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

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Read Part 1: How will AI-powered customer service help customer support agents?

Precise predictions and insight

You must have felt surprised at how Amazon e-commerce app knows what you would like based on your frequent page visits, cart items selection and social sharing. That right there is the essence of machine learning algorithm, and it can be also used to predict the kind of places, entertainment or merchandises you prefer. Similarly, AI can make predictions about what customers would want, which ultimately benefits customer service agents. Such insightful predictions can be translated into future actions to be taken by customers based on their choices, likes and visited contents.

AI suggests next best action for agents by learning about the most suitable responses to the customer-generated ticket. This is quite helpful in a business where product range and number of actions are high. Agents who are new to the business especially get a great amount of help and direction.

Not only that, once predictive analytics tools are integrated into customer support, it will be easy for agents to grasp their interaction quality by knowing in advance – the customer satisfaction level and overall customer experience.

Uninterrupted momentum of service

Who doesn’t appreciate customer support with fast response and uninterrupted service? One of the surprising benefits from using AI for automating responses is its independence from time constraints and holiday offs. This means that at any given moment customers will be able to interact with AI robot to resolve issues. Such uninterrupted customer service helps organizations stay responsive 24/7 to address incoming customer inquiries. As there will be an assurance of consistent support, problems faced in case of human customer service reps will be effectively eliminated.

The results are:

  • No wait time
  • Quick resolution
  • Prompt escalation
  • Enhanced customer satisfaction
  • High-grade service solutions
  • Improved commitment level
  • Increased brand reputation

Artificial Intelligence offers reliability

As customers’ needs evolve, businesses that are determined to serve the best quality have to integrate unique methods of assistance to offer unquestionable reliability and flexibility. In a tech-rich era, consumers expect a great level of maturity in the way enterprises propose service solutions. Using the cognitive knowledge base of intelligent chatbots, service-based industries can power their everyday interactions with their customers.

If manipulated correctly, AI technology yields such magnitude of reliability that is hard for human counterparts to achieve. The inclusion of chatbots helps surmount all possible barriers and pain points experienced in case of human customer support agents. Chatbots can:

  • Offer freedom from obstacles caused by humans
  • Eliminate all biases and barriers
  • Bridge the gap virtually between business and customers
  • Establish connection of reliability and trust
  • Improve brand reputation through quick, single-attempt assistance
  • Be designed to provide frictionless, flawless communication
  • Escalate customer inquiries when unable to solve themselves
  • Surpass negative human emotions (anger, annoyance, arguments, aggression, and forcefulness)
  • Bring repeated business 

Email support is thinkable with AI

Even after Amazon’s sensible Alexa and Apple’s Siri, we can say AI technology is still getting smarter while going through the process of improvement and innovations. Despite its role as Artificial Intelligence for customer service, machine learning capabilities of AI software still lack certain points where it needs refinement and human-like sensibility.

When it comes to handling email support, AI robot should ideally be making suggestions and writing a proper draft to answer customer inquiries through emails. Email support is where automated responses tossed directly to customers do not produce many results, giving businesses hard time to cope with incoming queries. However, this scenario can be something AI-powered customer service platforms can work on.

With gradually developed ability to learn from the large dataset, AI email support can offer certain meaningful solutions just like chatbots. It can suggest a help article using natural language processing system. It can even fetch some part of email draft for people working in a call center.

Since it requires accurate learning, AI can turn out to be a thinkable investment for service structures where the overall volume of support conversations is in thousands on monthly basis. Intelligent services can then be an efficient solution.

AI robots mean precision

The human brain has limited capacity and is often subject to issues of inaccuracies and flaws when it comes to serving people to the best of their performance caliber. On the other hand, AI assisted service solutions conform to predetermined standards and well-programmed efficiency, resulting in high-quality, straightforward customer experience delivered with minimal AHT (Average Handling Time).

Due to the highly capable machine learning process of AI-enabled chatbots, businesses can be sure their deliverables will be unscathed and immensely satisfying to customers’ expectations. Thus, we can conclude that inclusion of automating responses of AI-powered robots can pull off business target with utmost precision, without consuming much of customer’s time and resources.

Data mine transformed into personalization

In the online space, we all leave an enormous pile of data behind in our lifetime. But only 1/3rd of it is actually worth analysis. If analyzed and harnessed properly, organizations can leverage it to transform their businesses and boost brand engagement. Enterprises collecting such gigantic data can use the combined power of Big Data, AI and its machine learning capabilities to make customer journey more enlivened and personalized.

Brands can weave engaging product theories or personalized recommendations for each customer, creating an unparalleled stream of customers each day. Based on customer reviews and feedback, it becomes easy to navigate around their needs and browsing pattern and customize web design to individual customer’s taste. Such level of AI technology intervention for personalization greatly impacts on:

  • Customer service interaction
  • Engagement level
  • CSAT
  • Customer retention
  • Repeat business
  • Conversion metrics

The rise of AI-assisted human agent model

AI-augmented customer service is maturing as sophisticated enterprises turn to strategic investment in artificial intelligence for their innovative front-end chatbot service. AI blows trumpet across the globe with its attractive benefits such as efficiency improvement, fast resolution, accurate assistance, brand reputation and increased revenue.

Oracle in its study of AI as a customer service says that nearly 8 out of 10 businesses have adopted or are planning to adopt the power of AI for customer care solutions by 2020.

Instead of implementing fully automated front-end AI-powered bots, many enterprises prefer to invest in AI-assisted human agent model where human customer service representatives are supported by AI technology.

Front-end AI chatbots handle common first-level queries learning from historical tickets, FAQs and support documents, and helps optimize AHT (Agent Handle Time) to a good extent. Machine learning of AI gives intelligent agents ability to minimize escalation events, promote FCR (first contact resolution) and cuts down agent training cost.

The present glory of AI for customer service

Tata consultancy services recent survey unfolds that almost 31.7% of major companies are now using AI in customer service space.

In the domain of customer care, the bank that has massively leveraged AI technology is China Merchant Bank, a leading credit card issuer in China. The bank’s front-end bot powered by WeChat messenger handles as much as nearly 2 million customer inquiries on daily basis. Since most queries are quite common, automated responses via AI chatbot proves to be a cost-effective solution, eliminating the need for hiring thousands of employees.

When it comes to AI-assisted human agent model, LivePerson as a customer service platform provider delivers appreciable results, increasing efficiency by 35%.

KLM, the Netherlands airline, turned to DigitalGenius to provide AI-powered customer service solution and diminish waiting time before the queries are answered. The solution has AI learning from live support interactions, adapting to reply format and suggesting responses to the human reps.

ai customer service

Most popular food chains like Subway, Dominos, Starbucks have all recently embraced AI to enable customers to place orders without any human involvement. They can rely on Facebook Messenger chatbots or simply tell Amazon’s AI bot Alexa, to order a bite.

Like other financial structures, Bank of America is also determined to roll out Erica, an intelligent virtual banking assistant based on AI technology, which will take digital banking to far next level.

Conclusion:

AI powered chatbots for customer support is pushing the envelope of innovation and revolutionizing the way customers are assisted. AI means high-quality customer experience, personalized support, speed & efficiency and cost saving. Of all business segments, customer service is the one where Artificial Intelligence is hugely embraced and companies are confident about how chatbots can efficiently handle first-level queries and significantly minimize operational cost. We are most likely to experience further innovations in AI-powered applications for improving customer service solutions. Currently, major industries that rely on artificial intelligence in customer support space are food, travel, finance, retail, airline and clothing.

Maruti Techlabs offers an unparalled and automated customer support experience with chatbots that provide answers in real time. Companies can easily customize the chatbot to fit specific business needs, resolve customer queries, provide custom content while simultaneously matching brand voice and tone.

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