How To Use Technology To Enhance Customer Support

The rapid development of artificial intelligence (AI) is outpacing the awareness of many companies, yet the potential these AI tools hold is enormous. The nexus of AI and emotional intelligence (EQ) is emerging as a revolutionary game-changer. Here’s why this intersection is crucial and how you can leverage it: 🔍 AI can handle data analysis and repetitive tasks, allowing humans to focus on empathetic, creative, and strategic work. This synergy enhances both productivity and the quality of interactions. Imagine a retail company struggling with high customer churn due to poor customer service experiences. By integrating AI tools like IBM Watson's Tone Analyzer into their customer service process, they could identify emotional triggers and tailor responses accordingly. This proactive approach could transform dissatisfied customers into loyal advocates. Practical Application: AI-driven sentiment analysis tools can help businesses understand customer emotions in real-time, tailoring responses to improve customer satisfaction. For example, using AI chatbots for initial customer service interactions can free up human agents to handle more complex, emotionally charged issues. Strategy Tip: Integrate AI tools that provide real-time sentiment analysis into your customer service processes. This allows your team to quickly identify and address customer emotions, leading to more personalized and effective interactions. By integrating AI with EQ, businesses can create a more responsive and human-centric experience, driving both loyalty and innovation. Embracing the combination of AI and EQ is not just a trend but a strategic move towards future-proofing your business. We’d love to hear from you: How is your organization leveraging AI to enhance emotional intelligence? Share your thoughts and experiences in the comments below! #AI #EmotionalIntelligence #CustomerExperience #Innovation #ImpactLab

Let’s say your support center is getting hammered with repeat calls about a new product feature. Historically, the team would escalate, create a task force, and maybe update a knowledge base weeks later. With the tech available today, you should be able to unify signals from tickets, chat logs, and social mentions instead. This helps you quickly interpret the root cause. Perhaps in this case it's a confusing update screen that’s triggering the same questions. Instead of just sharing the feedback with the task force that'll take weeks to deliver something, galvanize leaders and use your tech stack to orchestrate a fix in real time. Don't have orchestration in that stack? Start looking into this asap. An orchestration engine canauto-suggest a targeted in-app message for affected users, trigger a proactive email campaign with step-by-step guidance, and update your chatbot’s responses that same day. Reps get nudges on how to resolve the issue faster, and managers can watch repeat contacts drop by a measurable percentage in real time. But the impact isn’t limited to operations. You energize the business by sharing these results in a company-wide standup and spotlighting how different teams contributed to the OUTCOME. Marketing sees reduced churn, operations sees lower cost-to-serve, and leadership sees a team aligned around outcomes instead of activities. If you want your AI investments to move the needle, focus on unified signals, real-time orchestration, and getting the whole business excited about customer outcomes....not just actions. Remember: Outcomes > Actions #customerexperience #ai #cxleaders #outcomesoveraction

Over 50% of our support chats were resolved by our AI assistant last week. No human intervention! This didn’t happen by accident. For small business owners looking to automate support, the real work happens before you flip the AI switch. It starts with building a strong foundation, and getting your team onboard. Here’s how we did it: The Process 1. Audit your support history We analyzed thousands of past tickets and chats to identify the most common and repetitive questions. Yes, we did this with AI. 2. Build (or expand) your knowledge base We created over 1,000 new help articles in a single quarter—filling gaps, refining answers, and making sure every article was easy to follow. Yes, we also created new articles with AI. 3. Train the AI assistant We integrated our knowledge base with our AI assistant and ran extensive testing to improve responses and coverage. 4. Educate and align the team We openly communicated how AI would help, not replace our support team. We showed how it would reduce mundane work and free them up to focus on more strategic, meaningful customer conversations. 5. Monitor, learn, and iterate We continuously tracked resolution rates, flagged weak responses, and kept refining the system. The Results • Faster, more consistent support for customers • 50% drop in manual support chats • A more energized support team, now focused on deeper issues, proactive outreach, and customer success initiatives The Takeaway AI isn’t just a tool. It’s a mindset shift. If your team sees it as a threat, you’ll hit resistance. But if you bring them along—show them how it removes the boring parts of the job so they can focus on the impactful ones, you unlock a whole new level of engagement. The real power of AI isn’t about replacement. It’s about elevation. Elevate your team. Serve your customers better. And don’t skip the groundwork. #AI #CustomerSupport #Automation #SmallBusiness #SaaS #Leadership #CustomerSuccess #ecommerce

Last week, I talked about the possibilities of AI to make work easier. This week, I want to share a clear example of how we are doing that at HubSpot. We’re focused on helping our customers grow. So naturally, we take customer support seriously. Whether it’s a product question or a business challenge, we want inquiries to be answered efficiently and thoughtfully. We knew AI could help, but we didn’t know quite what it would look like! We first deployed AI in website and support chat. To mitigate any growing pains, we had a customer rep standing by for questions that came through who could quickly take the baton if things went sideways. And, sometimes they did. But we didn’t panic. We listened, we improved, and we kept testing. The more data AI collects, the better it gets. Today, 83% of the chat on HubSpot’s website is AI-managed and our Chatbot is digitally resolving about 30% of incoming tickets. That’s an enormous gain in productivity! Our customer reps have more time to focus on complex, high touch questions. AI also helps us quickly identify trends—questions or issues that are being raised more frequently—so we can intervene early. In other words, AI has not just transformed our customer support. It has elevated it. So, here is what we learned: Don’t panic if customer experience gets worse initially! It will improve as your data evolves. Evolve your KPIs and how you measure success- if AI resolves typical questions and your team resolves tricky ones, they will need more time. Use AI to elevate your team's efforts How are you using AI in support? What are you learning? 

I’ve been asked a lot in the last few weeks about how we started to use AI for support…. We aren’t perfect and we definitely haven’t arrived, but for all the support leaders out there, here are a few things to consider as you transition to using more AI to support your customers. 1️⃣ Assessment of Support Processes: Start by assessing your current support workflows. Identify pain points, bottlenecks, and opportunities for improvement. Highlight the top 2-3 areas where AI could speed up the resolution for your customers. 2️⃣ Invest in AI Technologies: Embrace AI tools tailored to your support needs. From natural language processing to chatbots 🤖, explore solutions that align with your support goals and customer expectations. No two businesses are exactly the same, so do your homework. 3️⃣ Assess the numbers: Should you build it or buy it (more posts to come on this topic). Regardless of if you choose to build it or buy it, outlining a clear business case for the investment to share with other stakeholders is an important part of the adoption of any AI tools. 4️⃣ Build a Knowledge Hub: Lay the foundation for AI success by developing a comprehensive knowledge base. This foundation of information serves as the backbone for AI-driven responses, ensuring accuracy and efficiency. LLM’s thrive when the knowledge they are fed is extensive, accurate and detailed. 5️⃣ Prioritize Continuous Improvement: Monitor key performance metrics and gather feedback from both customers and agents. Use insights to refine AI algorithms, optimize processes, and deliver exceptional support experiences. You wouldn’t cut a brand new agent loose without QA and the same can be said for your “AI agent” Transitioning to AI does not have to lead to a degradation of service or even be scary for your team. Coupled with the right strategy it can enhance the experience for your customers and your agents and allow your team the time to focus on other areas of customer support. #CustomerSupport #AIInnovation #SupportLeadership #ContinuousImprovement #FutureReadySupport

While everyone's talking about AI replacing human agents, something more interesting is happening: technology and humans are forming a powerful partnership that's transforming customer experience. AI isn't stealing your agents' jobs – it's making them superheroes. At Callzilla - The Quality-First Contact Center, we've been implementing Agent Assist tools that give agents real-time support during customer interactions. The results speak for themselves: • Agent gets asked an impossible question? AI whispers the answer • Customer mentions an uncommon tech issue? Relevant articles appear automatically • Agent struggling to categorize the call? AI suggests the perfect reason code • About to make a mistake? AI catches it before it happens This creates a 'best of both worlds' scenario where technology handles routine tasks while agents focus on what humans do best: • empathy • genuine connection • creative problem-solving When to Automate vs. When to Humanize: • Let AI Handle: Repetitive tasks, basic info lookups, initial problem identification • Keep It Human: Complex problems, emotional situations, VIP customers who expect the red carpet treatment Pro tip: Give customers choice. Instead of forcing one path, ask: "We can have an agent available in 5 minutes, or you can chat with our AI assistant now who handles most issues. What works better for you?" Your tech should be: • Serving up answers faster than expected • Reducing agent cognitive load, not adding to it • Supporting natural conversation, not rigid scripts • Suggesting solutions, not just documenting problems AI doesn't replace your agents – it creates 'super agents' who resolve issues faster, with less effort, and greater accuracy. It's not about choosing between humans OR technology. It's about humans AND technology working together. The companies seeing the best results have figured out this perfect pairing – and their customers can't get enough. What's your experience with human-AI partnerships in CX?

In a recent project with Balfour & Co, the company was overwhelmed with nearly 20,000 customer support calls daily, straining resources and affecting efficiency. Empathizing with the support team’s struggle, I led a project to develop an automated solution to alleviate this burden. Balfour & Co was overwhelmed with unsustainable daily customer support calls, leading to long wait times and strained resources, 20k calls approximately, can you believe that?!! We designed and implemented a software solution to reduce call volume by automating responses to common queries. Action that helped execute this project successfully 1. Team Management: I led a diverse team using agile methodologies and tools like JIRA, Figma, and Slack for project management and collaboration. 2. Research and Development: We analysed call logs and customer feedback to design an AI chatbot capable of handling common queries. 3. Implementation and Testing: We developed, rigorously tested, and refined the chatbot, for efficient escalation handling. 4. Launch and Monitoring: Successfully launched the chatbot, continuously monitoring and improving its performance. Result: The AI chatbot reduced call volume by nearly 50%, easing the support team’s burden by sending order statuses, and customizations and guiding the customer through the website and improving customer satisfaction with quicker response times and 24/7 availability. Skills Developed - Project Management: This project enhanced my skills in team management and communication using tools like JIRA, Figma, and MIRO. - Task Prioritization: Learned to prioritize tasks for timely delivery and efficient problem-solving. - Empathy and Collaboration: Fostered a collaborative environment, valuing team input and supporting team challenges. This project was a significant milestone, reinforcing my passion for project management and my commitment to leveraging technology to solve real-world problems, equipping me with the skills and confidence for future challenges in project management roles. #ProjectManagement #CustomerSupport #Chatbot #TeamLeadership #TechInnovation #DigitalTransformation #AIChatbot #CustomerService #Automation #TechSolutions #BusinessSolutions #AIInAction #SoftwareDevelopment #LeadershipSkills