Mapping Out Customer Touchpoints

🗺️ AirBnB Customer Journey Blueprint, a wonderful practical example of how to visualize the entire customer experience for 2 personas, across 8 touch points, with user policies, UI screens and all interactions with the customer service — all on one single page. AirBnB Customer Journey (Google Drive): https://lnkd.in/eKsTjrp4 Spotify Customer Journey (High-res): https://lnkd.in/eX3NBWbJ Now, unlike AirBnB, your product might not need a mapping against user policies. However, it might need other lanes that would be more relevant for your team. E.g. include relevant findings and recommendations from UX research. List key actions needed for next stage. Add relevant UX metrics and unsuccessful touchpoints. That last bit is often missing. Yet customer journeys are often non-linear, with unpredictable entry points, and integrations way beyond the final stage of a customer journey map. It’s in those moments when things leave a perfect path that a product’s UX is actually stress tested. So consider mapping unsuccessful touchpoints as well — failures, error messages, conflicts, incompatibilities, warnings, connectivity issues, eventual lock-outs and frequent log-outs, authentication issues, outages and urgent support inquiries. Even further than that: each team could be able to zoom into specific touch points and attach links to quotes, photos, videos, prototypes, design system docs and Figma files. Perhaps even highlight the desired future state. Technical challenges and pain points. Those unsuccessful states. Now, that would be a remarkable reference to use in the beginning of every design sprint. Such mappings are often overlooked, but they can be very impactful. Not only is it a very tangible way to visualize UX, but it’s also easy to understand, remember and relate to daily — potentially for all teams in the entire organization. And that's something only few artefacts can do. Useful resources: Free Template: Customer Journey Mapping, by Taras Bakusevych https://lnkd.in/e-emkh5A Free Template: End-To-End User Experience Map (Figma), by Justin Tan https://lnkd.in/eir9jg7J Customer Journey Map Template (Figma), by Ed Biden https://lnkd.in/evaUP4kz Free Figma/Miro User Journey Maps Templates https://lnkd.in/etSB7VqB User Journey Maps vs. Service Blueprints (+ Templates) https://lnkd.in/e-JSYtwW UX Mapping Methods (+ Miro/Figma Templates) https://lnkd.in/en3Vje4t #ux #design

Last week, I shared how Gen AI is moving us from the age of information to the age of intelligence. Technology is changing rapidly and the way customers shop and buy is changing, too. We need to understand how the customer journey is evolving in order to drive customer connection today. That is our bread and butter at HubSpot - we’re deeply curious about customer behavior! So I want to share one important shift we’re seeing and what go-to-market teams can do to adapt. Traditionally, when a customer wants to learn more about your product or service, what have they done? They go to your website and explore. They click on different pages, filter for information that’s relevant to them, and sort through pages to find what they need. But today, even if your website is user-friendly and beautiful, all that clicking is becoming too much work. We now live in the era of ChatGPT, where customers can find exactly what they need without ever having to leave a simple chat box. Plus, they can use natural language to easily have a conversation. It's no surprise that 55% of businesses predict that by 2024, most people will turn to chatbots over search engines for answers (HubSpot Research). That’s why now, when customers land on your website, they don’t want to click, filter, and sort. They want to have an easy, 1:1, helpful conversation. That means as customers consider new products they are moving from clicks to conversations. So, what should you do? It's time to embrace bots. To get started, experiment with a marketing bot for your website. Train your bot on all of your website content and whitepapers so it can quickly answer questions about products, pricing, and case studies—specific to your customer's needs. At HubSpot, we introduced a Gen AI-powered chatbot to our website earlier this year and the results have been promising: 78% of chatters' questions have been fully answered by our bot, and these customers have higher satisfaction scores. Once you have your marketing bot in place, consider adding a support bot. The goal is to answer repetitive questions and connect customers with knowledge base content automatically. A bot will not only free up your support reps to focus on more complex problems, but it will delight your customers to get fast, personalized help. In the age of AI, customers don’t want to convert on your website, they want to converse with you. How has your GTM team experimented with chatbots? What are you learning? #ConversationalAI #HubSpot #HubSpotAI

🚨Customer Success needs to retire the phrase “Just checking in” 🚨✨ If your outreach doesn’t add value, it adds noise 😬📭 Customers don’t need more pings. They need insights, outcomes, and momentum 💥📈 So how do we move from “checking in” to showing up with purpose? 👇👇👇 ✅ Lead with a point of view. Share an observation, a trend, or a pattern you’re seeing across accounts 🔍💡 ✅ Anchor every interaction to a goal. Tie your message to their KPIs, roadmap, or priorities 🎯🧭 ✅ Bring receipts. Usage data, benchmarks, ROI snapshots, quick wins, show, don’t tell 📊📈 ✅ Teach something small. A feature they’re underusing, a shortcut, or a best practice they can apply today 🧠⚡ ✅ Be proactive, not reactive. Don’t wait for a problem to appear, surface risks before they feel them 🚦🔮 ✅ Make every meeting earn its spot. If there’s no agenda or takeaway, it shouldn’t be a meeting 🙅♀️🗓️ The new CS mindset: 👉 Every touchpoint should answer “What’s in it for the customer?” 🤝✨ Because great Customer Success isn’t about staying in touch…It’s about driving progress 🚀🔥

Imagine you're the CFO of a global company and someone pitches you a recruitment automation solution that will do the work of 400 recruiters and save you $30M per year. What would you do? When I was at LinkedIn's Talent Connect in October, I attended a workshop with John Vlastelica in which he shared that a global company had decided to implement a recruiting automation solution that would allow them to save $30M in costs by eliminating 400 recruiter positions. They also reduced the time to hire from 11 days down to 3. He shared that another company had used recruitment automation software to hire 300,000 workers with minimal human involvement - people only came into the process after background checks had been performed. They also maintained candidate quality and candidate experience while increasing the speed of hire. These kinds of case studies should not surprise anyone, although it is sobering to anyone in talent acquisition - the rapid advancement of AI and automation in recruiting is both exciting and concerning. On the one hand, the potential for efficiency gains, cost savings, and improved candidate experience is huge and undeniable, as these examples demonstrate. On the other hand, we must also be mindful of the human impact - thousands of recruiters are seeing their roles transformed or eliminated. As talent acquisition professionals, it's important to be thinking about how to adapt and provide value in this changing landscape. Some key questions to consider: -How can we upskill and position ourselves to work alongside AI rather than be replaced by it? -What are the uniquely human elements of recruiting that AI can't replicate, and how do we double down on those? -How might our roles evolve to focus more on passive talent sourcing, talent intelligence/advisory, strategic workforce planning, employer branding, candidate engagement, and employee experience? For companies considering or implementing recruitment automation, I believe it should be a thoughtful, strategic decision - not just a blind cost-cutting measure. Here are some key considerations: -What is the optimal mix of human and automated touchpoints to balance efficiency and candidate experience? -How will the balance of AI and human involvement vary based on the labor market dynamics for each role? Roles with talent scarcity may require more human touch to attract and engage candidates, while high-volume roles with ample supply lend themselves to greater automation. -How will we redeploy or reskill displaced recruiters? -How do we maintain our employer brand and human touch with increased automation? The future of recruiting is undoubtedly both human and machine - but the mix is up to each company and may vary by role/department. I'm curious to hear your thoughts - have you been impacted by AI/automation? How are you and/or your company preparing for the intersection of AI/automation and recruiting? #AI #Recruiting #FutureOfWork

I spent the week trying to answer the question: How can I build a property management company with zero human employees? After studying every AI tool in multifamily, I found something surprising. Here's what would happen if machines ran your apartment building: A few months ago, I designed a hypothetical zero-employee development firm. Now, I'm tackling property management. I can't stop thinking about how close we are to this reality. From leasing to maintenance, there's now an AI tool for almost every step. So I designed a hypothetical property management company with zero employees: Asimov Management. The goal: a full-service multifamily property manager that happens to have no full-time staff. For this to work, we'll use AI and automation to cover: • Marketing and leasing • Pricing optimization • Virtual and self-guided tours • Tenant screening and onboarding • Customer service • Maintenance coordination • Renewals and reporting While the tech isn't 100% there yet, here's what I learned: What's already possible: → AI-powered leasing assistants handle most prospective tenant questions → Self-guided tours work through automated access control systems → Maintenance requests can be routed to third-party gig workers → Renewal offers can be automatically generated and negotiated Where we're stuck: → Physical maintenance still requires humans (robots can't fix toilets...yet) → Many residents still prefer talking to a human at a front desk → Preventative maintenance relies on technicians' intuition → Larger buildings (250+ units) struggle with full automation The reality: • The most valuable application isn't replacing property managers • It's giving them superpowers to handle more properties with less effort Here's what this means for property management: • Class definitions may shift as service expectations change • Tasks will be centralized rather than eliminated • Resident preferences may actually evolve to favor AI interactions • The best operators will blend automation with strategic human touchpoints From my experience founding Common in 2015, I learned something critical: The approaches that worked well at 50-unit properties often broke at 250 units. Technology can centralize most functions. But, some residents always prefer walking to the front desk rather than using an app. This could change as AI improves. Meaning residents may prefer the predictability of AI over unpredictable humans. We're already seeing this in ride-sharing, where Waymo beats Uber and Lyft in user retention. So how close are we to machines running property management? Perhaps far closer than we expect. What parts of property management do you think AI will transform first? Full letter on how I designed Asimov Management is linked in the comments.

WANT CUSTOMER DELIGHT? GO THE EXTRA INCH, NOT THE EXTRA MILE In a world where companies strive to “go the extra mile” for their customers, I propose a counterintuitive thought: You don’t need to go a mile. You just need to go an inch. The smallest, low-cost gestures can have a massive impact on customers, turning ordinary transactions into memorable experiences. The secret - search for the asymmetry between cost and impact. Going the extra inch requires minimal effort and often costs next to nothing. It could be a handwritten note, a smile, a gesture of personal recognition, a small act of kindness. But the effect on customers is profound. It creates emotional connections, fosters loyalty, and makes customers into advocates. The irony - while everyone is busy trying to “go the extra mile,” it is the extra inch that nets you miles of customer loyalty. THE I.N.C.H. FRAMEWORK To master the art of the extra inch, use this simple yet powerful framework: I – Identify Moments of Truth: Look for touchpoints where expectations are neutral or low. These are prime opportunities to surprise and delight. For instance, when I got my car serviced at the Lexus dealership, they washed and vacuumed the car and left a red carnation flower on the dash. I have told more than 10,000 people about the 50-cent carnation. How’s that for ROI? N – Notice the Little Things: Train employees to observe and remember small details about customers—preferences, moods, or special occasions. At the Oberoi Hotel in Mumbai, I asked for a memory foam pillow. Every time I stay there, they put a memory foam pillow on my bed. C – Customize the Experience: Personalize the interaction or gesture. Even the smallest customization can create a huge emotional impact. At Chewy, when a customer returned dog food after their pet passed away, they received a condolence card and flowers. It wasn’t about making a sale; it was about showing empathy. H – Humanize the Interaction: Move beyond scripted conversations. Authenticity and empathy resonate more than robotic efficiency. At Café Lucci, our favorite Italian restaurant in Chicago, the valet, the server, and the owner Bobby - all know us, know our kids, and always ask about the family. We are customers for life! In the race to “go the extra mile,” it’s easy to overlook the power of the extra inch. The secret to exceptional customer service isn’t grand gestures or expensive perks—it’s the tiny, thoughtful actions that leave a lasting impression. Going the extra inch is about mastering the art of the unexpected. It’s about creating emotional connections through small acts of kindness and thoughtfulness. So, the next time you think about how to delight a customer, remember: You don’t have to go the extra mile. Just go the extra inch. You will get miles of loyalty. #Marketing #CustomerExperience #Loyalty #Advocacy

Most AI implementations can be technically flawless—but fundamentally broken. Here's why: Consider this scenario: A company implemented a fully automated AI customer service system, and reduced ticket solution time by 40%. What happens to the satisfaction scores? If they drop by 35%, is the reduction in response times worth celebrating? This exemplifies the trap many leaders fall into - optimizing for efficiency while forgetting that business, at its core, is fundamentally human. Customers don't always just want fast answers; they want to feel heard and understood. The jar metaphor I often use with leadership teams: Ever tried opening a jar with the lid screwed on too tight? No matter how hard you twist, it won't budge. That's exactly what happens when businesses pour resources into technology but forget about the people who need to use it. The real key to progress isn't choosing between technology OR humanity. It's creating systems where both work together, responsibly. So, here are 3 practical steps for leaders and businesses: 1. Keep customer interactions personal: Automation is great, but ensure people can reach humans when it matters. 2. Let technology do the heavy lifting: AI should handle repetitive tasks so your team can focus on strategy, complex problems, and relationships. 3. Lead with heart, not just data (and I’m a data person saying this 🤣) Technology streamlines processes, but can't build trust or inspire people. So, your action step this week: Identify one process where technology and human judgment intersect. Ask yourself: - Is it clear where AI assistance ends and human decision-making begins? - Do your knowledge workers feel empowered or threatened by technology? - Is there clear human accountability for final decisions? The magic happens at the intersection. Because a strong culture and genuine human connection will always be the foundation of a great organization. What's your experience balancing tech and humanity in your organization?

Every company says they listen to customers. But most just hear them. There's a difference. After spending years building feedback loops, here's what I've learned: Feedback isn't about collecting data. It's about creating change. Most companies fail at feedback because: - They send random surveys - They collect scattered feedback - They store insights in silos - They never close the loop The result? Frustrated customers. Missed opportunities. Lost revenue. Here's how to build real feedback loops: 1. Gather feedback intelligently - NPS isn't enough - CSAT tells half the story - One channel never works Instead: - Run targeted post-interaction surveys - Conduct deep-dive customer interviews - Analyze product usage patterns - Monitor support conversations - Build customer advisory boards - Track social mentions 2. Create a single source of truth - Consolidate feedback from everywhere - Tag and categorize insights - Track trends over time - Make it accessible to everyone 3. Turn feedback into action - Prioritize based on impact - Align with business goals - Create clear ownership - Set implementation timelines But here's the most important part: Close the loop. When customers give feedback: - Acknowledge it immediately - Update them on progress - Show them implemented changes - Demonstrate their impact The biggest mistakes I see: Feedback Overload: - Collecting too much data - No clear action plan - Analysis paralysis Biased Collection: - Listening to the loudest voices - Ignoring silent majority - Over-indexing on complaints Slow Response: - Taking months to act - No progress updates - Lost customer trust Remember: Good feedback loops aren't about tools. They're about trust. Every piece of feedback is a customer saying: "I care enough to help you improve." Don't waste that trust. The best companies don't just collect feedback. They turn it into visible change. They show customers their voice matters. They build trust through action. Start small: 1. Pick one feedback channel 2. Create a clear process 3. Act quickly on insights 4. Show results 5. Scale what works Your customers are talking. Are you really listening? More importantly, are you acting? What's your approach to customer feedback? How do you close the loop? ------------------ ▶️ Want to see more content like this and also connect with other CS & SaaS enthusiasts? You should join Tidbits. We do short round-ups a few times a week to help you learn what it takes to be a top-notch customer success professional. Join 1999+ community members! 💥 [link in the comments section]

In an AI-first customer journey, shoppers start in ChatGPT—and, with the new Instant Checkout and the Agentic Commerce Protocol (ACP), they don’t have to leave. This is Agentic Customer Experience (ACX): chat → consider → buy. What moves first: • Near term: “considered” specialty purchases shift to AI chat commerce—think bikes, strollers, mixers—where an agent can shortlist, explain trade-offs, and convert. • Longer term: commodity buys flip from search-led (Google/Amazon) to agent-led replenishment. Your assistant will keep you stocked and price-optimized. What doesn’t change (for specialty purchases): • Social discovery still sparks demand. • Brand still matters and earns trust and premium. What does change: • The front door to commerce becomes chat. • Storefronts become APIs. • The funnel compresses: intent, evaluation, and checkout collapse into one conversation. Implications for incumbents: Platforms around commerce, content management, personalization, analytics, and ads (Adobe, Salesforce, and more) will be re-architected for ACX. The surface area for differentiation shifts from page design to data, agents, and outcomes. Opportunities for founders: • Agent-native merchandising & attribution. • ACP connectors/adapters for major platforms; merchant tooling for offers, returns, identity, and fraud. • Product knowledge graphs & RAG for complex catalogs. • Compliance, safety, and brand controls for autonomous purchases. • Journey analytics for agentic flows (from prompt to purchase). ACX won’t kill commerce—but it will reroute the path to purchase for many brands.

Your Customers Are Lying to You. Not because they are malicious or deceitful, but because they are human. Listening to your customers isn't enough. You need to observe them. This is the core reason why many big research projects by deep-pocketed companies fail. They are only listening to their consumers. What Should You Do Instead? -> Watch Consumers' Behavior: Dive into analytics, conduct usability tests, and observe their interactions with your product in real-time. This is where the gold lies. -> Actions Over Words: Pay attention to what your customers do, not just what they say. Behavior doesn’t lie. In my experience, simply listening to consumers talk about why chili powder wasn't working for them versus understanding their actual usage in the kitchen did wonders for us. For any business to take their consumer understanding to the next level, stop listening and start watching. Agree or disagree? Share your thoughts and experiences in the comments! How has observing your customers changed your approach? #CustomerExperience #Innovation #BusinessStrategy #ProductDevelopment #CustomerInsight #brand