TRANSFORMING CUSTOMER SERVICE WITH ARTIFICIAL INTELLIGENCE

How to implement artificial intelligence? What functions can artificial intelligence perform? What’s new in artificial intelligence?

Wherever your organization is in its AI adoption journey, answer some questions and learn more about how AI can boost your business?

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Do you use AI in customer service, sales and marketing?

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Have you integrated AI with CRM and ERP systems? What kind of AI tools do you use in your CRM and ERP or other applications?

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Have you created an environment for human beings and AI collaboration? Do you use AI to optimise workforce?

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Do your chabots use both conversational and generative AI? Do they switch seamlessly between each other? Are your chatbots can be voicebots and provide customer service?

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What processes your AI can perform without any human intervention? Do people still analyse photos sent as a complaint item, or AI does it?

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Do people or AI verify stock status, supplies, orders fulfilment, deliveries, etc?

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How quickly do your employees respond to customers’ emails? Do they write emails by themselves or use AI to generate content? If AI writes emails and response, can employees add anything to the message?

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Who updates knowledge bases and how? Or, maybe you have already transformed that to AI?

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What tools do you use for proactive communication with customers? How can you exceed customers’ expectations?

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How do you manage huge volume of contacts, data and facts? How do you filter tasks? How do you set your priorities? How do you analyse sentiment? Do you use AI summary of emails and contacts? Do you use AI and automation to do those tasks?

Transforming customer service with AI

Customer service agents usually work under intense pressure to resolve customer issues quickly, and AI gives them more time to focus on having good customer interactions. Through automation AI reduces manual and repetitive tasks such as ticket categorization and information searching. Service tools enabled by generative AI can help agents to quickly summarise customer information, so they don’t waste time for searching information in different systems. With AI assistance, service agents can connect more deeply with customers and truly use their human skills.

Generative AI is a game-changer when it comes to crafting fast, personalized e-mails. It captures essential information from multiple sources and write routine texts where agents can add their personal touch to each interaction to make sure all communication is human like.

The combination of artificial and human intelligence is beneficial for both side – it ensures customers get fast, high-quality responses they want while reducing the burden on agents.

When emotional intelligence meets artificial intelligence

When customer service agents aren’t engaged in routine tasks, they can spend more time on active listening, empathy, and technical knowledge. Despite being excellent at handling data and recognizing patterns, AI tools can’t replicate the nuanced understanding and human emotional empathy. With AI managing basic tasks, agents can use their experience and empathy to better understand a customer’s needs. As a result – each interaction is a better experience for both customers and agents.

AI is a powerful tool for faster problem resolution. In customer service today, inquiries are increasingly complex, and the volume of information agents must sift through is larger than ever. AI helps agents manage the complexity by supporting service teams with recommended solutions, filtered information, and quick summaries of long e-mail conversations. By assisting service agents in tackling even the most complex inquiries, AI not only simplifies the work but also fosters a sense of achievement to keep agents motivated.

Old way vs new way

The complaint management process shows perfectly how AI transforms customer service process.

Before when a customer e-mailed about a damaged device (e.g. mixer) then the customer service agent must carefully review this e-mail and the attached photos, and then arrange for a replacement. This involves checking inventory for the exact model and color, checking stock, organizing delivery, and crafting a response that addresses her frustration and outlines the next steps. With traditional methods, these steps are highly manual and time-consuming. Agents need access to accurate data about orders, products, and customer interactions. They must then create responses and actions based on this information. The result? While some customer experiences go smoothly, many suffer from long handling times and poor communication, eroding customer satisfaction and loyalty. Challenges that customer service agents had to deal before:

Manually reviewing customer communications and time-consuming work that is prone to delays
Cross-referencing product details and inventory
Sometimes complex systems work to process return
Having to craft empathetic and informative responses

New way – with AI approach to the same customer scenario — the damaged mixer that needs replacing — this time with AI in place. As soon as the customer service agent receives the customer’s e-mail, AI immediately analyzes the attached photos, cross-references inventory to find the correct replacement, and drafts a response that acknowledges her frustration and details the next steps. The entire process is faster, more accurate, and highly personalized. The customer receives a prompt, empathetic response, and her replacement mixer is on its way quickly. A bad experience has been turned positive. AI in service connects all necessary data, spot patterns, and automates the creation of responses and actions. AI can integrate orders, supply chain information, product details, inventory status, and customer profiles. And this integration is just the beginning.

Generative AI can take this data and turn it immediately into actionable content. It can create a comprehensive customer profile, draft an empathetic e-mail response, even build a new knowledge base article. With AI, agents have immediate access to the information they need, formatted and ready to use. Benefits are:

Automated data integration and real-time updates
Immediate generation of tailored responses and actions
Enhanced accuracy and personalization
Reduced handling times and improved communication
Ability to bridge knowledge gaps

SAP Business AI transforms basic CRM and ERP data into actionable insights. How this powerful technology works?

Data integration: Seamlessly connect ERP and CRM data to gather comprehensive customer and product information.
Generative AI: Use AI to transform data into readable customer profiles, empathetic email responses, and knowledge base articles.
Business insights: Leverage AI tools for business entity extraction, case categorization, and similar case matching to understand customer needs.
Real-time guidance: Provide reps with realtime information and guidance, ensuring quick and effective resolutions

Specific AI use cases in customer service

AI improves service interactions at scale. Here are just a few ways enterprises can take advantage of this evolving technology:

AI-powered chatbots: AI chatbots can handle a significant portion of customer inquiries, providing instant responses to common questions. They can guide customers through troubleshooting steps, process orders, and even escalate complex issues to human agents when necessary. This not only reduces the workload on human reps but also ensures customers receive timely assistance. Chatbots can be voicebot as well and talk with customers like a human beings.

Triaging customer enquiries: Categorizing and prioritizing customer inquiries based on urgency and complexity is critical but time-consuming. By analyzing the content of each inquiry, AI can assign cases to the appropriate service agents or teams, ensuring that high-priority issues are addressed promptly. This triage process helps manage workload more effectively and improves response times.

Proactive customer support: AI can anticipate customer needs by analyzing historical data and predicting potential issues before they arise. For example, if a product is known to have a particular fault, AI can identify customers who might be affected and proactively reach out with solutions or preventive measures. This proactive approach not only prevents problems but also enhances customer trust and satisfaction.

Sentiment analysis: By analyzing the tone and sentiment of customer communications, AI can estimate customer emotions and tailor responses accordingly. If a customer is frustrated, the system can flag the interaction for immediate attention and suggest a more empathetic and solution-focused response. Sentiment analysis helps create more personalized and effective customer interactions.

Knowledge base management: AI can continually update and optimize the knowledge base by analyzing customer inquiries and feedback. It can identify gaps in the information available to service agents and customers, suggesting new articles or updates to existing ones. This ensures that the knowledge base is always relevant and useful, improving the overall efficiency of the service process.

Automated follow-ups: After resolving an issue, AI can automate follow-up communications to help ensure customer satisfaction. It can send surveys, request feedback, and offer additional assistance if needed. These automated follow-ups help maintain a positive relationship with customers and identify areas for further improvement.

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