Choosing Ecommerce Customer Service Tools

Four years ago, I worked on a technical automation project for a client via Fiverr. This week, he reached out again, same client, new challenge. He needed a system where AI-powered agents could make personalized inbound & outbound calls to leads and then automatically handle all the follow-up tasks without human intervention. So, I built a connected automation using Retell AI, GoHighLevel (GHL), Make.com, and Chatdash that: ➡️ For inbound calls: Looks up the lead in GHL in real-time, sends the details back to the agent, and allows live appointment booking while on the call. ➡️ For outbound calls: Triggers from actions in GHL, sends lead info to the agent for a personalised approach, waits for the call to finish, gathers transcript + sentiment, and stores it in GHL. ➡️ Across both: Retell AI checks calendar availability, and Make.com books meetings based on the lead’s preferred time, no manual follow-up needed. Impact: ✅ Personalized conversations every time ✅ Automated note-taking and sentiment logging ✅ Faster appointment scheduling with zero back-and-forth Automation isn’t just about replacing task; it’s about enhancing human interactions so agents can focus on building relationships, not juggling tabs and CRMs. If your sales or support team still spends time searching for client info during calls or manually scheduling follow-ups, this is the type of automation that changes the game. PS: What’s one repetitive client interaction in your business you’d love to automate?

🎯 Enhancing Customer Service with AI in Microsoft Dynamics 365 CRM 🚀 Customer expectations are evolving, and businesses must adapt to provide faster, more personalized, and efficient support. Microsoft Dynamics 365 Customer Service is leading this shift with AI-driven innovations and automation-first experiences. Here’s what’s new in 2025: 🛠️ Key Enhancements in Dynamics 365 Customer Service 🔹 AI-Powered Case Summarization • Copilot now generates automatic case summaries from past interactions, enabling agents to get up to speed quickly. • Reduces manual effort and improves first-contact resolution rates. 🔹 Intelligent Routing with AI • Uses machine learning and natural language processing (NLP) to classify and route cases to the right agent or bot. • Ensures faster resolution times and improved customer satisfaction. 🔹 Proactive Issue Resolution with IoT & AI • Integrated IoT monitoring detects potential issues before customers even notice them. • Triggers automated case creation and assigns tasks to service teams before a failure occurs. 🔹 Virtual Agent Improvements • The built-in Copilot chatbot now offers more natural conversations and automated workflows for common issues. • Seamlessly integrates with Omnichannel for Customer Service, reducing agent workload. 🔹 Omnichannel Customer Engagement • Deeper integration with WhatsApp, SMS, and social messaging apps to enable real-time, AI-assisted interactions. • Supports live sentiment analysis to help agents tailor responses effectively. 🔹 Enhanced Knowledge Management • AI-driven knowledge article recommendations ensure agents always have the most relevant information. • Automated content updates keep documentation accurate without manual intervention. 💡 Business Impact ✔️ Faster response times and reduced case resolution effort. ✔️ More personalized customer experiences with AI-driven insights. ✔️ Improved agent productivity through automation and knowledge suggestions. ✔️ Cost savings by deflecting simple queries to AI-powered chatbots. 📌 Want to learn more? Check out Microsoft’s official release notes on Customer Service: https://lnkd.in/gvCtGZFd What’s your experience with AI in customer service? Have you implemented these features yet? Let’s discuss in the comments! 👇 #MicrosoftDynamics365 #CustomerService #AI #Automation #DigitalTransformation #CRM

Zendesk just rolled out auto assist procedure insights, giving admins powerful visibility into how AI-powered procedures are performing in real-time. The new dashboard provides three key metrics: • Tickets (30d) - How often auto assist follows procedures • Acceptance rate - How often agents approve AI suggestions  • Edit rate - How often agents modify suggestions 3 ways you can use this for your customer experience: 1. Optimize AI Performance - Identify which procedures need refinement based on low acceptance rates, ensuring your AI actually helps agents instead of creating more work 2. Data-Driven Training - Use edit rate insights to understand where agents struggle most, then create targeted training programs to improve both human and AI performance 3. ROI Measurement - Track procedure usage and acceptance to quantify the actual impact of your AI investment on agent productivity and customer resolution times This is exactly the kind of transparency we need to make AI truly effective in customer service - not just deployed, but optimized. Source: https://lnkd.in/d9JRvghP

AI + HI = Improved CX In today’s digital world, businesses strive to deliver exceptional customer experiences (CX) to stand out. While artificial intelligence (AI) has revolutionized CX by enabling automation, personalization, and efficiency, it cannot fully replace the human touch. AI enhances CX by processing vast amounts of data in real time, predicting customer preferences, and providing instant responses through chatbots, recommendation engines, and self-service options. It reduces wait times, offers 24/7 support, and ensures consistency across interactions. However, AI alone has limitations—it lacks emotional intelligence, creativity, and the ability to handle complex, nuanced customer concerns. Human agents bring empathy, critical thinking, and problem-solving skills that AI cannot replicate. When combined with AI, human agents become more efficient, as AI handles routine tasks, provides insights, and allows them to focus on high-value interactions. Impact on BPO KPIs 1. First Call Resolution (FCR) Improvement: • AI-driven knowledge bases and predictive analytics equip human agents with real-time solutions, reducing repeat calls. • Virtual assistants handle routine inquiries, allowing human agents to focus on complex issues. 2. Reduction in Average Handling Time (AHT): • AI-powered tools like speech analytics and automated summaries minimize the time agents spend on after-call work (ACW). • Virtual assistants can gather customer information before handing over to a live agent, speeding up resolutions. 3. Increased Customer Satisfaction (CSAT): • AI ensures faster response times and personalized interactions based on past behavior. • Human agents, equipped with AI-driven insights, can provide more empathetic and accurate solutions, improving overall satisfaction. 4. Enhanced Agent Productivity and Utilization: • AI automates repetitive tasks such as data entry, ticket classification, and FAQs, freeing up agents for complex interactions. • Sentiment analysis tools help agents adjust their approach in real time for better engagement. 5. Lower Cost Per Contact: • AI-driven self-service options reduce the volume of inbound calls and chats, lowering operational costs. • Intelligent routing ensures the right agent handles the right query, optimizing workforce efficiency. 6. Improved Net Promoter Score (NPS): • Personalized AI-driven recommendations and proactive outreach enhance customer engagement. • The combination of AI efficiency and human empathy fosters long-term customer loyalty. The synergy of AI and HI leads to an improved CX by ensuring speed, accuracy, and emotional connection. AI-driven insights empower human agents to offer proactive solutions, while human empathy ensures customers feel valued. AI and HI are not competitors but collaborators. Businesses that successfully integrate both will deliver superior CX, optimize BPO performance, and achieve sustainable growth in an increasingly digital world.

The AI Revolution in Call Centers: From Chatbots to Voice Synthesis In 2024, artificial intelligence is dramatically reshaping customer service, particularly in call centers, where 90% now utilize AI technology. This transformation is redefining how businesses engage with customers, offering enhanced efficiency and personalization. 🌍 Key Features and Benefits - Enhanced Efficiency: AI automates routine tasks, allowing human agents to focus on complex issues. - Improved Customer Experience: Faster, personalized service through data analysis and predictive capabilities. - Boosted Agent Productivity: Real-time assistance and automated post-call tasks streamline operations. - Cost Reduction: Automation and smart routing lead to significant savings. 🌍 Cutting-Edge Voice AI Technologies Recent advancements in voice tokenization and AI voice synthesis are pushing the boundaries of customer interactions: 1. dMel: A novel speech tokenization method that outperforms existing techniques in recognition and synthesis. 2. SpeechTokenizer: Combines semantic and acoustic tokens for a comprehensive speech representation. 3. Vec-Tok Speech Framework: A system for speech vectorization showing strong performance across various speech tasks. 🌍 Applications of Voice AI - Voice Cloning: Companies like ElevenLabs are creating high-fidelity voice cloning for customized AI agents. - Multilingual Support: AI-generated speech enables seamless multilingual service. - Emotional Intelligence: AI can modulate tone and emotion for empathetic interactions. - Personalization: Unique voice identities tailored to different customer segments. 🌍 Implementation Strategies 1. Assess Needs: Identify areas for AI implementation. 2. Start Small: Begin with select AI applications like chatbots. 3. Invest in Training: Prepare your team to work with AI technologies. 4. Choose Compatible Tech: Ensure seamless integration with existing systems. 5. Monitor and Iterate: Continuously evaluate and adjust AI performance. 🌍 Ethical Considerations Address ethical concerns regarding disclosure and potential misuse, prioritizing transparency in AI voice technologies. 🌍 Future Outlook The integration of advanced voice AI with existing solutions will redefine call center operations. With predictions of a 50% productivity increase and enhanced customer experiences, AI is set to deliver unprecedented efficiency and personalization in customer service. By leveraging these cutting-edge technologies, businesses can create more responsive and efficient customer service experiences, positioning themselves for success in an increasingly digital world. 1. Wang, L., et al. (2023). Voice‐based AI in call center customer service: A natural field experiment. Production and Operations Management. 2. Cornell University. (n.d.). AI in Contact Centers: Artificial Intelligence and Algorithmic Management in Frontline Service Workplaces. 4Enlight, AI Innovation Lab, AI Research Lab

Why Most “AI Support Bots” Still Fail Not because they lack automation. But because they lack context. Most systems automate replies  not resolutions. They save minutes but lose trust. That’s why we built the Thunai.ai Customer Support Automation Framework. It’s designed to make AI support feel human again  fast, accurate, and context-driven. Here’s how it works ↓ Ticket Categorization Automation → No manual triage, no lost priority emails. → Urgent issues rise automatically to the top. → Thunai reads every incoming ticket, identifies intent, and tags it instantly. Response Template Generation → Agents just review, personalize, and send. → Response time drops by 60%, quality stays consistent. → AI drafts context-aware responses based on company tone. Sentiment Analysis Integration → Thunai detects tone and emotion in customer messages. → Managers see mood trends across customers in real time. → Angry, confused, or happy  it knows how to route them right. Escalation Logic Setup → Rules built on “context, not keywords.” → Complex issues land directly with the right expert  not a random queue. → If AI sees repeated complaints, it auto-escalates before frustration spikes. Knowledge Base Auto-Updates → Every resolved ticket updates your help articles automatically. → FAQs, guides, and macros stay fresh without human effort. → Over time, support becomes smarter with every solved issue. Metrics That Actually Matter → Track response speed, resolution accuracy, and sentiment improvement. → Spot friction points before they become customer churn. → AI insights feed directly into performance dashboards. Support automation isn’t about replacing people. It’s about giving them the clarity and time to care again. The best customer experience comes from AI that understands context  not just text. ♻️ Repost this to help teams build smarter support systems. ➕ Follow Jegan Selvaraj for clear insights on context-first and agentic AI for enterprises.

This week I automated the process of identifying which clients are wrapping up a training and do not have anything else scheduled with us afterward. This week I built a small Power Automate flow that solves a problem we kept bumping into, but never took the time to automate. We store all of our client trainings in a single SharePoint list. Past, present, and future sessions all live together. The data was there, but the insight was not. The question we wanted to answer was simple: → Which clients are finishing a training this month and do not have anything else scheduled with us afterward? Manually, that meant filtering dates, scanning company names, cross checking future sessions, and then writing a follow up email. It worked, but it never happened as consistently as it should. So I automated it. Here is what the flow does: 1. First, it runs automatically on the first of every month. 2. It pulls all trainings that occur during the current month from SharePoint. 3. From there, it evaluates each company on that list and checks whether they have any trainings scheduled after the current month. If they do, the flow ignores them. 4. If they do not, the automation captures the company name and the name of their most recent training session and formats the results into a clean bulleted list. 5. Finally, it sends an email to our Director of Client Services with that list included in the body. Each bullet shows the company name and their latest training so follow up conversations are grounded in context. The email also includes a link to our full training library so she can easily dig deeper if needed. The outcome is simple but powerful. ★ Leadership gets a proactive view of clients who may need follow up. ★ Client services can prioritize outreach without pulling reports. No one has to remember to run a manual check every month. This is a good example of how automation does not need to be flashy to be valuable. Sometimes the best flows just make sure the right information reaches the right person at the right time, every time. If you are sitting on good data but still relying on reminders and manual checks, this is usually a sign there is an automation opportunity waiting. Let’s start building!

𝐂𝐗𝐎𝐬: 𝐖𝐡𝐚𝐭 𝐈𝐟 𝐘𝐨𝐮𝐫 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐂𝐨𝐮𝐥𝐝 𝐁𝐞 𝐁𝐨𝐭𝐡 24/7 𝐚𝐧𝐝 𝐃𝐞𝐞𝐩𝐥𝐲 𝐇𝐮𝐦𝐚𝐧 𝐰𝐢𝐭𝐡 𝐀𝐈? Here’s the challenge: Customers demand instant, 24/7 support, but they also want empathy and personalized solutions. 𝐀𝐈 𝐚𝐥𝐨𝐧𝐞 𝐜𝐚𝐧’𝐭 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐭𝐡𝐚𝐭. 𝐇𝐮𝐦𝐚𝐧𝐬 𝐚𝐥𝐨𝐧𝐞 𝐜𝐚𝐧’𝐭 𝐬𝐜𝐚𝐥𝐞 𝐭𝐡𝐚𝐭. 𝐁𝐮𝐭 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫? That’s where the magic happens. This is 𝐇𝐮𝐦𝐚𝐧-𝐢𝐧-𝐭𝐡𝐞-𝐋𝐨𝐨𝐩 (𝐇𝐈𝐓𝐋)—the perfect blend of AI efficiency and human empathy. 𝐖𝐡𝐲 𝐒𝐡𝐨𝐮𝐥𝐝 𝐓𝐡𝐢𝐬 𝐌𝐚𝐭𝐭𝐞𝐫 𝐭𝐨 𝐘𝐨𝐮? Because 64% 𝐨𝐟 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬 𝐝𝐨𝐧’𝐭 𝐭𝐫𝐮𝐬𝐭 𝐀𝐈-𝐨𝐧𝐥𝐲 𝐬𝐞𝐫𝐯𝐢𝐜𝐞 (Gartner). And because 53% 𝐰𝐨𝐮𝐥𝐝 𝐬𝐰𝐢𝐭𝐜𝐡 𝐭𝐨 𝐚 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐨𝐫 𝐢𝐟 𝐭𝐡𝐞𝐲 𝐟𝐞𝐥𝐭 𝐀𝐈 𝐦𝐚𝐝𝐞 𝐢𝐭 𝐡𝐚𝐫𝐝𝐞𝐫 𝐭𝐨 𝐫𝐞𝐚𝐜𝐡 𝐚 𝐡𝐮𝐦𝐚𝐧. Your customer service strategy can’t be “AI vs. Humans.” 𝐈𝐭 𝐦𝐮𝐬𝐭 𝐛𝐞 𝐀𝐈 𝐰𝐢𝐭𝐡 𝐇𝐮𝐦𝐚𝐧𝐬. 𝐇𝐨𝐰 𝐇𝐈𝐓𝐋 𝐖𝐨𝐫𝐤𝐬 𝐢𝐧 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 1️⃣ AI handles repetitive tasks like FAQs, tracking orders, or simple troubleshooting. 2️⃣ Complex or emotional issues? AI escalates seamlessly to a human agent—no context lost, no frustration added. 3️⃣ During live interactions, AI assists agents with real-time insights, suggested responses, and customer history to resolve issues faster. 4️⃣ Agents provide feedback on unresolved queries, continuously improving the AI system over time. It’s a partnership: AI does the heavy lifting; humans bring the heart and creativity. 𝐖𝐡𝐚𝐭’𝐬 𝐢𝐧 𝐈𝐭 𝐟𝐨𝐫 𝐘𝐨𝐮 𝐚𝐬 𝐚 𝐂𝐗𝐎? ✅ Efficiency at Scale: Automate routine tasks without compromising on quality or empathy. ✅ Higher Customer Satisfaction: Customers get instant resolutions from AI and personalized care from humans when needed. ✅ Cost Savings + Retention Gains: Reduce operational costs while building loyalty through exceptional service experiences. ✅ Actionable Insights: Escalations and feedback help refine both your AI systems and your overall strategy. 𝐓𝐡𝐞 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐄𝐯𝐞𝐫𝐲 𝐂𝐗𝐎 𝐒𝐡𝐨𝐮𝐥𝐝 𝐀𝐬𝐤 Is your customer service strategy designed to scale with empathy? The companies that master this balance—leveraging AI to empower humans—will lead their industries in 2025 and beyond. Great customer service isn’t just automated; it’s orchestrated. And HITL is how you make it happen. What’s your take on blending AI with human expertise? Let’s discuss! 👇 #AI #CustomerService #CXLeadership #Innovation #HumanInTheLoop #DigitalTransformation

In my work with back-office and customer support teams in logistics and other B2B service areas, I find they’re often overwhelmed.   They’re fielding endless “Where’s my shipment?” emails, entering the same data into multiple systems, and chasing updates across siloed platforms. Most of these teams are doing heroic work — but they’re stuck in reactive, manual workflows.   Over the past decade, traditional AI tools — including machine learning models, regression analysis, and optimization algorithms — have made operations smarter and more efficient. We’ve seen them drive real value through things like: * Route optimization * Demand forecasting * Inventory and network planning * Load consolidation Dynamic pricing   But generative AI opens a new frontier — one that transforms how customer-facing teams interact, communicate, and respond.   We now have AI tools that can:   * Instantly answer tracking and status questions * Generate proactive updates before the customer even asks * Interpret and summarize internal systems in plain language * Draft accurate, personalized responses at scale   This isn’t just automation — it’s a fundamental shift in how we serve customers. It improves response times, eliminates bottlenecks, and significantly reduces the cost to serve.   The organizations that adopt these tools thoughtfully — and integrate them into real workflows — will gain a serious competitive advantage.   Are you rethinking how your teams serve customers? #LogisticsTech #GenerativeAI #DigitalTransformation #CustomerExperience #AIinBusiness #Automation #OperationsExcellence

Process chaos isn’t just frustrating. It’s destroying your profit margins. I saw this in action yesterday: a nail appointment turned into a 2-hour productivity nightmare. 💅 Not because they were busy. Not because they were short-staffed. But because of process blindness. The scene was painfully familiar: no appointment system, constant interruptions, staff juggling too much, and frustrated customers. If this sounds like your business, you’re leaving money on the table. Research shows automation can free up 20–30% of managers’ time and improve accuracy and efficiency across the board. Throwing more hours or people at process problems doesn’t solve them. You need intelligent systems to cut through the noise. Here are 7 automation solutions we implement in our Culture & Workflow Reset program, with simple action steps: 1️⃣ Client Communication Hub AI phone systems handle calls and bookings automatically. ⏱ Cuts interruptions, saves 3–5 hours per week per employee. 👉 Replace your front-desk phone with an AI-enabled system that auto-books into your calendar and routes urgent calls only. 2️⃣ Automated Client Experience Smart follow-ups, confirmations, and reminders. 📈 Reduces no-shows by up to 29% and boosts client satisfaction. 👉Use an AI CRM that sends automated confirmations, follow-ups, and post-appointment surveys without staff time. 3️⃣ Intelligent Task Management AI assigns and prioritizes work. ⚡ Cuts management overhead by 25–30% and reduces delays. 👉 Integrate tools like Asana, ClickUp, or Monday.com with AI rules so recurring tasks are auto-assigned to the right person. 4️⃣ Process Documentation Auto-generated SOPs and training guides. 📘 Speeds onboarding by 40% and reduces early mistakes. 👉 Use AI transcription and process mapping tools like Scribe or Loom to automatically turn workflows into step-by-step guides. 5️⃣ Real-Time Customer Analytics AI feedback and trend tracking. 🔍 Issues identified 2x faster, with 75% more accurate resolutions. 👉 Add AI-powered survey tools like Qualtrics or Medallia that analyze responses instantly and flag emerging issues. 6️⃣ Admin Automation Smart invoicing, reporting, and data entry. 💰 Saves 8–10 hours per month per employee, with more than 90% accuracy. 👉 Connect your finance system to AI-powered invoicing like QuickBooks, Xero, or Bill.com so invoices and reports run automatically. 7️⃣ Dynamic Resource Planning AI-optimized scheduling and resource allocation. 📊 Improves utilization by 20% and reduces overtime costs by 25–30%. 👉 Use AI scheduling tools that balance workload across staff, auto-adjust when demand shifts, and prevent double-bookings. Ready to stop losing time and money to process chaos? Comment RESET or DM me to book your 30-minute Workflow Assessment. ♻️ Share if your company needs a culture reset ➕ Follow Rene Madden for more insights on driving transformation in financial services