Customer Experience Improvements Through Efficient Responses

Came back from vacation Monday. Inbox? On fire.🔥 Buried in the chaos: a customer story that stopped me in my tracks (and made me so happy). A Customer Support leader at a fast-growing financial services company used AI to transform his team - in just a few weeks. This leader works for a financial services company that’s in high-growth mode. Great news, right? Yes! For everyone except his Customer Support team… As the business grew faster, they were bombarded with repetitive questions about simple things like loan statuses and document requirements. Reps were overwhelmed. Customers faced longer response times. The company has been a HubSpot customer for nearly 10 years. They turned to Customer Agent, HubSpot’s AI Agent, and got to work: - Connected it to their knowledge base → accurate, fast answers - Set smart handoff rules → AI handles the simple, reps handle the complex - Customized the tone → sounds like them, not a generic bot (you know the type) In a short space of time, things changed dramatically: - Customer Agent now resolves more tickets than any rep - 94.9% of customers report being happy with the experience - For the first time, the team can prioritize complex issues and provide proactive support to high-value customers It’s exciting to see leaders using Customer Agent to not just respond to more tickets, but to increase CSAT and empower their teams to drive more impact. 2025 is the year of AI transformed Customer Support. I am stunned by how quickly that transformation is playing out!

The number 1 driver of customer satisfaction for accountants: Not: Technical ability Not: Your tech stack Not: Your website aesthetic It's answering the d*** phone. Responding to emails. Following through on [your desired comms channel] within [timeframe your client expected]. It isn’t a high bar these days, but simply being responsive and following through puts you ahead of the pack. 13 tips to standardize comms & align expectations: 1. Communicate a standard turnaround time. Doesn’t matter what it is, it just needs to exist. 2. Not all requests are created equal. Your turnaround time is your *acknowledgment* time. Many requests will take longer to resolve. 3. The only exception is when you’re OOO. So don’t forget your OOO, or pull in a teammate when you’re out. 4. Over-communication beats under-communication. Never be afraid to send a quick update, or a no-update update. 5. Don’t leave turnaround time up to your team to decide. For each role there’s a rule, and we’re all held to our turnaround time rules. 6. Your availability is the most scarce in your firm. If it isn’t, why won’t clients just go to you every time? 7. Design turnaround times to drive client behavior. For example an immediate call with an admin, same-day call with a staff, 72 hour call with the big boss. 8. No channel should jump the line. If you respond to that text, they’ll never follow the flow again. 9. Where possible trade synchronous work - let’s have a quick call to discuss - with asynchronous work - here’s a loom outlining my proposed solution, and a scheduling link if we still need to discuss. 10. In almost no situation should the big boss be taking unscheduled client comms of any kind. 11. Enable self-service wherever possible. Fetching docs from their own portal, paying an invoice online etc. 12. Integrate response times into how team members are incentivized. Be careful rewarding over-responsiveness, but keep a close eye on under-responsiveness. 13. Wrangle rogue channels. You make the rules about how clients can interact with your firm. Any comms outside those channels must be redirected. Clients are no different than mice in a maze. If they can get the cheese by texting you, calling you directly, they’ll never go through your team again.

Financial services is turning customer service into a 24/7 AI front door. Leaders expect 20% lower cost to serve and response times improving by more than 20%. Here’s what we learned reviewing Roland Berger’s new FS report: ✅AI is moving from pilots to production. By 2027, 92% of leaders expect AI to be very important in service. ✅The outcomes they are targeting are clear: 16% higher process efficiency, 12% NPS lift, and a 12% reduction in service headcount while preserving quality. ✅The tech stack is ready. The gap is operational - clean data, unified systems, and human-in-the-loop guardrails. Main Street takeaway: community banks, credit unions, and local agencies can win on speed and trust at the same time. You do not need a massive transformation. You need one well-chosen workflow and a clean handoff to your team. Small businesses can implement this by: 1️⃣Start with one high volume queue, password resets, balance checks, claim or payment status. 2️⃣Connect the context, core system, CRM, phone, and knowledge base so AI can read status and show its work. 3️⃣Set guardrails, auditable logs, escalation paths, and clear handoff to a person for edge cases. 4️⃣Measure outcomes, cost to serve, first contact resolution, handle time, and CSAT or NPS. 5️⃣Train people, not just models, teach agents to review, correct, and coach the AI. The results speak for themselves: when you unify data and pilot beside your agents, customers get faster answers and fewer call backs, and your team focuses on the conversations that actually need a human. If you run a local bank or insurance office, this is the moment to pick one queue and prove the ROI in 30 days. Keep it simple. Track the numbers. Then scale. P.S. This is Report 4 of 7 in my Industry AI series this week. What industry should I break down next?

As an e-commerce business owner, here’s one metric you shouldn’t ignore in 2024: First response time - the time it takes to respond to a customer's initial outreach.  Your first response time can make or break the entire customer experience.  If it's too slow, you risk losing trust and future business.  Most customers expect a response within 1 hour.  After 1 hour, they start questioning your reliability.  After 24 hours, many will give up and go to a competitor. Do you know what your average first response time is?  If not, start tracking it now.  Getting under 1 hour should be a top priority.  Quick responses show customers you are on top of things, care about their needs and are ready to provide excellent service.  This builds loyalty and increases repeat purchases. So monitor and improve your first response metrics, especially on high-priority channels like live chat.  It's one of the most impactful things you can do to stand out from the competition.

Learnings from transforming CX with Gen AI for a Financial Services giant in APAC 🚀 One of the largest Financial Services players in the APAC recently leveraged Verloop to transform its contact center. The outcomes? Transformational change in customer support experience which not only drove CSAT up but also helped them bring efficiency into their CX Ops. Here is a snapshot of outcomes and learnings Outcomes -------------- 1. About 30% increase in Customer Satisfaction score 2. 43% fewer tickets assigned to their support desk 3. 70% Reduction in Average Response Time 4. 30% Cost Savings by CX efficiency Learnings -------------- 1. Effort - Easier said than done; most models are great for building demos but a nightmare when implementing large complex scenarios 2. Focus - Niche-trained LLMs work better than a large model 3. Latency - Latency in response especially in audio calls is a deal breaker. 4. RAG + LLM - Balancing when to refer to RAG vs when should LLM handle the task takes a while 5. Cost - Models cost significant amount of money to run; attach and focus on business outcomes 6. Data Quality - Investing time in data cleansing and organization pays off massively 7. AI + Human - AI handles the repetitive tasks, while AI-assisted human agents are required for empathy and complex problem-solving 8. Keep Building - Continuous improvements and training of flows is critical more so in the first few months of launch Implementing Guardrails --------------------------- 1. Focus on Ethical AI usage with strict guidelines to ensure AI operates within ethical boundaries, maintaining transparency and customer trust. 2. Adhere to rigorous data privacy regulations to protect customer information. Protecto works like a charm! 3. A key trait of any such implementation is AI knowing when to hand over Launch Experience -------------------- 1. Collaborative Approach - Everyone is learning in this journey; engage early and frequently with all stakeholders 2. Stay Agile - Launch iteratively and keep improving instead of one big bang launch 3. Human training - Focus on training all stakeholders; things are different vs structured data We started Verloop with the idea that the future of contact centers is AI-first, human-assisted. These engagements help us stay on the course and keep building towards our vision. We are already living in the future and it is slowly spreading everywhere! 🌟 #contactcenter #GenAI #CXTransformation #transformation Verloop.io CA. Ankit Sarawagi Melisa Vaz Nikhil Gupta Urvashi Singh Kiran Prabhu Ravi Petlur Kumar Gaurav