How to Automate Customer Interactions

How we built AI agents that run a LOT of our business using n8n (detailed breakdown) After a few months of refining our automation stack at Kendo ai and my other companies, I want to share exactly how we're using n8n to create AI-powered workflows that operate 24/7 First, what is n8n? It's an open-source workflow automation tool that connects your apps, data, and APIs. Think Zapier but far more powerful and customizable. Here's our exact setup for creating autonomous agents: The foundation: Customer data flow Every customer interaction feeds into our CRM n8n monitors for trigger events (new signup, support request, etc.) Custom nodes extract relevant context from these events Real example: When someone books a demo, our n8n workflow instantly creates a personalized onboarding sequence based on their company size, industry, and the specific features they showed interest in. The intelligence layer: AI integration n8n connects to Claude API and GPT-4 for different reasoning tasks We've built custom prompts for each business function Webhooks allow the AI to trigger specific responses Real example: Our support system has n8n workflows that analyze incoming tickets, categorize the issue, retrieve relevant documentation, and draft personalized responses for our team to review before sending. The action layer: Automated responses Sentiment analysis determines appropriate response paths n8n routes information to the right team member Custom logic handles exceptions and escalations The continuous improvement cycle: Every interaction gets logged and analyzed n8n pulls data weekly to identify bottlenecks Successful patterns get reinforced in updated workflows The game-changer has been creating specialized agents for different functions: Content Agent: Monitors our post performance, suggests topics based on search trends, drafts outlines, and schedules publication Sales Agent: Uses customer info to help create the ai prospects inside of Kendo Ai. Basically creating randomized life stories for the Ai Data Agent: Pulls insights from customer behavior, generates reports, and flags opportunities we're missing Advanced techniques we're using: Chaining multiple n8n workflows together for complex decision trees Using temporary data storage to maintain context between workflow runs Creating feedback loops where one agent can trigger another Start with a single, high-value process and perfect it before expanding. Our first workflow just handled meeting scheduling, but it was the foundation for everything else. (Pro tip: Start with the cloud version to learn, then migrate to self-hosted for more control and to avoid workflow execution limits) N8N is like zapier on steroids and while it has a bit of a learning curve, it is well worth the time investment and automating things inside of your business Comment "n8n" below and i'll try my best to send you all some of the templates we use 🤝🏽 #n8n #ai

Still sending manual emails to your customers? Here’s how we automated the entire email marketing funnel for our client. Most large enterprises have already embraced AI to track SKUs, forecast hiring, and optimise financial decisions. But when it comes to marketing? They’re still stuck with batch-and-blast emails… generic content, poor timing, zero personalisation. AI is improving how companies work but not yet how they connect with customers. Recently, we helped a retail client move from batch emails to AI-driven journeys using Salesforce Marketing Cloud. 📍We mapped customer data across touchpoints to build unified audience profiles 📍We set up automated, trigger-based journeys tailored to user behavior and purchase history Within 3 months: ↪️ Customer engagement increased by 38% ↪️ Repeat purchases rose by 22% especially among previously inactive users By connecting customer data and automating responses, their marketing became timely, relevant, and proactive. Remember, when AI powers the backend and the customer experience, that’s when real growth happens. Which part of your marketing funnel do you think AI should automate next?

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?

We built a Zendesk email assist AI agent and it's handling a full quarter’s work for one human support rep. Here's the step-by-step flow: 1. User sends a complex or nuanced product question to support@voiceflow.com 2. Tico (our AI agent) reviews the question and passes the content and intent. 3. The most fitting knowledge base is tapped via confidence level. 4. A personalized, accurate & highly-specific response is drafted. 5. The draft is slotted into Zendesk as a private comment. 6. Our team reviews, tweaks if necessary, and sends it to the user. This has slashed the onboarding and training time for support staff that's typically slowed down by the complexity of the product. The impact? ✅ Our support team is no longer just keeping up; they’re ahead, delivering faster, sharper responses. ✅ Customers feel understood, their issues addressed with pinpoint accuracy, boosting our CSAT scores. ✅ Tico’s continuous learning means every interaction makes it smarter, ready for even the most nuanced queries. So far, Tico Assist is tackling over 2000 tickets - a full quarter’s work for one human support rep, for less than the price of lunch. If you’re navigating high support volumes with a lean team, this type of Zendesk AI Assist Agent can help blend automation with quality for your customers. P.S. Tico doesn’t just fetch any answer. It pulls from the most relevant knowledge base (e.g. a technical code response for a developer question). From my post last week, this multi-knowledge base strategy is something that I think we will see much more of in CX this year.

Last month our team of 5 did the work of 50 people. While taking every weekend off. The secret? We replaced the most expensive job with code: Let me show you exactly how this works. Three features transformed our support from "answers questions" to "handles entire workflows": 1. Guidance: When someone requests a feature, our AI: - Thanks them properly - Logs feedback automatically - Directs to feedback portal - Updates them on progress - Maintains perfect brand voice 2. Processes: Take a refund requests. Our AI: - Checks account status - Verifies eligibility - Processes through Stripe - Sends confirmation - Logs everything instantly 3. Actions: This is the real power. AI can: - Pull CRM data - Process payments - Update records - Trigger notifications - Make API calls Real workflow example: Customer: "Can I get a refund?" AI: - Verifies account instantly - Checks eligibility - If eligible: processes immediately - If not: explains why + alternatives - Everything logged in seconds What used to take 30 minutes Now happens automatically. Start with feature requests. It's simple but shows the power. Then you'll want to automate everything. Because your support team should solve problems. Not copy-paste responses at 3AM. What would you automate first? Interested in seeing how Helply can do this for you? Shoot me a DM

🫶 What do the 3 New Autonomous Agents offer for Dynamics 365 Contact Center & Customer Service? As the public preview for the 3 autonomous AI agents progresses, recently I've been discussing their impact with clients and wanted to pull together some key features and benefits into a single slide, so here you go. ⚙️ Case Management Agent This agent revolutionises the case lifecycle by automating the creation, updating, and resolution of cases across chat, email, and other service interactions. It reduces average handling time, minimises errors, and frees up customer service representatives to focus on more complex and value-driven tasks. 🧠 Customer Intent Agent Leveraging generative AI, this agent continuously learns from historical interactions to understand customer intent in real-time. It builds an evolving intent library that powers smarter self-service and delivers contextual support to human agents. The result? A more intuitive, responsive, and scalable service experience for customers. 📚 Customer Knowledge Management Agent Maintaining an accurate and useful knowledge base has always been a challenge. This agent simplifies the process by autonomously generating and updating knowledge articles from real-world cases, conversations, and notes. It ensures your content remains relevant and actionable while reducing the burden on service teams. As I mentioned, you can begin using all 3 agents now as part of the paid public preview (Copilot Studio message capacity required). If you've been using the agents, would love to hear your feedback in the comments. Learn more and get started: https://lnkd.in/erNDSkWg #autonomousagents #contactcentre #customerservice #d365

Checklist: What to Prepare Before Automating 50% of Your Support Tickets AI agents are powerful but if you automate chaos, you just get faster chaos. Before handing over 50% of your support tickets to automation, here is what needs to be in place 👇 1. Enlist Top Repeat Issues Start with the obvious: “Where’s my order?”, “How do I reset my password?”. These are the low-effort, high-impact wins. 2. Identify Support Friction Look for high volume, high effort, or emotional triggers - pull past tickets, tag by intent, not product. That’s where automation makes an impact. 3. Know What Not to Automate Keep humans in the loop for nuanced tasks like refunds, legal issues, or sensitive escalations. Don’t delegate complexity to bots. 4. Set Confidence Thresholds Command it to respond only when your AI is more than 90% sure. Bots guessing will result in broken trust and bad experiences. 5. Build Escalation Paths There should be no dead ends. If the bot cannot help, it should hand off instantly to a human agent seamlessly. 6. Use Real Data, Not Assumptions Use real customer conversations, not made-up examples. Train on real tickets, as the answers are already in your inbox. 7. Involve Your Team Your human agents know what is slowing them down. So, use that input to guide automation priorities. 8. Match the Tool to the Task Not everything needs AI. Use decision trees for simple queries, backend bots for lookups, and AI agents for multi-step workflows. Prepare well, and you are not just saving costs instead unlocking better CX. What is one support task you can’t wait to automate? #CustomerSupport #AIChatbots #SupportAutomation #SaaS #VoiceAgents #ArtificialIntelligence #AI