Artificial intelligence customer services are on the rise. The automation of services has accelerated recently, providing customers with the facility they need to carry out their routine duties. Users may now make restaurant reservations, order pizza, book movie tickets, and hotel rooms, and even arrange appointments at doctors’ offices, thanks to sophisticated systems powered by automated solutions.
What is artificial intelligence customer service (AIaaS)?
The term “artificial intelligence as a service” (AIaaS) refers to a service that outsources AI to allow people and businesses to experiment with and expand AI methods at a low cost. Businesses can benefit from artificial intelligence in many ways, from improving consumer experiences to automating repetitive jobs. But creating internal AI-based solutions is a difficult process that costs money. Because of this, companies are enthusiastically adopting AIaaS, a model in which third parties provide ready-to-use AI services.
As a result, artificial intelligence career paths are expanding.
Artificial intelligence (AI) radically alters how we operate in many industries. Customer service has long been a component of these industries, whether in retail, finance, manufacturing, or law. According to experts, it may become impossible to distinguish between a human and an AI bot in the upcoming years.
Similar to infrastructure as a service (IaaS) and software as a service (SaaS), AIaaS offers a package that a third-party supplier hosts. This is an affordable and dependable replacement for software created by an internal team. As a result, everyone in the corporate ecosystem can now access AI. With AIaaS, customers may take advantage of AI’s capabilities through tools and application programming interfaces (APIs) without needing to create intricate code.
Did precursors of artificial intelligence dream of it?
Role of AI in customer service
The reasons behind this are the demonstrated advantages of AI, which include:
- Improved user satisfaction: A study by Aberdeen and IBM found that 33% of users are more likely to be satisfied as a result of the personalized experiences provided by AI.
- Customer acquisition: Businesses that have made AI investments are three times more likely to attract new clients.
- Customer retention: AI use increases client retention 2.5 times more likely in businesses.
Due to the automation offered by intelligent solutions, businesses that invest in AI can boost their income and sales while saving a significant amount of money on routine and operational chores.
Artificial intelligence customer service challenges
Only one in ten businesses have successfully put AI into production. Smaller businesses find it difficult to embrace, while larger organizations with specialized teams and resources only employ it for the most important projects. How come? Most of the time, at least one of the following is to blame:
- Lack of talent: Data scientists and competent AI engineers are difficult to find and keep.
- Access to data: Most businesses lack unified, high-quality data that AI-embedded apps may utilize to learn from.
- Know what to do: Most businesses lack the knowledge necessary to launch an AI effort effectively.
Examples of AI in customer service
Organizations are looking to artificial intelligence (AI) to help close the gap as demand for a better and more personalized consumer experience increases.
Here are 10 cases where AI will improve customer service:
AI customer service bot: Chatbots
Chatbots are one of AI’s most widely used applications in customer service. Businesses already employ chatbots of different complexity to answer common inquiries about order status, delivery dates, outstanding debt, and other topics obtained from internal systems. It is one of the best examples of artificial intelligence customer service.
The customer support team can assist more individuals and improve the overall experience by moving these commonly asked questions to a chatbot, all while lowering operational costs for the business.
Agent assist technology is used in many contemporary multichannel contact centers to automatically understand the customer’s question, search for knowledge articles, and display them on the customer care agent’s screen while on the phone.
The procedure can minimize the average handle time, lowering costs and saving the agent and consumer time.
Customer self-service includes the ability of customers to recognize and locate the assistance they require without relying on a customer service representative. If given the right tools and information, most consumers would choose to resolve problems on their own if given a choice.
Self-service features will spread more widely as AI advances and provide users the freedom to address issues on their own schedules.
Robotic process automation
Many straightforward operations that an agent used to complete can be automated with robotic process automation (RPA). For example, automating bots to handle record updates, problem management, or proactive customer engagement can significantly lower costs and enhance efficiency and processing times. Asking the customer service representatives is one of the finest ways to find out where RPA can help with customer service. It is one of the best promising examples of artificial intelligence customer service.
They can probably pinpoint the procedures that take the longest or involve the most system clicks. Or they might propose automated, routine, straightforward transactions. This business process optimization can save customer service firms millions of dollars annually when properly prioritized and implemented.
Collaborators can extract important information from client feedback using language analysis technologies and modify their messages. It is one of the best useful examples of artificial intelligence customer service.
The use of language analysis can greatly enhance your call center experience. With it, your customer service representatives can determine if the person they are speaking to is happy or unhappy and change their tone and behavior accordingly.
Optical Character Recognition (OCR)
Automated document processing often makes use of optical character recognition.
OCR allows you to program your systems to read documents like invoices or orders, extract the pertinent data, and automatically fill in the appropriate fields. By processing documents more digitally and effectively, you may assist in information retrieval from paper documents that are quicker and more precise.
Machine learning models
To build and evolve predictive analytics that will assist you in making better and more informed business decisions, you can train machine learning models and incorporate them into your apps.
Machine learning has several applications, with the following being the most prevalent:
- Automation of a business outcome, risk analysis, or approval decision.
- Sort tickets into support triage, team assignment, and solution recommendation categories.
- Forecast the availability of stock, product demand, customer support demand, and sales discounts.
Businesses are increasingly using AI to find patterns and derive insights from the vast amounts of data they have to support decision-making. Based on transactional data collected in their databases, AI-driven holistic solutions are being used to automate business intelligence and analytics activities. Companies can use the insights gained from identifying patterns and changes for a variety of commercial applications, including the development of new products or services, location-based trends, or new service requirements.
Smart assistants like Alexa, Google Assistant, and Siri are intriguing new ways to provide individualized assistance, but the practical implications for businesses and customer support teams are still under development. Customers value and prefer it when businesses connect with them on their preferred platform, which is a smart home gadget for some individuals. It is one of the best exciting examples of artificial intelligence customer service.
Imagine a time in the future when a user could ask their smart speaker a single inquiry to resolve any product or service-related issue without using a phone call or email. This clearer communication could mean the difference between a happy and dissatisfied consumer.
Conversational AI for customer service
Artificial intelligence (AI) that uses data, machine learning, and natural language processing (NLP) to enable human-computer conversation is known as conversational AI. With the ability to recognize speech and text inputs and translate their meanings between human and computer languages, chatbot technologies are a booming industry that addresses numerous challenges in enabling human-like communications.
Call centers increasingly use conversational AI for Customer Services, such as online chatbots (bots) and voice assistants (VAs), to simulate human agents to automate customer support services.
Conversation AI for customer service is crucial for prompt responses and proactive engagement since it enables your company to interact with clients on their preferred channels.
A FAQ chatbot or a conventionally written chatbot are two straightforward examples of low-maturity Conversational AI customer service applications. In this case, a user inputs an inquiry, and the response is the answer pre-programmed for the term or phrase. These “answer and response” chatbots don’t use machine learning, NLP, or dialog management. This means that while chatbots may manage client requests that proceed in a predetermined manner, they cannot improvise in the event of unexpected twists.
Future of AI in customer service
Customer service will receive a large share of that AI investment: Emerging technologies, such as mobile messaging and machine learning apps, will be used in 70% of consumer contacts by 2022, up from a projected 65% in 2018. Further, it will keep expanding. We have compiled for you which areas you should look at in the near future.
5 trends to watch
Here are five intriguing AI-powered customer service trends to get a head start on as AI is well on its way to becoming a cornerstone of customer service for businesses worldwide:
Chatbots will become more advanced
Thanks to recent technological breakthroughs, most chatbots, and virtual assistants can already pass the Turing test. Specifically, conversational AI blends machine learning and NLP to assist machines in comprehending subtleties of human language and even mimicking it in a lifelike way.
AI has enabled organizations to provide a more consistent customer care experience across all channels, regardless of whether the consumer is speaking to a live person or a virtual one, by enabling chatbots to identify intent, gain contextual awareness, and respond in kind.
New applications for chatbots
Organizations are finding new uses for chatbots and virtual agents beyond one-off, transactional support engagements as they develop and grow more sophisticated.
AI & Marketing
AI-enhanced marketing is one of the most significant new use cases for AI in customer care. The ability to combine data from many marketing platforms and use prescriptive analytics to that data to provide customized suggestions is expected to become a big potential for marketing teams all around the world.
AI-powered customer journeys
Few things are more annoying for customers than having to repeat themselves each time they speak to a different member of a company’s customer care team. This will likely happen when a customer interacts with a firm across various channels.
By adopting an AI-powered customer service solution to handle customers’ initial inquiries and then referring them to the appropriate agent for extra support, businesses may save customers time, effort, and frustration.
Despite how far AI has come, it still has its limitations. Happily, NLP and machine learning have made it possible for chatbots and virtual assistants to discern when human assistance is required and will escalate as necessary in the future.
What companies use AI customer service?: Real-world examples
A new study from MIT Technology Review and Genesys found that over 90% of businesses with well-known brands and strong customer satisfaction rates employ artificial intelligence (AI) solutions to boost customer satisfaction, compared to 42% of businesses.
These businesses include Alibaba, BT Global Services, Lexus, Nubank, Uber, and Zurich Insurance, which are referred to in the report as “iconic” businesses. According to the survey, these companies are more likely to understand that automated AI tools operate best when they “supplement and extend” the capabilities of their customer care team rather than taking the place of human employees.
Here are some further instances of how companies are coming up with creative ways to use AI to enhance customer service and the entire customer experience:
Delta Air Lines
To provide clients flying directly to an international destination out of specific U.S. airports with a unique biometrics boarding program, Delta Air Lines and U.S. Customs and Border Protection (CBP) cooperated in 2018.
Customer insight research conducted by a third party indicated that 70% of customers found the curb-to-gate facial recognition experience appealing and that 72% preferred facial recognition to traditional boarding. In fact, the program has been so successful that Delta has added airports in eight significant American cities, including Boston, New York City, and Los Angeles.
The chatbot Domino’s Dom is unique among chatbots. This voice-activated pizza ordering assistant not only responds to frequently asked inquiries but also simplifies the process by remembering prior orders from clients and using data integration to calculate delivery times accurately.
The best part is that Dom keeps track of each pizza’s progress throughout preparation and once it is sent out for delivery, giving customers real-time updates so they never have to worry about when their order will arrive.
The Muse, a popular job and recruiting portal for Millennials, partnered with Blueshift, a CDP+ marketing automation platform supplier, to advance its marketing strategy. To produce highly tailored email messages based on user behaviors and traits, the two businesses collaborate to use predictive analytics and AI algorithms.
These intricate, multi-triggered campaigns, which were targeted at various user engagements across several different catalogs and sections of The Muse’s website, increased visitors to the targeted pages by 200 percent.
Can AI replace call center agents?
The Artificial Intelligence Call Center era has begun. But, let’s get to the point: Is AI displacing call centers’ human customer service representatives? No, not really, is the quick response.
Of course, that quick response doesn’t really cover everything. Even though real, live human agents and supervisors still play a crucial overall role in call centers, call center AI technology is becoming increasingly integrated into how these so-called next-generation call centers operate. In reality, it is replacing some agents’ responsibilities along the process.
But let’s be clear: While current AI solutions for contact centers may be taking over some call center operations, like a portion or even the entirety of a client conversation, they are not necessarily completely replacing human agents.
For one thing, call center AI is still limited in what it can accomplish. Shortly, the call center will continue to require significant human engagement. AI is thereby supplementing agents’ work rather than replacing it, making it simpler, more effective, and efficient for agents to accomplish their duties.
By the way, don’t be scared of AI jargon; we have created a detailed AI glossary for the most commonly used artificial intelligence terms and explain the basics of artificial intelligence as well as the risks and benefits of artificial intelligence. Is artificial intelligence better than human intelligence?
One area where AI is presently being used extensively and impacting is customer service. It is utilized in various ways to lower the cost of client service in sectors like fast food, banks, insurance, and retail.
Major corporations are investing heavily because they are sure that voice-activated and AI-integrated chatbots can consistently handle simple requests.
This implies that businesses will probably be able to offer the same level of service they do now for less money. Still, it does not imply that all businesses will be able to cut costs in the customer service vertical.
The main effect of AI on customer service may be a decrease in overall spending for the same industry, or it may result in a race to increase quality for others while spending the same amount.
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