Mapping Out Customer Touchpoints

🚨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 🚀🔥

Every time technology takes a big step forward, the same question comes up: What does this mean for people? During the Industrial Revolution, as machines took over manual tasks, they didn’t make people obsolete—they created new roles that allowed us to work in ways not possible. The arrival of computers and data processing didn’t just replace office tasks; it freed us up to tackle higher-level work, pushing us to new heights. Now, AI is doing the same. It’s not here to replace our strengths but to amplify them. For teams in marketing, sales, and customer service, AI provides powerful tools that make our jobs easier, faster, and more impactful, giving us more time to focus on what truly matters. In Marketing, AI creates, and people curate. AI can quickly draft content, but it’s people who polish it into something that truly connects with an audience. AI can provide a starting point, but it’s the human touch that makes it shine. In Sales, AI offers context, and people offer connection. AI can save time by preparing data and insights, allowing salespeople to spend more time with customers. While AI lays the groundwork, it’s the sales rep who builds trust and connection. In Customer Service, AI handles simplicity, and people handle subtlety. Chatbots can answer basic questions, giving human reps the chance to focus on complex issues that need empathy and a personal touch. AI isn’t here to take over; it’s here to power us. By handling tasks that can save us time, it frees us up to do what we do best—connect, create, and make a difference.

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.

🔎 How To Redesign Complex Navigation: How We Restructured Intercom’s IA (https://lnkd.in/ezbHUYyU), a practical case study on how the Intercom team fixed the maze of features, settings, workflows and navigation labels. Neatly put together by Pranava Tandra. 🚫 Customers can’t use features they can’t discover. ✅ Simplifying is about bringing order to complexity. ✅ First, map out the flow of customers and their needs. ✅ Study how people navigate and where they get stuck. ✅ Spot recurring friction points that resonate across tasks. 🚫 Don’t group features based on how they are built. ✅ Group features based on how users think and work. ✅ Bring similar things together (e.g. Help, Knowledge). ✅ Establish dedicated hubs for key parts of the product. ✅ Relocate low-priority features to workflows/settings. 🤔 People don’t use products in predictable ways. 🤔 Users often struggle with cryptic icons and labels. ✅ Show labels in a collapsible nav drawer, not on hover. ✅ Use content testing to track if users understand icons. ✅ Allow users to pin/unpin items in their navigation drawer. One of the helpful ways to prioritize sections in navigation is by layering customer journeys on top of each other to identify most frequent areas of use. The busy “hubs” of user interactions typically require faster and easier access across the product. Instead of using AI or designer’s mental model to reorganize navigation, invite users and run a card sorting session with them. People are usually not very good at naming things, but very good at grouping and organizing them. And once you have a new navigation, test and refine it with tree testing. As Pranava writes, real people don’t use products in perfectly predictable ways. They come in with an infinite variety of needs, assumptions, and goals. Our job is to address friction points for their realities — by reducing confusion and maximizing clarity. Good IA work and UX research can do just that. [Useful resources in the comments ↓] #ux #IA

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]

So you’re a digital brand, what’s your physical touch point? Oh… you don’t have one? Listen to this (you might want to make a coffee first)👇🏼 Last year Snap Inc. launched Snapchat+ membership gift cards via Amazon. They saw memberships rise from 5 million in September to 7 million by end of December. That’s a 40% subscription increase in one quarter. I think all of our finance teams would agree that’s the greatest Christmas present of all. So this year Snapchat are doubling down. They’ve just introduced physical gift cards in retail stores marking a strategic move to blend digital experiences with tangible interactions. In an age where 82% of consumers say they feel more connected to brands that offer in-person experiences, digital brands are realising that physical touchpoints not only reinforce loyalty but can also bring a whole new depth to their offerings. Here’s why this approach matters—and how some of the most innovative digital brands are pulling it off ⬇️ 1️⃣ Meeting Customers Where They Are – IRL Digital-first brands are finding that physical experiences resonate in powerful ways. Look at Runna - a running training app that brought its brand to life with a pop-up at the New York Marathont this weekend, offering runners real-world support, community, and connection. These brands turn online experiences into memorable in-person touchpoints, meeting users in the moments where they’ll connect best. Smart! 2️⃣ Tangibility Boosts Brand Loyalty There’s something about holding a product that brings a brand closer to home. Bumble Inc. the networking and dating app, understood this when they launched Bumble Hives—real-life lounges where users could attend dating workshops and networking events. These moments make the app experience feel more personal, building stronger loyalty. 3️⃣ Targeting the Gift-Givers - NOT the receivers While Gen Z is immersed in digital ecosystems, physical products like Snapchat gift cards are designed for their parents and grandparents. These tangible items offer a straightforward way for older generations to gift experiences that align with Gen Z’s digital lifestyles, effectively bridging the generational gap. This is what makes this super smart. 4️⃣ Why It Matters Now – People Want Real-World Experiences Consumers are increasingly seeking real-life interactions with their favorite brands, especially digital-first brands, as 78% of people now say they want brands to connect with them in more experiential ways. Physical experiences, whether pop-ups, branded parties, or beautifully crafted stores, offer a chance for digital brands to deepen relationships, bring their values to life, and connect with audiences in memorable, tangible ways. — As marketers, it’s essential to recognise the value of this intersection - but only when it’s smart, not just for the sake of it. What are some of your favourite examples of digital meets physical? Who’s doing this REALLY well? 👇🏼👇🏼👇🏼

Most people have the wrong idea about sales. The pushy SDR. The smooth-talking closer. The reality: good sales is simply the art of removing friction. Here's what sales actually looks like: Early Airbnb hosts hesitated to list their homes. The stated problem was "no bookings," but the hidden objection was trust. Brian Chesky (CEO) went door-to-door in New York in 2009 and watched where confidence fell apart - poor photos and thin profiles. He didn't add more explainers about trust and safety. He removed the psychological barrier. Pro photography. Identity verification. Conversion lifted. Sales wasn't persuasion. It was friction removal. Founders do the opposite because they're uncertain. So they overexplain and try to overqualify every lead. They add more copy, more form fields, more steps. Each one asks users to trust you before they have proof. Here's where that shows up: Landing pages: You wrote three paragraphs explaining your product. Healthy landing page conversion (visitor to signup) is 3-6% (OpenView). Below 2%? Your message isn't landing. Cut it to one line: "For [who], we [outcome]." Signup forms: You ask for company name, role, team size. Each extra field causes 10-40% drop-off. Start with email and password. Get them to value first. Pricing pages: You buried pricing three clicks deep. If users work to find your price, you lost them. Make it visible. "Cancel anytime.” Things you can try this week: 1. Watch 3 users try your product. Track where they stop: landing, signup, first action, first value. That's your barrier. 2. Remove the biggest friction point(s). Low landing conversion? Test if a stranger can explain what you do in 5 seconds. Low activation? Cut steps between signup and first value. 3. Measure. A 10% lift on 2% landing conversion means 2.2%. On 10K monthly visitors, that's 20 more signups. Good sales is listening for where users stop and removing what's stopping them. Build the product and remove everything between them and proof.