Customer Experience

This may be an unpopular opinion but.... the most important characteristics I look for in a leader are vulnerability, empathy, and intuition. Everything else is secondary. Why? ➡️ Hire a leader with empathy because if they can create a culture where your employees are not terrified to fail or make a mistake, that will allow them to be more innovative. At Spanx we had 'oops' meetings where we would go around and talk about a mistake we made that week. Employees (and leadership!) had to stand up and share their biggest screw-ups. It made it to where the fear of embarrassment didn't kill performance. ➡️ Hire a leader who's vulnerable and doesn't feel the need to put on a facade to be taken seriously. When I started Spanx, instead of talking at my customer, I wanted to talk to them. I made myself vulnerable, and I tried to apply that same logic to working with my employees. Vulnerability helps you connect with everyone. Your customers, your employees, even your critics! ➡️ Hire a leader who's in touch with their intuition. Do they know how to listen to their gut? Do they know when to throw out the data and the 'expert opinions'? The Spanx team and I did this in 2019 when picking the famous leather legging as our hero product of the year.... we had no proof that it would create a cult-following but we had a gut feeling and we trusted it. What are your top 3 things you look for in a leader? ⬇️

🗺️ 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, a customer said something that stopped me in my tracks: “Our data is what makes us unique. If we share it with an AI model, it may play against us.” This customer recognizes the transformative power of AI. They understand that their data holds the key to unlocking that potential. But they also see risks alongside the opportunities—and those risks can’t be ignored. The truth is, technology is advancing faster than many businesses feel ready to adopt it. Bridging that gap between innovation and trust will be critical for unlocking AI’s full potential. So, how do we do that? It comes down understanding, acknowledging and addressing the barriers to AI adoption facing SMBs today: 1. Inflated expectations Companies are promised that AI will revolutionize their business. But when they adopt new AI tools, the reality falls short. Many use cases feel novel, not necessary. And that leads to low repeat usage and high skepticism. For scaling companies with limited resources and big ambitions, AI needs to deliver real value – not just hype. 2. Complex setups Many AI solutions are too complex, requiring armies of consultants to build and train custom tools. That might be ok if you’re a large enterprise. But for everyone else it’s a barrier to getting started, let alone driving adoption. SMBs need AI that works out of the box and integrates seamlessly into the flow of work – from the start. 3. Data privacy concerns Remember the quote I shared earlier? SMBs worry their proprietary data could be exposed and even used against them by competitors. Sharing data with AI tools feels too risky (especially tools that rely on third-party platforms). And that’s a barrier to usage. AI adoption starts with trust, and SMBs need absolute confidence that their data is secure – no exceptions. If 2024 was the year when SMBs saw AI’s potential from afar, 2025 will be the year when they unlock that potential for themselves. That starts by tackling barriers to AI adoption with products that provide immediate value, not inflated hype. Products that offer simplicity, not complexity (or consultants!). Products with security that’s rigorous, not risky. That’s what we’re building at HubSpot, and I’m excited to see what scaling companies do with the full potential of AI at their fingertips this year!

This is how Anthropic decides what to build next—and it's brilliant. Instead of endless spec documents and roadmap debates, the Claude Code team has cracked the code on feature prioritization: prototype first, decide later. Here's their process (shared by Catherine Wu, Product Lead at Anthropic): Step 1: Idea → Prototype Got a feature idea? Skip the spec. Build a working prototype using Claude Code instead. Step 2: Internal Launch Ship that prototype to all Anthropic engineers immediately. No polish required—just functionality. Step 3: Watch & Listen Track usage religiously. Collect feedback actively. Let real behavior, not opinions, guide decisions. Step 4: Data-Driven Prioritization - High usage + positive feedback → roadmap priority - Low engagement or complaints → back to iteration This "prototype-first product shaping" flips traditional product development on its head. Instead of guessing what users want, they're measuring what users actually use. The beauty? They're dogfooding their own tool to build their own tool. The feedback loop is immediate, honest, and impossible to ignore. The takeaway: Your best product decisions come from real user behavior, not theoretical frameworks. Sometimes the fastest way to validate an idea isn't a survey or interview—it's a working prototype.

I once lived at distributor’s home in a small town because I had no choice... When Marico Limited was nascent, Bombay Oil Industries was still the family’s backbone. In those early days, I wanted our business to transform from a commodity trade into a branded consumer company. To do that, I had to understand the ground truth. There were no fancy hotels in the towns we visited. I stayed in dusty and small guest rooms. I sat with distributors over chai and samosas. I watched how coconut oil was stored, how shopkeepers priced it, how packaging changed hands. One day, a retailer told me matter-of-factly: “You always sell big tins. When people come back to buy, they carry a few kilos. If your packet is small, they will pick your brand at convenience.” That simple insight was a turning point. It nudged us to expand SKU ranges, introduce smaller packs, and think about how to become a “grab-and-go” brand, rather than just a bulk commodity supplier. If you ask me where innovation begins, it begins in the least glamorous places. In the musty shelves of neighbourhood stores, in conversations that feel insignificant, in paying attention to what people don’t say aloud. Takeaway for entrepreneurs: Your real research lab isn’t spreadsheets or agencies. It’s the ground. If you go build empathy for your customer at the shelf level, the brand strategy almost builds itself. #entrepreneurship #business #resilience #mindset #growth

Cold digital interactions will destroy your D2C brand. Your beauty product is at risk of failing if you don’t address this. Industry is rooted in enhancing self-image and boosting confidence, goals that are inherently emotional. While online shopping is undeniably convenient, it often comes at the expense of personal interaction. This is especially problematic in the beauty sector, where purchasing decisions are often influenced by sensory experiences, personalized recommendations, and emotional connections. +64% consumers believe brands are losing touch with customer experience. +85% higher sales achieved by brands that emotionally engage. +68% women & 56% men choose beauty products based on how they make them feel. >>Online emotional challenges << →Lack of personalization in online transactions. E-commerce lacks the personal engagement of in-store shopping, such as trying products and consulting with beauty experts. →Absence of sensory experiences. Customers are unable to explore key sensory elements like texture, scent, and application when shopping online. →Overwhelming variety. The sheer number of options online can confuse customers and lead to decision fatigue without proper guidance. >>Strategies to build emotional connections<< →Transform brick and mortar stores into immersive experiences. Redefine your physical stores as experiential hubs where customers can enjoy personalized consultations, interactive product trials, and even beauty treatments. +30% boost in sales is seen in flagship stores that offer immersive experiences. →Retail as entertainment, retailtainment. Host creative pop-up shops, in-store events, and experiential retail activations to engage customers emotionally with unique deco, exclusive product offerings, and hands-on activities. +70% of beauty consumers value in-store experiences over online alternatives. →Leverage influencer trust. Partner with influencers who bring authenticity to your brand by sharing personal stories, reviews, and tutorials. Their relatability and trustworthiness create stronger emotional ties with consumers. +49% customers rely on influencer recommendations for beauty product purchases. →Build community through social media. Use social media to foster continuous engagement through live Q&A sessions, interactive content, user-generated campaigns, and community forums. +72% of beauty consumers discover products through social media. To finish. Despite the challenges of the digital era, the industry is finding ways to close the emotional gap with creative solutions like flagship experiences, influencer collaborations, virtual consultations, and community-driven marketing. Check out my curated collection of visuals to spark your next big idea. Featured brands: Benefit Glossier Kylie Cosmetics Marc Jacobs Molecula Miu Miu Nina Ricci Laneige Rhode #BeautyBusiness #EmotionalConnection #SocialBeauty #ExperientialRetail #InfluencerMarketing

AI handled 75% of customer chats at Klarna… and they still brought humans back. Why? Because speed isn’t the same as quality! Because customers noticed the difference. And it wasn’t good. Speed? Great. Empathy? Missing. Trust? Slipping. After a year of leaning heavily on AI, they’re rehiring human support agents. Real people. Not because AI failed—but because it wasn’t enough. AI can answer your question. But only a human can make you feel heard. Klarna is now hiring in rural areas and among student communities—betting on empathy, not just efficiency. This should be a wake-up call. You can automate tasks. But relationships? They still need people! This is why the future isn’t human vs AI. It’s human with AI. And the companies who get that balance right? They’ll win customer loyalty, and talent, faster than any chatbot ever could.

Trust at scale has always been the hardest thing to build in business. Word of mouth was the original mechanism. One person tells another, credibility transfers, trust builds slowly. It worked, but it was a limited mechanism you couldn't control. What's changed today is the infrastructure. Reach, repeated visibility to a large audience, is now one of the most powerful trust-building tools available to any founder or business. I am not saying being seen is the same as being trusted, but trust requires repeated exposure before it forms. The people and businesses that maintain high engagement at scale on their social media are the ones that showed up repeatedly, with a clear point of view, long before the numbers got impressive. Trust is a perception built over time through repeated signals: what you say, what you stand for, what you consistently show up for. Reach accelerates that process. Every post is another data point for your audience to evaluate whether your judgment is worth following. Enough of those data points, delivered consistently, and reach becomes evidence that you are someone worth trusting. The people and businesses who understand this aren't just building audiences. They're building credibility that makes everything else, fundraising, hiring, selling, structurally easier. #rajshamani #figuringout

RAG stands for Retrieval-Augmented Generation. It’s a technique that combines the power of LLMs with real-time access to external information sources. Instead of relying solely on what an AI model learned during training (which can quickly become outdated), RAG enables the model to retrieve relevant data from external databases, documents, or APIs—and then use that information to generate more accurate, context-aware responses. How does RAG work? 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗲: The system searches for the most relevant documents or data based on your query, using advanced search methods like semantic or vector search. 𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: Instead of just using the original question, RAG 𝗮𝘂𝗴𝗺𝗲𝗻𝘁𝘀 (enriches) the prompt by adding the retrieved information directly into the input for the AI model. This means the model doesn’t just rely on what it “remembers” from training—it now sees your question 𝘱𝘭𝘶𝘴 the latest, domain-specific context 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲: The LLM takes the retrieved information and crafts a well-informed, natural language response. 𝗪𝗵𝘆 𝗱𝗼𝗲𝘀 𝗥𝗔𝗚 𝗺𝗮𝘁𝘁𝗲𝗿? Improves accuracy: By referencing up-to-date or proprietary data, RAG reduces outdated or incorrect answers. Context-aware: Responses are tailored using the latest information, not just what the model “remembers.” Reduces hallucinations: RAG helps prevent AI from making up facts by grounding answers in real sources. Example: Imagine asking an AI assistant, “What are the latest trends in renewable energy?” A traditional LLM might give you a general answer based on old data. With RAG, the model first searches for the most recent articles and reports, then synthesizes a response grounded in that up-to-date information. Illustration by Deepak Bhardwaj

My biggest takeaways from Jason Cohen: 1. “Too expensive” is never the real reason customers cancel. They already saw your pricing and decided to buy, so something else changed. When customers cite price, dig deeper—the actual reason might be changing needs, integration issues, or feature gaps. 2. Ask “What made you cancel?” instead of “Why did you cancel?” Jason tested both phrasings and saw response quality double with the “what made you” version. The first version directs attention to the product or situation and invites one-word deflections like “budget.” 3. Most companies undercharge because they just guessed at pricing and never revisited it. One founder selling to enterprise charged $300 per year, and Jason advised switching to $300 per month. Signups stayed exactly the same. When you 12x your price and conversion doesn’t budge, you’re not even close to finding the right number yet. 4. Pricing selects your market more than it signals value. When your product costs too little, larger companies assume it can’t be serious: not mature enough, no governance policies, inadequate support. Raise prices and you don’t necessarily lose customers; you enter a different market segment where your price signals credibility. The founder who went from $300 per year to $300 per month and saw no change in signups—he just shifted who was buying. 5. Your churn rate sets a ceiling on your business that most founders underestimate. The math is simple: divide your monthly new customers by your monthly cancellation rate, and that’s the maximum number of customers you will ever have. This is why logo churn is the first metric to examine when growth stalls. 6. Onboarding is the highest-leverage lever to reduce churn. Small improvements in the first 30 days compound into retention gains over the customer lifetime. When you don’t know where to start on retention, start with onboarding. 7. Positioning can allow you to charge an order of magnitude more without changing your product. The same exact product can command higher prices depending on how you frame it. “Cut your ad costs in half” caps what customers will pay—they’ll only give you a fraction of the savings you drive them. While “double your leads” aligns with what executives actually want and opens a much higher budget. CEOs reward growth; they merely acknowledge cost savings. 8. Sometimes the right answer is accepting that not growing is OK. If you’ve optimized churn, pricing, NRR, and channels, maybe growth has natural limits. Bootstrap founders reach a point where healthy annual dividends make further scaling optional. The question “Do you need to grow?” deserves honest examination—not because stasis is fine but because growth at all costs can destroy what made the company good.