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How will AI-powered customer service help customer support agents?

5 min read
ai customer service

Automation of services has picked up its fastest pace by now, giving users the much needed facility to fulfill their regular tasks. With advanced systems powered by automated solutions, users can now book a restaurant reservation, order a pizza, book a movie ticket, hotel room and even make a clinic appointment. Customer service industry is gaining much momentum especially due to disruption of Artificial Intelligence – a technological breakthrough that has taken almost every business industry by storm.

By transforming customer service interactions, AI-powered digital solutions are prepared to improve every aspect of your business including online customer experience, loyalty, brand reputation, preventive assistance and even generation of revenue streams. Digital market moguls project that by 2020 more than 85% of all customer support communications will be conducted without engaging any customer service representatives.

This blog delves into the subject a little more to convey how AI-powered customer service can possibly help customer support agents online.

AI for customer service: what is real?

According to a recent Zendesk study, as much as 42% of B2C customers showed more interest in purchasing after experiencing good customer service. The same study also goes to claim that 52% of them stopped purchasing due to a single disappointing customer support interaction.

There is no argument that forward thinkers consider AI technology as a solution that will open the doors for real-time self-service for customer service platforms. Also, it is true that the technology has power enough to change the way customer service solutions are designed. However, there is a massive hype floating around about how AI assisted responses will completely replace the need for human agents.

Though most of the excitement about AI is due to its two major capabilities:

  1. a) Machine learning and
  2. b) Natural language processing (NLP)

Machine learning is attributed to a powerful computing system that churns a large amount of data to learn from it. Facebook messenger, request suggestions and spam folders are everyday examples of AI machine learning process.

Natural language processing supports your daily interactions with AI software using its ability to process and interpret spoken/written messages. Siri, Cortana, Alexa are best examples of evolved NLP.

Artificial Intelligence mainly revolves around these two innovative capabilities to power the job of customer support agents. Its cognitive computing power enables businesses to offer efficient services to customers.

A recent Gartner report suggests that 55% of established companies either have started making investments in the potential of artificial intelligence or are planning to do so by 2020.

Let’s learn more about how much AI can really do for today’s customer service representative working in a call center and for businesses they work for.

ai customer service

AI as a brand messenger

In last 5 years, we have seen social media flooded with people devouring messaging apps. They are generously relying on messaging apps not just to communicate with their closed ones, but also to engage with brands they are curious about or familiar with. This is why AI-powered, customized, real-time messaging bot services could provide an incredible opportunity for businesses to connect with new and existing customers and foster a unique revenue stream.

Facebook Messenger leverages powerful chatbots integrated with cognitive capabilities based on this idea. Other leading industries that are now seen galloping towards this space include fashion, tourism, food chains, airline, e-commerce, hotels, etc. Consumers are thrilled to welcome new AI technology for services they avail, and they are happy to interact with their favorite brands to book flights, hotel accommodation, travel trip, or get fashion tips. The world is watching eagerly for next industries to adopt the trend.

AI for well-informed actions

AI is swiftly disrupting the customer service space with its massive power to multi-task and quick-respond with automated queries. By limiting research time and offering considerable action plans, AI-assisted automation of customer service platforms can generate responses with accuracy and speed that humans can’t deliver.

According to Forrester report on customer service trends, we have already stepped into the era of automated, smarter and more strategic customer service. Individuals will appreciate pre-emptive actions delivered by intelligent agents fuelled with artificial intelligence.

AI for customer service will not only make self-service interfaces more intuitive and economical, but its intelligence will help anticipate specific customer needs learning from their contexts, previous chat history and preferences. AI integrated system will capture infinite online data in order to:

  • Identify customer issues
  • Process and learn from gathered information
  • Define customer behavior pattern
  • Determine their frequent decisions and preferences
  • Respond with solutions and suitable products
  • Prompt with proactive alert messages
  • Suggest personalized offers and discounts
  • Offer real-time support (FAQs, help blogs, reports)
  • Resolve issues before they arrive
  • Minimize customer abandonment rate and complaints

With such wide scope of intelligent assistance and pre-emptive recommendations, companies will leave behind rich customer experience.

One-time investment for timeless merits

Stinting on cost is the first priority for businesses as on today. When it comes to call center practices, it takes a good deal of money and time in hiring and training staff for customer service, as well as in erecting the whole brick-and-mortar infrastructure. Just 10 support individuals can cost you as much as $35000, or even more if recruits frequently quit (attrition being quite high in the call center industry) – which is a nightmare.

On the other hand, automating responses via AI enabled customer service platforms can minimize this burden by reducing cost and time. This is what Watson as an AI platform does. It is a pre-programmed intelligent system stuffed with domain-specific knowledge base. All it requires is to be trained, just once. Upon introducing new process changes, just re-configure the software instead of retraining your entire support staff.

Such AI assisted platforms take over the same routine customer requests, enabling call center employees to work on more important and grueling tasks at hand.

AI controlled Multi channels of support

AI technology is not just for giving direct assistance to customers, but it can also be used to usher customer service path. At times when issues get complicated, an intelligent support system will have a certain capability to direct customers towards parallel support channels. For instance, if a telecommunication customer service agent is unable to resolve queries regarding technical network issues, the chat AI can identify the problem as specific to dedicated support channel and shift customers towards it.

Thus, AI for customer service process brings comprehensive balance in the support system. While customers receive efficient solutions, agents fulfill their service commitments and relieve loaded support channels from the hectic rush.

AI machine learning for extra support

If not directly, AI functions best even indirectly for customers and service agents alike. Human representatives can take extra assistance they need to serve the B2C customers. It can speed up the resolution process by discovering and delivering solutions in time on behalf of agents. By learning from repeated issues that are frequently resolved, machine learning power enables customer support to be ready for tough challenges that chatbots sometimes fail to address.

Any call center with AI machine learning capabilities can perform well by suggesting accurate solutions to specific issues. AI’s learning potential to sense human behavior patterns can contribute to both agents and customers.

Read How will AI-powered customer service help customer support agents? Part 2


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