calls are recorded in mono, only the human ear can manage to differentiate the participants based on the unique sound of their voices, but when it comes to machines, it’s simply not that easy.

Split recording tackles this issue by recording both participants in stereo, in two different channels: one creates a recording of what the participants hears, and the other channel records what the participant says. This feature is especially helpful when participants accidentally speak over each other.

With this clear distinction of channels, the playback is not only easier for machine to understand, but also the agent as well. Further, if businesses use transcription services, the resulting transcripts will be much more accurate and provide actionable insights. Additionally, recordings and transcripts can be used to better analyse a company’s customer service strategy. Larger companies can leverage this information to address the competency of their teams and clearly identify which agents need better training or support.

Programmable contact centre solutions can provide a powerful solution for businesses looking to improve their customer service and differentiate themselves from competitors. While we’re already leveraging AI’s potential in many ways, by integrating these tools, the next wave of advancement will undoubtedly provide stakeholders even more tangible benefits.

Omar Javaid, Chief Product Officer at Vonage

Image Credit: Lenetstan / Shutterstock