Introduction

As artificial intelligence tools become more accessible to users at all levels, businesses across various industries are experiencing new efficiencies and opportunities for growth. Delivering exceptional customer service is essential for a thriving business. Customers anticipate prompt and convenient support, no matter the platform—whether it's social media, your website, email, or phone. Demonstrating that you value their business is crucial in every interaction.

Fortunately, managing customer service doesn't have to be overwhelming. Numerous tools are available to help you handle all customer inquiries and requests from a single, user-friendly platform.

The widespread availability of artificial intelligence (AI) technology is revolutionizing business operations. The concept of "democratization of AI" describes the movement towards making AI technologies more accessible, affordable, and user-friendly across various industries from airlines to finance regardless of users' formal technical training. AI holds significant potential in the enterprise sector to foster innovation, boost efficiency, and enhance decision-making.

Ways to use AI in customer service

AI has long been a staple of pop culture (think: The Terminator), but recent advancements like ChatGPT and AI-powered bots have revitalized the discussion about its role in business. Both company leaders and consumers are increasingly recognizing the benefits of AI in customer service and how it can simplify our lives.

So, how can AI enhance customer service? The AI Customer Experience Trends Report 2023 reveals that many users of AI experience 30 percent faster resolution times, and businesses using AI bots saw a two percentage point increase in CSAT year over year. Continue reading to discover how your business can leverage AI to improve customer service.

How AI can improve customer service

1. Improve agent efficiency and productivity:
   • AI can enhance agent productivity and efficiency with tools and automations that streamline workflows. Business chatbots can handle simple requests, while automated processes eliminate repetitive, time-consuming tasks. This reduces your team's workload, allowing agents to focus on high-value tasks and complex customer issues.
   • AI can also analyze customer interactions to understand sentiment and intent, identifying positive, negative, and neutral language. This enables accurate ticket routing to agents when a handoff is necessary, reducing escalations through sentiment detection. When transferring to a human agent, the sentiment information is included, helping the agent approach the interaction appropriately to avoid or de-escalate elevated situations.
   • For example, offers a variety of AI-powered productivity tools to simplify agents' tasks. These tools include:
   • Advanced Bots: Greet customers on your website or messaging channels as the first line of support, answering common questions and saving agents' time. These bots come pre-trained to understand top customer issues specific to your industry, identifying intent, language, and sentiment. AI also provides a bot builder to create customized, conversational responses.
   • Intelligent Triage: Uses AI to analyze customer requests, determining intent, sentiment, and language. It then routes the request to the most suitable agent, along with the customer context.
   •  Intelligence in the Context Panel: An AI-powered assistant within the Agent Workspace that offers insights and guidance on resolving issues. It displays customer intent, sentiment, and language, suggesting relevant responses to help agents resolve issues faster.
   • Content Cues: An AI-powered feature that identifies gaps in knowledge base content based on trending topics and flags existing content needing improvement, making it easier to keep self-service resources relevant and up-to-date.
   • Example scenario: A customer messages via Facebook Messenger for business, asking, “Where is my order? It was supposed to be delivered yesterday.” The AI detects negative sentiment and understands the customer's frustration. It automatically triages the ticket to the right agent, helping the business avoid further escalations.

2. Make proactive recommendations to customers:
   • With the right data and customer context, bots can proactively offer personalized recommendations based on a customer's preferences, website behavior, previous conversations, and more.
   • Lauren Hakim, a product marketer at AI highlights proactive engagement as one of the most effective uses for AI-powered chatbots.
   • For instance, AI can effectively prevent customers from abandoning their shopping carts. Customers may have additional questions about a product, encounter issues with shipping costs, or not fully understand the checkout process. AI can automate workflows to help close sales, with chatbots offering discounts, sending reminders to complete the purchase, or proactively reaching out to address any questions.
   • Example scenario: AI identifies a website visitor who frequently adds items to their shopping cart but often abandons them. A bot sends a proactive message to the visitor with a discount code to encourage the purchase.In today’s rapidly evolving digital landscape, credit card fraud has become a prevalent activity among cybercriminals. This form of   fraud involves stealing debit or credit card details through unsecured internet connections.

3. Provide customers with 24/7 service:
   • Implementing AI-powered chatbots enables customer service teams to provide convenient, 24/7 support. This ensures customers can connect with your business at any time, day or night, and receive real-time assistance even when support agents are unavailable.
   • Chatbots, such as AI bots, operate around the clock. They can address general inquiries and offer self-service resources, like help center articles, allowing customers to find answers or complete simple tasks independently. As businesses expand into global markets, continuous support is essential for maintaining an excellent customer experience.
   • Example scenario: A customer reaches out for support at 3:00 am Pacific Time. They are immediately greeted by a chatbot that asks a series of questions. The bot collects the customer’s information and opens an asynchronous ticket via email. It also provides a relevant help center article while the support team addresses the request.

4. Deliver personalized support:
   • According to our CX Trends Report, 59 percent of customers expect businesses to use the data they collect to personalize their experiences. AI can utilize this customer data to provide tailored support in several ways:
   • Offering assistance based on previous behaviors or inquiries.
   • Keeping customers informed about new, relevant products and services based on their purchase history.
   • Sending relevant discounts for items saved in a customer’s cart.
   • Serving customers in their preferred language.
   • Can customers and bots engage in rich, personalized conversations? AI built on customer intent models specific to customer service, the answer is yes. You can configure bots to deliver an immersive customer experience and convey genuine empathy in a conversational manner.
   • Example scenario: AI automates a friendly message wishing a customer a happy birthday and includes a 50 percent discount code. It sends this message on the customer’s preferred messaging channel, addresses them with the correct pronouns, and recommends products based on their purchase history.
5. Gather consumer insights:
   • Implementing AI in customer service enables teams to gather valuable consumer insights. For instance, AI in the context panel provides AI-powered insights that give agents access to customer intent, language, and sentiment, helping them approach interactions more effectively.
   • All relevant data is stored in a unified workspace, eliminating the need for agents to switch between apps to find the information they need.
   • Agents can automate responses, saving time and reducing manual tasks, especially during peak periods. The intelligence in the context panel eases the pressure on agents by streamlining workflow.
   • Example scenario: A customer reaches out via live chat because their order was lost in the mail. AI prompts the agent with a suggestion to offer a refund or replacement for the missing product.
6. Create powerful intelligent workflows:
   • Redirecting customers to different departments and representatives can detract from a positive customer experience. AI offers the ability to create sophisticated intelligent workflows, leading to faster support for customers and more efficient agents. This approach reduces wait times by intelligently routing customers to the most suitable agent for their needs.
   • AI support teams can leverage AI to route requests to the appropriate person based on:some text
     • Customer intent, sentiment, and language
     • Agent capacity
     • Agent status
     • Agent skill set
   • Example scenario: A customer calls to report being charged a different price than expected for a service add-on. AI detects the customer's angry tone, identifies that they speak Spanish, and captures their account type and billing information. The AI then locates an available senior-level agent who is proficient in handling billing discrepancies and speaks Spanish. It completes the handoff, providing the agent with all relevant customer context.
7. Offer multilingual support:
   • Conversational AI technology leverages natural language understanding (NLU) to detect a customer’s native language and automatically translate the conversation, thereby enhancing multilingual support capabilities. 
   • Integrating multilingual support automation software with your customer service solution allows AI to access customer information, adding a personalized touch to the conversation. This includes data such as the customer’s location, device, buying preferences, and conversation history.
   • Example scenario: A bot automatically identifies the customer's language based on their location and the text in the chat window.

8. Assist with agent onboarding and training:
   • When agents join a new customer service team, there's a lot for them to learn. AI support provides every customer service agent with a virtual assistant, simplifying the onboarding process and training. Advanced AI helps agents get up to speed and improve their customer service skills by:
   • Gradually increasing the complexity of requests they handle through intelligent routing
   • Suggesting the next course of action in various scenarios
   • AI support, Rhythm Energy reduced the time spent training new agents while maintaining high-quality customer service.
   • “AI is easy to teach because everything’s automated,” says Brandon Cancino, customer care manager at Rhythm Energy. “We can take an agent with zero knowledge right off the training floor and have them assisting customers like a tenured agent.”
   • Example scenario: A newly hired agent who recently completed training is still getting comfortable handling live customer service requests. A bot assists by offering relevant help center articles and suggested responses to customer inquiries, helping the agent learn the ropes faster.

9. Save agents’ time by automatically identifying customer intent:
   • Smartphones equipped with NFC chips allow users to make payments with a few taps, increasing the risk of hacks and cyber threats. Machine learning for fraud detection can efficiently identify abnormal activities for each user, thereby reducing the risk of digital wallet fraud.
   • AI advanced bots come equipped with pre-trained customer intent models designed to address common, industry-specific issues based on customer service data. These advanced bots can automatically identify customer intent and classify requests, such as password resets or billing issues, providing more personalized and accurate responses. They can then share this intent with agents for added context.
   • These bots can be deployed on messaging and email channels to deflect customer questions and handle repetitive tasks-such as troubleshooting or collecting feedback—allowing agents to focus on queries that require a human touch. Instead of spending hours manually configuring chatbots, you can set up an advanced bot with just a few clicks.
   • Example scenario: A customer sends an Instagram DM saying their order was never delivered. An advanced bot automatically understands the intent based on the customer’s language and responds with an offer to send a replacement or issue a refund.

The benefits of using AI for customer service 

According to our CX Trends Report, 72 percent of business leaders prioritize expanding their use of AI and bots across the customer experience over the next 12 months. As businesses invest in customer service AI, they discover numerous benefits. Here are some of the top advantages of AI for businesses:

• AI keeps costs low: Tools like chatbots, intelligent triage, and workflow automation enable customer care teams to handle higher ticket volumes without increasing staff. AI enhances agent efficiency and productivity, contributing to cost savings.
• AI delivers fast, consistent support: AI provides instant support without involving an agent. When a customer handoff is needed, AI supplies key information and context to the agent, along with insights and suggested actions for faster resolutions.
• AI boosts customer satisfaction and retention: Businesses using AI bots saw a two percentage point increase in CSAT year over year, according to our CX Trends Report. Fast, convenient, and consistent service fosters customer loyalty.
• AI reduces agent burnout: By handling tedious tasks, AI reduces the workload for support teams. When agents focus on tasks that match their skillset, their jobs become more fulfilling.

Examples of AI and automation in customer support

Examples of AI and automation in customer support include chatbots, natural language processing (NLP), face and voice recognition, interactive voice response (IVR), and intelligent virtual assistants (IVAs). AI technology is relatively new and will continue to evolve and improve. As technology advances, business leaders can leverage innovative AI-powered tools to enhance customer experience (CX). Here are a few examples of AI and automation in customer support:

• Chatbots: Conversational AI that understands customer inquiries and automates responses in a friendly manner.
• Natural language processing (NLP): Machine learning technology that comprehends and responds to voice commands and translates text.
• Face and voice recognition: Biometric AI that uses algorithms to detect and distinguish human facial features and voices for authentication.
• Interactive voice response (IVR): An automated phone system that answers incoming calls, understands vocal replies, and offers options for next steps, such as routing calls to the appropriate agent or department.
• Intelligent virtual assistant (IVA): An AI program that understands voice commands and completes tasks for customer support agents.

What are the challenges of AI in customer service?

Implementing AI in the workplace, like any emerging technology, may present unique challenges. Here are some of the most significant obstacles to consider as you start incorporating AI into your business. When selecting AI software, ensure you choose a solution that can address these challenges for your team.

Choosing AI: The smart decision for customer service 

Implementing AI in the workplace, like any emerging technology, may present unique challenges. Here are some of the most significant obstacles to consider as you start incorporating AI into your business. When selecting AI software, ensure you choose a solution that can address these challenges for your team.

Integrating machine learning into customer service can be challenging for many businesses due to the need for specialized coding skills and deep AI expertise. The scarcity of AI talent and high hiring costs further exacerbate the problem.

However, the emergence of no-code AI-powered customer service tools is transforming the landscape. These tools democratize AI implementation, enabling businesses of all sizes to leverage machine learning without requiring specialized coding skills or AI expertise.

Different services are built on the world's first Unified-CXM platform, seamlessly integrating pre-built AI models into workflows that facilitate the effortless development of sophisticated AI applications.

With a user-friendly platform, you can confidently deliver personalized and efficient customer service experiences regardless of your technical expertise. Don’t just take our word for it-experience Sprinklr Service for yourself.

Brands using machine learning in customer service

Here are the companies that are utilizing machine learning in their day-to-day customer service, setting benchmarks for their peers.

1. Sephora uses machine learning-powered social media customer service chatbots:
   • Sephora, a renowned cosmetics retailer, leveraged machine learning (ML) to develop social media customer service chatbots on platforms like Facebook Messenger and Kik.
   • These chatbots, such as the Sephora Reservation Assistant and the Color Match for Sephora Virtual Artist, provide functionalities like appointment bookings, makeup tips, and product recommendations.
   • This innovation enhanced Sephora's booking conversion rates and improved the shopping experience, making it more personalized and efficient for customers.

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2. H&M improves the fashion retail experience with a conversational service bot:

• H&M, a prominent fashion retailer, employs machine learning to enhance its customer experience through a conversational bot. This live chat interface offers style tips and personalized fashion recommendations to online shoppers.
• The bot asks customers about their style preferences to suggest outfits and redirects them to H&M's website for purchases.
• By incorporating machine learning in customer service, H&M engages customers, saves agents' time, and provides a more tailored shopping experience, aligning with modern consumer preferences for personalization and convenience.
  
  

3. Planet Fitness improves customer service with a full-stack AI and ML platform

Planet Fitness, a leading fitness center franchise, has adopted the Sprinklr AI+ platform to enhance its customer service operations on social media channels. By leveraging AI and machine learning in customer service, Planet Fitness streamlines its customer service processes while upholding a high standard of customer interaction on social media.

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Conclusion

The democratization of AI brings significant opportunities and challenges. To fully realize its potential, it's crucial to embrace responsible development, encourage collaboration between humans and AI, and prioritize ethical considerations. This approach can lead to a future where AI empowers individuals, revolutionizes industries, and contributes to a fairer and more sustainable world.

Maintaining human control over AI and utilizing its power effectively are essential for maximizing benefits and minimizing risks. Organizations, individuals, and governments must work together to adopt responsible AI practices, provide training and education for workforces, encourage open dialogue, and engage stakeholders from diverse backgrounds in discussions about AI's future and the development of responsible solutions.

The democratization of AI is a transformative force shaping our future. Embracing its potential responsibly can help create a more inclusive, innovative, and sustainable world for everyone. To learn more about Stefanini’s leading omni-channel AI assistant, check out this blog and reach out to us today.