Smart Customer Experience Solutions

AI in Customer Support isn’t new. I’ve been rethinking how we actually use it. Customer Support is moving past basic "faster replies" and learning to implement Claude as a core part of our workflow. The goal? Shifting from reactive firefighting to structured, scalable systems. It’s a work in progress, but here is the blueprint we’re using to turn Claude into a true CX reasoning engine: 1️⃣ It’s not about speed. It’s about structure. Yes, you can draft replies faster. But the real value comes from setting it up properly: → align it with your tone and guidelines → connect it to your knowledge base → define clear boundaries (what it can and can’t say) → train it to understand context, not just keywords That’s how you get consistent, reliable output across the team. 2️⃣ It helps move Support from reactive → proactive Used well, it’s not just answering tickets. It’s helping you: → detect sentiment and urgency → identify recurring friction points → surface gaps in self-service → spot early churn signals That’s where Support starts influencing the whole customer experience. 3️⃣ It fits into your existing workflows (not replaces them) The most effective setups I’ve seen are simple: → Claude + Zendesk → ticket analysis → Claude + Zapier → automate workflows → Claude + Gong→ review calls → Claude + Intercom → inbox support → Claude + n8n → workflow automation → Claude + Notion → knowledge management No complex rebuilds. Just better use of what you already have. 4️⃣ The quality of output = quality of input Small things make a big difference: → assign a role (support agent, CX lead, analyst) → provide context (customer, goal, constraints) → iterate with examples (good vs bad responses) Without this, you get generic answers. With it, you get something your team can actually use. From a leadership perspective, this isn’t about “adding AI.” It’s about designing how your Support team operates at scale. Because the goal isn’t to answer more tickets. It’s to build a system where fewer things break, and when they do, the experience still feels consistent. If you’re already using AI in Support, what’s actually working for you? 👇

I’m not asking my CSMs to resolve support tickets. I’m asking them to leverage them. Support tickets aren’t just a backlog of problems; they’re customer truth bombs waiting to explode. If you’re not mining them for insights, you’re flying blind—and that’s exactly how churn sneaks up on you. Every Customer Success team I’ve ever led has been trained to use Support tickets strategically. Why? Because they’re packed with insights that make us better at our jobs. ✅ We learn more about the product. ✅ We spot trends before they become problems. ✅ We understand our customers’ use cases more deeply. If you’re not tapping into support data, here’s what you’re missing: 🔥 Emerging Pain Points Recurring issues expose friction in the customer journey. Ignore them, and those minor frustrations turn into churn-worthy headaches. 🔥 Product Gaps Customers vote with their tickets. If the same feature requests or usability complaints keep surfacing, your roadmap is practically writing itself. 🔥 Engagement Risks A spike in tickets isn’t just noise—it’s a flare. Users don’t submit tickets when they’re thriving; they do it when they’re stuck, frustrated, or in need of more enablement. Here are a few ways my team and I are using these insights: ✅ Spot & Engage Struggling Users A surge in ticket volume? Proactively reach out before frustration turns into a cancellation. ✅ Create Targeted Content If the same questions keep coming up, turn those insights into help docs, webinars, or office hours. ✅ Surface Expansion Opportunities Seeing frequent feature requests? Build them—or better yet, use them to tee up expansion conversations. ✅ Map Out User Behavior Support tickets tell you who’s onboarding, who’s adopting new features, and who’s stuck. Use that data to drive deeper engagement. ✅ Collaborate with Product Your product team needs this intel. Share support trends regularly to influence meaningful fixes and features. High ticket volume isn’t necessarily a bad thing—but you need to know how to use it to your advantage. Bottom line? CSMs don’t need to fix support tickets. But the best ones know how to use them to drive retention, expansion, and adoption. _____________________________ 📣 If you liked my post, you’ll love my newsletter. Every week I share learnings, advice and strategies from my experience going from CSM to CCO. Join 12k+ subscribers of The Journey and turn insights into action. Sign up on my profile.

Today I noticed something interesting on LinkedIn. Several ads in my feed were addressing me by my name. Not in the comments. Not in a mention. Right in the ad creative itself — first name, at scale. At first, I wondered if it was a coincidence. Then I realized LinkedIn has rolled out personalized ad capabilities — where advertisers can use real profile data like first name, job title, company name, and industry to dynamically tailor the ad experience for each viewer. No guesswork or creepy scraping. It’s a built-in feature tied to Dynamic Ads and personalization macros that pull directly from a member’s profile at the time the ad renders. What’s fascinating as a marketer is how this blends relevance with scale. Instead of generic spray-and-pray campaigns, brands can create creative templates like: “%FIRSTNAME%, here’s how teams like yours unlock growth.” and LinkedIn replaces the macro with your actual name when you see the ad. We’ve talked for years about hyper-personalization in email and account-based marketing. Now it’s directly in sponsored content — in the feed itself. That’s a big deal for anyone running digital campaigns: it’s not just about better targeting, but about being personally relevant without losing scale. For marketers and advertisers, this feels like a step toward truly intelligent performance marketing on LinkedIn — where message, context, and audience align in a way that’s both respectful and resonant. And for the rest of us? It’s a reminder that in the right hands, advertising doesn’t interrupt — it converses. #LinkedInAds #DigitalMarketing #Personalization #ABM #PerformanceMarketing #SpeakupwithBhumica

POST-4/7👉 Email used to be a megaphone. In 2025, it’s a whisper in a very specific ear. Gone are the days when “blast to all” could pass as a strategy. In fact, that approach in 2025 is actively hurting your deliverability. Email Service Providers (ESPs) like Gmail, Yahoo, and Outlook are no longer just evaluating your IP health—they’re scoring your sender behavior at the recipient level. That means if 40% of your list is cold or disengaged, Gmail sees you as the problem—not just the user. ⚠️ Real Consequence: 1. We audited an ecommerce fashion brand with 220K contacts. Over 92K of them hadn’t clicked a single email in 90+ days. Gmail flagged them for bulk spam behavior, and inboxing fell from 78% to 46% overnight. 2. They were running promos weekly. Nothing was technically broken—but nothing was relevant. That’s what got them crushed. What Micro-Segmentation Solves in 2025: ✅ Reduces spam complaints ✅ Increases engagement velocity ✅ Signals positive intent to inbox providers ✅ Unlocks higher revenue per send with smaller cohorts Micro-Segmentation Tactics That Work Now: 1. Behavior-Based Journeys: Forget static tags. If someone viewed winter boots but didn’t buy, your next 3 emails better talk about warmth, snow, or style—not your general spring lookbook. ✅ Klaviyo + Shopify data lets you trigger flow branches based on: Last viewed product category Cart abandonment by SKU group Pages viewed in session (via UTMs or on-site behavior) Pro Tip: Use dynamic content blocks inside campaigns to adjust hero sections based on browse activity without cloning entire flows. 2. Lifecycle Automation by Spend Velocity This isn’t “new vs returning” logic anymore. In 2025, flows shift based on: Time since last order AOV trends SKU replenishment cycles Example: First-time customer who hasn’t returned in 30 days → “2nd purchase incentive” High-value buyer within 7 days → “VIP early access” Customer inactive 60+ days → Winback + dynamic offer block + channel sync suppression 3. AI-Supported Clustering Tools like RetentionX, Lexer, and even Klaviyo’s predictive analytics are now building multi-dimensional customer clusters using: Purchase frequency Channel source Time to second order Category loyalty It’s loyal mid-value buyers who shop monthly but only when free shipping is offered. ✅ What to do: Export these clusters to your ESP Build messaging that maps exactly to their past actions Suppress low responders from paid channels and warm email instead. Ready to Execute? Create 5 foundational micro-segments: 1. High spenders 2. First-time buyers 3. VIPs (CLV > 2.5x avg) 4. Dormant >90 days 5. Active clickers, no conversion Test 2 cadences per segment: VIPs: 4x/month + early access Dormant: 1x/month reactivation with content—not promos Use Recency, Frequency, and Monetary score buckets to tag customers and let your automations react to movement between them. #EmailMarketing #email

"We noticed you haven't logged in for 60 days..." This is NOT how you build loyal customers. If you're only reaching out after two months of silence, you've already lost them. After analyzing thousands of customer journeys, I've found a clear pattern: By day 14 of inactivity, the probability of churn increases by 67%. By day 30, it jumps to 85%. By day 60, you're just sending emails to ghosts. Here's why reactive customer management destroys loyalty: 1. You're ignoring early warning signs - Engagement decline is gradual, not sudden - Behavioral shifts appear weeks before complete disengagement - Your CRM has the data, but you're not using it proactively 2. You're demonstrating that you don't pay attention - Customers notice when you only care after they've left - The 60-day mark proves you're tracking metrics, not relationships - Your message screams "we only noticed when our numbers changed" 3. You've missed the intervention window - Emotional connection breaks down completely after 30 days - Habit loops get replaced with competitor experiences - The cost of reacquisition is now 5-7X higher than early intervention 4. You're confirming their decision to leave - Late outreach validates their choice to disengage - The generic "we miss you" message feels disingenuous - You've proven they made the right choice by leaving 5. You're treating symptoms, not causes - Reactive messages don't address why they left - Generic reactivation campaigns ignore individual context - The problems that drove them away still exist So what does proactive customer management look like? ✔️ Monitor engagement velocity, not just binary active/inactive states ✔️ Create interventions at the first sign of behavior change (often day 5-7) ✔️ Develop usage milestone celebrations that prevent disengagement ✔️ Build relationship-deepening touchpoints during high engagement periods ✔️ Design preemptive educational content for common drop-off points The best brands don't wait for customers to leave. They make it impossible to imagine wanting to go. Want to learn how to build a proactive customer retention system that prevents churn before it starts? Comment "PROACTIVE" below for our complete strategy guide ✅

Warning - potentially upsetting logistics sales post from a logistics managers point of view... As a logistics manager I regularly receive multiple sales calls per day. I know from experience that sales teams in freight forwarding work hard to win new customers, you are all legends in your own right. Cold calls, emails, meetings - it all takes time and effort to bring new business on board. I've been in logistics a long time so I genuinely like speaking to logistics companys, I have worked with most, but I can't work with everyone all the time. First and foremost I have to manage the logistics needs of the company. So, this can mean, if things aren't working out, we need to see other people. It's not me, its you. So what goes wrong? Here are a few things that can lose you business. ❌ The wrong approach to problem solving I’ve lost count of the times I’ve been told over the years, "If you have a problem, call me." It sounds like a perfectly reasonable request but surely that’s the wrong way around? If something goes wrong, I shouldn’t need to chase you - you should be calling me. Be proactive - jump on issues immediately and update your customers. I'd be happier hearing "there's a problem but I'm on it" over "I didn't know there was a problem, I'll get on it" ❌ Lack of proactive updates My team or I shouldn’t have to chase you for shipment updates. If we are always the ones chasing then we will soon become frustrated. Be proactive - look at implementing automatic updates. As a customer I'd rather have more updates than I need than be left in the dark. ❌ Ignoring small issues until they become big problems A minor delay or documentation error, if handled well, is usually forgivable. But silence? Well that damages trust and confidence. Be proactive - be the person who gets stuff done. Can't resolve it yourself? escalate it to someone who can. Show you are doing everything you can to get it resolved and provide regular feedback. Even if nothing has changed - a call to say you are still on it can put your customer's mind at ease. ❌ No relationship, just transactions If the only contact we get is an invoice, we will start wondering if we are valued at all. Stay in touch - a regular friendly call or email, even just to say "hello, everything going ok?" can help build rapport and give the customer an opportunity to mention any niggles they have for you to resolve. Its sounds like you are generating work but what you are really doing is giving reassurance and building confidence in you and your service. Your customers will appreciate it. Remember: winning new business is important, but retention is where profits are made. Keeping a customer engaged with good communication, reliability and a personal touch is far easier than replacing them. How do you keep your customers loyal? Let me know below 👇 #logistics #logisticsmanagement #freightforwarding #sales #customerservice #supplychain

The Cloud Odyssey team partnered with a leading credit rating organization to streamline dispute resolution using Salesforce Service Cloud and Agentforce. The challenge: Fragmented data, manual dispute handling, and delayed responses were impacting operational efficiency and customer trust. Teams were switching between multiple systems, dispute resolution cycles were extended, and customers lacked timely status updates. The transformation: Agentforce-powered automation on Salesforce delivered a unified, intelligent workflow: • Emails automatically converted into cases • AI-driven validation to identify missing information • Intelligent case routing to the appropriate teams • Context-aware, accurate responses to customer inquiries The impact • 30–40% faster dispute resolution • 30–35% improvement in agent productivity • 20–25% increase in CSAT A scalable, AI-driven approach that significantly improved speed, accuracy, and customer experience. #Salesforce #Agentforce #ServiceCloud #Automation #AI #CustomerExperience #DigitalTransformation #FinTech #OperationalExcellence Anindo Roy Navya Arora Suresh Goli Vara Polina Chaitanya Bollamreddi Pratap Veluri Venkatesh Vishwanathan Srinivas Bheemanapalli Dinesh Mohan Ramakrishnan

"Support isn't about replying to tickets. It's about removing the need for them." I wrote this on a recent post — and the comment section went wild. That one idea resonated with people across roles, industries, and seniority levels. Because it reframes support from reactive to preventative. So here's the system I used at Loom and Airbnb👇 𝟭. 𝗦𝘁𝗼𝗽 𝗰𝗲𝗹𝗲𝗯𝗿𝗮𝘁𝗶𝗻𝗴 𝗳𝗶𝗿𝗲𝗳𝗶𝗴𝗵𝘁𝗶𝗻𝗴 Legacy support tools celebrate "tickets solved" and "response time." They measure the problem, not the solution. 𝟮. 𝗔𝘀𝗸 𝗯𝗲𝘁𝘁𝗲𝗿 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 Ask: "What if those 1,000 people never needed to contact us?" Not: "How can we answer them faster?" 𝟯. 𝗥𝗲𝗱𝗲𝗳𝗶𝗻𝗲 𝘆𝗼𝘂𝗿 𝘃𝗮𝗹𝘂𝗲 Less ticket volume doesn't eliminate support teams. You become irreplaceable, not redundant. 𝟰. 𝗔𝗹𝘄𝗮𝘆𝘀 𝗱𝗼 𝘁𝗵𝗲 𝗺𝗮𝘁𝗵  Answer same question 1,000 times — or fix it once, forever? 90% of teams still choose the wrong one. 𝟱. 𝗦𝗵𝗶𝗳𝘁 𝘆𝗼𝘂𝗿 𝗶𝗱𝗲𝗻𝘁𝗶𝘁𝘆 Stop thinking you're in support. Start thinking you’re in systems design. It's almost 2026. We need to talk about what the future of customer support looks like. For me, it’s not about higher or lower volume. It’s about the type of questions your customers contact you for. The real question is: What could support become if it wasn’t drowning in tickets? A high volume of “how does this work?” tickets means your product isn’t doing its job — and your team is stuck in a reactive loop. Support shouldn’t be about that. It’s about designing experiences so good, people rarely need help — and when they do, it matters.

Here’s the solution Amogh M Aradhya & I built at the Google Agentic AI Hackathon! 👉 What if just clicking a photo could kickstart action on civic issues around your locality? No forms. No apps. No digging for contact details. Just one photo. And done. 🚧 Potholes. 🗑️ Overflowing garbage. 💡 Faulty streetlights. We all see them on a daily basis. But we never even report them because we have normalised having this as a part of culture in India. To challenge this, we built a WhatsApp-based solution that lets any citizen raise a civic issue with a single photo. Here’s how it works 👇 📸 Take a photo of the issue 💬 Send it to our WhatsApp chatbot From there, our AI agent takes over: 🔍 Extracts the latitude & longitude from the image’s EXIF metadata 🧠 Analyzes the issue — determines whether it’s a pothole, garbage dump, broken light, etc., and provides a short auto-generated description 📬 Identifies the nodal officer responsible for that area using open-source public data ✍️ Auto-drafts an email complaint, including details, location, and context, addressed to the right official 👥 Here's the Cherry on the cake. We have also tried sourcing the reporting officer’s boss in CC, ensuring visibility and accountability of the issue. ✅ All the user has to do? Click send. No chasing departments. No wondering if your complaint reached the right person. No friction. We prototyped this in under 30 hours. 💪 Check this out if you're interested in learning more: https://lnkd.in/g7gXeUh8 #GoogleCloud #AgenticAIDay #Hackathon #Product #TGIB #google #whatsapp