AI in Customer Service: How to Enrich Your Customer Experience

Delivering intelligent voicebot experiences to resolve complex taxpayer needs. Our IP-led, expert-managed solution accelerates enterprise value by delivering both top- and bottom-line benefits, along with enhanced B2C and B2B experiences. “By teaming with Accenture and using leading-edge artificial intelligence to assist customers, we have been able to provide them with a fast and easy way to meet their needs.” Say hello to CommBox.io, the intelligent customer communication center for live and automated interactions.

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" 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One company that tried this approach is BT, which used AI to improve customer service by focusing its field engineers on the right job at the right time. “Aisera’s AI technology is transforming our Service Desk to enable a true self-service experience for our employees. With Aisera, we can provide faster solutions to employee problems and provision their requests from IT. Aisera’s conversational AI and RPA have significantly improved our employee experience in requesting catalog items and searching knowledge bases for relevant answers to continuously self-learn and improve.” There are some AI tools that empower contact center agents to be more effective in customer service interactions. (Which ultimately leads to improvements in areas like wait times and on-hold times).

Smart suggestions to support emails

Should customer service professionals in 2020 be afraid of losing their jobs to AI? Harness the power of data and artificial intelligence to accelerate change for your business. An AI-powered customer engagement strategy can reduce the trade-off between cost savings and excellent service. Responsibly establish a strong foundation of customer and journey data to generate insights around specific business inefficiencies that unlock value. Apply a data-driven approach to identify and prioritize customer intents for automation.

For instance, MonkeyLearn automatically identifies customers’ sentiments and tags tickets for better prioritization. Tagged tickets are analyzed and gain insights from the internet, especially social media sites, products or services reviews, and app reviews. Machine learning is now an indispensable part of practically every corporate development. It’s an essential mechanism for analyzing large data streams and deriving valuable insights. Machine learning empowers human agents by analyzing thousands of conversations and predicting common questions and possible answers when it comes to customer support.

Ultimate guide to customer service for businesses

Some chatbots are designed to simulate human conversation, while others are designed to provide information or perform tasks. Companies are increasingly adopting AI to identify trends and gain insights from the huge volumes of data they hold in order to aid decision-making. AI-driven holistic solutions are being utilized to automate business intelligence and analytics processes based on transactional data found in their databases. By detecting patterns and changes, companies can use the resulting insights for a wide range of business applications, such as new service requirements, location-based trends or new product development. Providing agents with AI-powered tools and solutions to extend their abilities, enabling them to master complex device guidance processes and provide better service, is an effective way to improve job satisfaction and reduce attrition.

  • An add-in comment box can add some value, but only if it’s smartly managed and feedback is implemented.
  • However, technology is evolving every day, and the risks are becoming less and less significant.
  • 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.
  • This model is what underlies the “robots will take all the customer service jobs” fear.
  • Utilize the latest in Conversational AI intent narrowing and automated topic suggestions for cohesive conversations.
  • Belarmino, who has a Ph.D. in hospitality administration, remembers managing a call center for a reservations system, where her predecessor would monitor how much time agents spent on a call. “The customers who don’t need to call won’t call,” she says, adding that many travelers will simply book online. When gamification is introduced into a call center environment, agents compete with each other to complete objectives and outpace other reps in specific KPIs such as hours worked, lessons learned or average speed to answer. Gamification can be an immersive, exciting experience that engages and motivates agents. Rewards may include recognition on leaderboards, physical prizes or alternative rewards like preferred shifts or free parking.

    While customers receive efficient solutions, agents fulfill their service commitments and relieve loaded support channels from the hectic rush. AI Takes Marketing to the Next Level One of the biggest emerging use cases for AI in customer service is AI-enhanced marketing. For example, agents will have time to ensure FAQ articles are up-to-date so that any bots and knowledge bases always remain relevant.

    What is AI-powered customer service?

    AI-powered customer service involves making use of Natural Language Processing (NLP) along with Machine Learning (ML) to serve your customers, answer their questions instantly, and improve your brand’s customer experience.

    For instance, AI can screen incoming support inquiries to decide how a customer best be assisted and direct them to the appropriate agent or department. Manually responding to routine email inquiries can eat up your resources by taking agents’ attention away from more complicated issues. Here’s a quick look at four specific reasons we’ll continue to see a AI For Customer Service growing presence of AI in customer support. Nowadays, whenever we read any marketing and advertising article, we tend to encounter the term customer engagement. However, sometimes it can be a grueling task to ensure that you are doing all that you can to improve your team’s performance, especially if you’re not using the right tool or using one at all.

    The customer begins by stating in their own words why they are calling. AI authenticates the caller, recognises their intent, and automatically answers or routes them to the right agent. When it does so, it pulls out the customer’s details and call history and transcribes their own words so the agent immediately has the right context. A UK police force, for instance, used service design to discover that a large number of 999 calls were mere requests for information and were hindering call handlers from helping citizens truly in need. Additional research showed that fragmented processes and workarounds for existing blockers were reducing efficiency and visibility of the process for citizens. The solutions focused on better access to information rather than automation.

  • They had developed a partnership with IBM Watson and gained approximately $200 million last year.
  • A chatbot is a system that is intended to allow human customers to converse naturally with a piece of software and receive assistance or answers.
  • Automated AI-powered assistants answer customer queries instantly, gather complete details regarding the product or services, and advise customers to help them make the right decisions.
  • Services that might have previously been very time consuming can now happen in real-time.
  • One of the best ways to determine where RPA can assist in customer service is by asking the customer service agents.
  • Combining the power of AI with the capabilities of human support agents gives companies the ability to provide the high level of service their customers expect and deserve. AI is a great tool for most support teams to provide exceptional customer service. Chatbots undertake various activities, from reminding customers to revisit their shopping carts to collecting feedback and asking them to write reviews. AI in customer service means 24/7 availability around the globe in any language, which inevitably attracts new customers and increases customer satisfaction.

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