How Genai can Improve Customer Support

The customer support industry is experiencing a seismic shift, and at the heart of this transformation is the integration of Generative AI (Gen AI) capabilities. What's remarkable about this technology is that it empowers customer service agents, rather than replacing them, to provide personalized, efficient, and impactful support. Gen AI can generate human-like responses swiftly and accurately, reducing the need for human agents and supercharging efficiency. 🔍 Let's delve into how Gen AI is reshaping the customer support landscape, creating a league of super agents who harness AI to elevate customer service. Agile Case Resolution: Gen AI streamlines support by facilitating agile case resolution, helping service agents resolve customer issues with lightning speed. Personalized Experiences: By analyzing customer interactions, Gen AI crafts personalized responses, curates relevant knowledge articles, and delivers instant solutions, enhancing the capabilities of human agents. Boosted Agent Creativity and Proficiency: Gen AI propels customer support agents' productivity by 14%, freeing them to focus on complex tasks and deliver an exceptional customer experience. 24/7 Customer Service and Support: Businesses can now offer round-the-clock customer service and support, trimming the need for human agents and boosting operational efficiency. Deeper Customer Insights: Gen AI delves into customers' needs and behaviors, enabling businesses to anticipate future requirements and make data-driven improvements. Financial Benefits for Companies: Revenue Growth: Personalized and efficient support builds customer loyalty, leading to increased revenue. Cost Savings: Gen AI automates repetitive tasks, reducing operational costs and providing 24/7 support, saving on labor expenses. Improved Efficiency: Faster and more accurate responses trim resolution times and customer effort, enhancing overall efficiency. Real-World Examples: Email Response Automation: A Gen AI-based customer service application now handles a third of all customer inquiry emails, freeing agents for more complex tasks. Call Center Transformation: Retail giants like Walmart and Walgreens, financial institutions like Capital One, and airlines like Cathay Pacific use Gen AI to revolutionize their call center operations, delivering hyper-personalized customer experiences and driving revenue growth. Self-Service Support: Gen AI enhances self-service support, empowering customers to find answers quickly without human assistance As Gen AI continues to evolve, we can anticipate even more innovative applications in the customer support industry, further enhancing the customer experience and driving business success. The future of customer support has arrived, and it's incredibly promising! #CustomerSupport #AIRevolution #GenAI #Innovation #CustomerExperience 🌐🤝📈

Hey Salespeople: Here is a collection of current use cases for AI in sales & CS: ** GenAI in Sales ** --> Draft messaging for personalized email outreach --> Generate post-call summaries with action items; draft call follow ups --> Provide real-time, in-call guidance (case studies; objection handling; technical answers; competitive response) --> Auto-populate and clean up CRM --> Generate & update competitive battlecards --> Draft RFP responses --> Draft proposals & contracts --> Accelerate legal review & red-lining (incl. risk identification) --> Research accounts --> Research market trends --> Generate engagement triggers (press releases; job postings; industry news; social listening; etc.) --> Conduct role-play --> Enable continuous, customized learning --> Generate customized sales collateral --> Conduct win-loss analysis --> Automate outbound prospecting -->Automate inbound response --> Run product demos --> Coordinate & schedule meetings --> Handle initial customer inquiries (chatbot; voice-bot / avatar) --> Generate questions for deal reviews --> Draft account plans ** Predictive AI in Sales ** --> Score leads & contacts --> Score /segment accounts (new logo) --> Automate cross-sell & upsell recommendations --> Optimize pricing & discounting --> Surface deal gaps / identify at-risk prospects --> Optimize sales engagement cadences (touch type; frequency) --> Optimize territory building (account assignment) --> Streamline forecasting (incl. opportunity probabilities; stage; close date) --> Analyze AE performance --> Optimize sales process --> Optimize resource allocation (incl. capacity planning) --> Automate lead assignment --> A/B test sales messaging --> Priortize sales activities ** GenAI in CS ** --> Analyze customer sentiment --> Provide customer support (chatbot; voice-bot / avatar; email-bot) --> Draft proactive success messaging --> Update & expand knowledge base (incl. tutorials, guides, FAQs, etc.) --> Provide multilingual support --> Analyze customer feedback to inform product development, support, and success strategies --> Summarize customer meetings; draft follow-ups --> Develop customer training content and orchestrate customized training --> Provide real-time, in-call guidance to CSMs and support agents --> Create, distribute, and analyze customer surveys --> Update CRM with customer insights --> Generate personalized onboarding --> Automate customer success touch-points --> Generate customer QBR presentations --> Summarize lengthy or complex support tickets --> Create customer success plans --> Generate interactive troubleshooting guides --> Automate renewal reminders --> Analyze and action CSAT & NPS ** Predictive AI in CS ** --> Predict churn; score customer health; detect usage anomalies, decision maker turnover, etc. --> Analyze CSM and support agent performance --> Optimize CS and support resource allocation --> Prioritize support tickets --> Automate & optimize support ticket routing --> Monitor SLA compliance

Contacting customer service is not usually something we look forward to. It is often a pain point for companies as well, and they are constantly looking for ways to improve. Service agents need more powerful tools in their daily flow of work to capture customer needs, pass along critical information, and find answers within their knowledge base. Today, #GenAI is becoming a huge boost for agent productivity, and helping them focus on serving customers better. In the latest episode of #Pivotal, Microsoft’s Ric Todd discusses what we are learning after we implemented Copilot for Microsoft Dynamics Customer Service within our customer support teams. Ric’s team is seeing not only the benefits of a large language model that can reason over massive amounts of information instantly — but also a surprising ability for AI to help agents tune into customers’ sentiments, communicate more effectively, and onboard into their roles more quickly. To learn more about how #AI is transforming customer service at Microsoft, listen here <https://lnkd.in/gfPXcgsq>

I had a great conversation with Na Li about how her Customer Care Tech team is using #GenAI to support the Walmart associates who assist our customers every day. Some of her teams are building AI inside products, like our chatbot and agent-assist experiences. Others are using it to help support networking, stream management, and customization of third-party software. She shared a great example. One of her teams handles scripting for a third-party platform and receives hundreds of requests each quarter. They recently built an agent that writes the scripts automatically, so they no longer need to do that work manually. Now the team has more bandwidth to work on strategic initiatives, and our customer care teams are getting what they need faster. Na said it well. Our associates’ engineering craft is still critical. GenAI helps us amplify it. That’s people led and tech powered in action! Walmart Global Tech #TeamWalmart #AgenticAI #FutureOfWork #CustomerCare #SoftwareEngineering

The potential of Generative AI chatbots in customer support is vast. For those looking at ways to maximize value from AI investments, as I see with many of my clients, it is important to understand that Gen AI works best when augmenting an organization’s resources. That takes a lot of time and effort to get to the right outcome. According to a report in Harvard Business Review, of the 13 essential tasks involved in customer support, four could be fully automated, while five could be augmented by AI to help humans work more effectively. In the last two years, I’ve seen countless examples of how Gen AI has challenged and enriched different industries around the world. Especially in customer support, where today’s customers demand quick, efficient, and personalized solutions to their problems. The goal here is not only to embrace the technology, but also identify where challenges lie, to ensure the technology remains an asset to business operations. Some of my key takeaways from a recent article on this same topic by Bernard Marr in Forbes: 1. Generative AI will bring businesses increased efficiency and a constantly thinking system that learns from every customer interaction to meet needs in real-time 2. Using AI-driven agents like chatbots and virtual assistants will reduce the burden of time and resources, leaving room for human agents to focus on more complex and nuanced tasks that need a human touch 3. Upskilling will need to be prioritized. It’s not enough to stay on top of technology; companies need to train and develop their workforce for tomorrow’s innovation 4. Data privacy and ethics should always be front and center. With great power comes great responsibility In my experience, we need to stay adaptable and open to what the technology can bring while also prioritizing continuous upskilling to equip talent with the skills that they need to thrive. #McKinseyDigital #GenAI #Innovation