Improving Customer Experience

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.

The digital bank is an outdated concept. Fast being replaced by the intelligent bank. The only question is how soon banks can manage the transition. Let’s take a look. I have broken down the main elements that make up the transition to the intelligent bank: 1. From transactional to predictive banking: digital banking enabled 24/7 self-service, but intelligent banking takes it further by predicting customer needs. AI-driven models analyse real-time data to offer personalised financial insights, proactive credit offerings, and automated investment recommendations. 2. AI-powered risk & fraud management: traditional risk assessment relied heavily on historical data. Intelligent banks use AI and machine learning to detect fraud in real time, identify suspicious patterns and prevent threats before they occur. 3. Hyper-personalisation: instead of generic offers, intelligent banks use AI to tailor financial products to individual customers (mass personalisation). 4. Seamless omni-channel experience: customers no longer interact with banks through a single channel. Intelligent banking ensures that a user can start a transaction on a mobile app, continue it via a chatbot, and complete it with a human advisor. All while maintaining a seamless, connected experience. 5. Autonomous banking operations: intelligent banks optimise back-office processes using cloud and AI automation, reducing human errors and significantly improving efficiency. Functions such as loan approvals, compliance checks, and reconciliation are increasingly self-regulated by AI-driven workflows.   Banks are in a time race. They not only need to move from digital to intelligent but also do it fast.   In doing so technology is the biggest dependency. One of the most interesting approaches I have seen on how to best support banks in this transition is Huawei's 4-Zero model, which is based on 4 main pillars:   1. Zero Downtime → Instant Readiness AI-powered predictive maintenance and cloud resilience ensure 24/7 availability, allowing banks to deploy and scale AI solutions without service disruptions. 2. Zero Wait → Faster Customer Experiences AI-driven real-time processing eliminates delays in transactions, approvals, and customer interactions, making banking services ultra-responsive. 3. Zero Touch → Reduced Operational Burden End-to-end automation using AI and machine learning removes manual intervention in processes like KYC, loan approvals, and compliance, freeing up resources for AI innovation. 4. Zero Trust → Seamless AI Integration AI-driven security frameworks continuously validate access, ensuring trust and compliance while enabling banks to integrate AI-powered services without increasing risk. The era of intelligent banking isn’t a distant future - it’s happening now. Banks will not be able to transform in months but getting a head start can make a difference. Opinions and graphics: Panagiotis Kriaris  #HuaweiMWC  #RAAS  #IntelligentFinance

From the department-of-mythbusting: our Just Walk Out technology is not going anywhere but to even more locations worldwide. Let's walk through what's really going on here... If you want to optimize any experience, a great place to start is with the biggest, most egregious, inefficient part of that experience. For physical shopping - you don't have to look much further than waiting in line for a checkout. It's boring, and it's a waste of time for both the shopper, and the store. So when we started to look at how to improve physical shopping - we started with the question: how do we take out the line? This is a hard problem - but it led to inventions like Just Walk Out (an AI and sensor fusion system for checkout-free shopping), Amazon Dash Cart (where you scan items as you place them into your cart), and Amazon One (our palm-based payments and identity). These technologies are complementary, and serve a very different purpose depending on these store and shopping task: 🚶 Just Walk Out is great for really quick, "mission driven" shopping - like small-format convenience stores for snacks, drinks, and so on. You know what you want, and you don't want a lot. Enter. Grab. Just walk out. Even with relatively few items sold per visit, we have already sold over 18 million items in Just Walk Out stores, and there are now more than 140 third-party locations with Just Walk Out technology in the U.S., UK, Australia, and Canada. The response from shoppers to Just Walk Out in small-format stores has been so strong that we will launch more small-format third-party Just Walk Out stores in 2024 than any year prior, more than doubling the number of third-party stores with the technology this year. 🛒 In larger grocery stores, where customers are making a big weekly trip and buy a greater number of items, customers so far prefer Amazon Dash Cart. Dash Cart serves as a shopping companion that travels through the store with a customer, helping them locate items with an on-cart screen featuring maps and navigation, and receive personalized shopping experiences, all while tracking their savings and spending in real time. ✋ Regardless of the size or format of the store, shoppers tell us they like the security and convenience of Amazon One. Amazon One is in 500+ Whole Foods stores, other Amazon stores, and 150 third-party locations like stadiums, airports, fitness centers, and more. Just Walk Out, Dash Cart, and Amazon One - together - let us remove these pesky lines in more places than we could in isolation. They are complements to one another - like The Beatles. Stronger than the sum of their parts. So don't believe the headlines. Just Walk Out isn't going anywhere, except into more locations, in more countries, to help more shoppers, and more businesses. Now back to your regular scheduled programming... :)

I think a very visible observation at this year's Restaurant Show was logical tech instead of theoretical. There was less "glimpses into the future" and more "proof of concept." Here's one of those in action: For two and a half years, Wingstop has worked on a new Smart Kitchen that forecasts demand in 15-minute increments, telling the store how many wings to drop. The system takes into account more than 300 variables tailored to each unit, like weather, sales trends, and sports. It also features digital touch-screen displays at every work station instead of paper chits and an order-ready screen at the front so consumers can keep up with their order. Another feature: there are now sticker print outs that identify what flavors are in each package. At restaurants where the technology has been installed, wait times have been cut in half to about 10 minutes, and there have been notable improvements in guest satisfaction, accuracy, consistency, and employee turnover. In the delivery channel, Wingstop has been able to show up in under 30 minutes. Why is this important? Shorter wait times allow the brand to become a greater consideration. Instead of serving as a destination—with an average frequency of just three times per quarter and once a month—the quicker service could entice guests to visit more often, especially during on-the-go periods like the afternoon daypart. The Wingstop Smart Kitchen is in 400 restaurants and the chain hopes to complete the rollout by the end of the year. Again, real-time innovation in the back of the house. That seems to be the battleground right now. More here: https://lnkd.in/eMHMUkmZ

🔎 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

Excited to share insights from Walmart 's groundbreaking semantic search system that revolutionizes e-commerce product discovery! The team at Walmart Global Technology(the team that I am a part of 😬) has developed a hybrid retrieval system that combines traditional inverted index search with neural embedding-based search to tackle the challenging problem of tail queries in e-commerce. Key Technical Highlights: • The system uses a two-tower BERT architecture where one tower processes queries and another processes product information, generating dense vector representations for semantic matching. • Product information is enriched by combining titles with key attributes like category, brand, color, and gender using special prefix tokens to help the model distinguish different attribute types. • The neural model leverages DistilBERT with 6 layers and projects the 768-dimensional embeddings down to 256 dimensions using a linear layer, achieving optimal performance while reducing storage and computation costs. • To improve model training, they implemented innovative negative sampling techniques combining product category matching and token overlap filtering to identify challenging negative examples. Production Implementation Details: • The system uses a managed ANN (Approximate Nearest Neighbor) service to enable fast retrieval, achieving 99% recall@20 with just 13ms latency. • Query embeddings are cached with preset TTL (Time-To-Live) to reduce latency and costs in production. • The model is exported to ONNX format and served in Java, with custom optimizations like fixed input shapes and GPU acceleration using NVIDIA T4 processors. Results: The system showed significant improvements in both offline metrics and live experiments, with: - +2.84% improvement in NDCG@10 for human evaluation - +0.54% lift in Add-to-Cart rates in live A/B testing This is a fantastic example of how modern NLP techniques can be successfully deployed at scale to solve real-world e-commerce challenges!

We may be witnessing the biggest shift in ecommerce UX since mobile. This week, Shopify quietly updated the robots.txt files on major sites, including Allbirds, Alo Yoga, and Brooklinen, to warn against automated scraping by agents that complete full checkout flows without a final review step. At the same time, Shopify was added as a shopping search partner for OpenAI, joining Bing. There's no doubt that OpenAI would love to complete the shopping experience within its ecosystem. Meanwhile, AI payments startup Skyfire launched Agent Checkout, a technology that enables AI agents to navigate ecommerce sites completely autonomously, including research, sign-ups, logins, and payments. This tension is building fast, and decisions are being made quickly. Shopify’s move appears to be a shot across the bow aimed at preserving control of the checkout process (and revenue). OpenAI is clearly moving toward a future of agent-led commerce. And startups are rapidly building the infrastructure to support it. The big question isn’t whether the online shopping experience changes, it's how fast. And who gets to own that experience. If anyone. Fascinating time to be in the game.

𝗗𝗥𝗘𝗔𝗠𝗙𝗢𝗥𝗖𝗘 𝟮𝟬𝟮𝟱 - 𝗜‘𝗺 𝗶𝗻 𝗦𝗮𝗻 𝗙𝗿𝗮𝗻𝗰𝗶𝘀𝗰𝗼 𝘄𝗶𝘁𝗵 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲!! ☁️💙 [𝗔𝗱/𝗔𝗻𝘇𝗲𝗶𝗴𝗲] Many companies like to talk about AI painting big pictures of what might come next. Salesforce takes a different approach: they build! For more than a year now, Salesforce has been rolling out AI agents that are already running inside companies around the world. In yesterday’s keynote, 𝗠𝗮𝗿𝗰 𝗕𝗲𝗻𝗶𝗼𝗳𝗳, 𝗖𝗘𝗢 𝗼𝗳 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲, shared new use cases that made it easier than ever to understand how these agents really work in daily operations. 𝗕𝘂𝘁 𝗼𝗻𝗰𝗲 𝗮𝗴𝗮𝗶𝗻: 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮𝗻 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁? Imagine opening your laptop and finding a small team of digital helpers already inside. Each one is an expert… one knows your customers very well, one your workflows, one is your data expert. They don’t just answer your questions or react to commands but fix things before you see them and make work feel more fluent, faster, personal & fun. Marc Benioff described this evolution clearly: “𝘈 𝘺𝘦𝘢𝘳 𝘢𝘨𝘰, 𝘈𝘨𝘦𝘯𝘵𝘧𝘰𝘳𝘤𝘦 𝘸𝘢𝘴 𝘢 𝘱𝘳𝘰𝘥𝘶𝘤𝘵. 𝘛𝘰𝘥𝘢𝘺, 𝘪𝘵’𝘴 𝘵𝘩𝘦 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘣𝘦𝘩𝘪𝘯𝘥 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘸𝘦 𝘥𝘰.” 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗳𝗼𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀: –> up to 30 % faster service resolution and 40 % lower response time in customer operations –> productivity gains between 20–35 % across early adopters –> now used by 12,000+ companies from retailers to logistics firms –> interoperability with AWS, Microsoft & OpenAI, so it fits into existing tech stacks –> built-in governance and transparency layers, critical for regulated industries 𝗟𝗲𝘁’𝘀 𝘁𝗮𝗹𝗸 𝗮𝗯𝗼𝘂𝘁 𝘀𝗼𝗺𝗲 𝗰𝗼𝗻𝗰𝗿𝗲𝘁𝗲 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀: 𝗪𝗶𝗹𝗹𝗶𝗮𝗺𝘀 𝗦𝗼𝗻𝗼𝗺𝗮 – An AI “shopping chef” that knows your taste. It connects recipes, products, and past purchases turning every visit into a personalized experience that feels more like a conversation than a normal shopping experience. 𝗙𝗲𝗱𝗘𝘅 – AI agents read and route thousands of logistics documents in seconds catching exceptions, rerouting shipments, and reducing manual work across global operations. 𝗣𝗮𝗻𝗱𝗼𝗿𝗮 – An AI assistant follows you from online to in-store. What you like in chat appears ready in the boutique creating one seamless, personalized customer journey. 𝗗𝗲𝗹𝗹 – AI agents automate supplier onboarding verifying documents, sending approvals, and cutting setup time from 60 days to under 20. Faster partnerships, faster production. Each example shows how AI can move beyond experimentation, into real outcomes & that‘s what we need more now: REAL IMPLEMENTATION! Tomorrow continues with more 𝗧𝗲𝗰𝗵 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝗮 𝗚𝗟𝗢𝗕𝗔𝗟 𝗦𝗨𝗣𝗘𝗥𝗦𝗧𝗔𝗥 I was able to meet and we all probably know more for his music than for his tech… STAY TUNED!! 💙🦾 Do you already use AI Agents in YOUR business? –> If yes, what for? –> If not, which tasks would you 𝘭𝘰𝘷𝘦 to hand over to an agent friend?

Story of my date ! A few months ago, I walked into a Starbucks in the middle of a packed day. The line was long, and I was worried I’d have to rush. But the moment I walked in, I noticed something different. The barista at the counter greeted me with a warm smile, asked my name, and even commented on how lovely the weather was that day. I ordered my usual (a caramel macchiato, if you’re curious), and while waiting, I noticed how seamlessly their operations flowed. Despite the rush, the staff was calm, collected, and attentive to details—ensuring that every single customer felt valued. As I took my first sip, it struck me: Starbucks isn’t just about coffee; it’s about an experience. Here’s what I learned from Starbucks about delivering a world-class customer experience: - Personalization is Everything. Starbucks serves around 100 million customers a week globally—yet they make every customer feel like the only one in the room. By asking your name, offering customization (over 170,000 drink combinations possible), or remembering your usual order, they turn a transaction into a connection. - Consistency Creates Trust. Across 35,000+ stores in 80 countries, Starbucks delivers a predictable yet delightful experience. No matter where you are, the taste, ambiance, and service remain consistent. - Moments of Delight Make the Difference. Starbucks is famous for going the extra mile—writing a personalized note on your cup, offering a free drink on your birthday, or making the perfect foam on your latte. These small gestures turn ordinary moments into memorable ones. The Data Speaks for Itself • 60% of Starbucks customers use their loyalty app, showcasing how well they understand and engage their audience. • Their $1 billion annual investment in employee training ensures baristas can handle every situation with empathy and expertise. • Starbucks’ Net Promoter Score (NPS) of 77 is higher than most retail giants, showing the loyalty and love they inspire. How Can You Deliver a Class-Apart Customer Experience? 1. Empathy in Action: Listen actively to what your customers need. Make them feel heard. 2. Personalized Engagement: Leverage customer insights to offer tailored experiences that delight. 3. Operational Excellence: Behind every great experience is a strong backend. Invest in processes, people, and technology. Customer experience is no longer a “nice to have”; it’s a differentiator. In a world full of choices, it’s what makes your customers choose YOU—again and again. What’s one brand that made you feel special as a customer? I’d love to hear your story! #customerexperience #customers

In a recent discussion with Priscilla Ng, Prudential plc’s Group Chief Customer and Marketing Officer, we delved into Prudential’s shift towards customer-centricity. This conversation underscored the seamless integration of digital innovation and the essential human touch in the insurance sector.   Here are five key insights from our discussion applicable across industries:   🔹Strategic Integration of AI and Human Insight: Prudential is not just using AI to streamline processes; they are using it to significantly enhance personalization and customer service. From simplifying underwriting to transforming service at customer touchpoints like call centers, AI is proving to be transformative. How can other industries use AI not merely for efficiency but as a catalyst for customer connection?   🔹Empowering Employees: In the journey of digital transformation, the role of technology is as crucial as the people behind it. Priscilla emphasized the importance of equipping over 15,000 employees with the necessary mindset, skills, and tools to excel in a digitally evolving landscape. What strategies can companies implement to ensure their teams thrive amidst technological change?   🔹Balanced Approach to Digital and Human Interaction: Despite extensive technological integration, the human element remains critical at Prudential. Their approach ensures that digital enhancements support rather than replace human interactions, thereby strengthening customer relationships. How can businesses maintain this balance to enhance, not undermine, human connections?   🔹Navigating Challenges in Transformation: Adapting to digital transformation comes with challenges, from aligning large teams with new strategies to continuously adapting to emerging technologies. Priscilla shared that a steadfast focus on customer-centricity is essential for navigating these challenges. How can other organizations keep their focus on customer needs while managing transformation complexities?   🔹Continuous Learning and Adaptation: A crucial aspect of Prudential’s transformation is fostering an environment of continuous learning and adaptation. This involves training in new technologies and developing a deeper understanding of customer needs and behaviors. How can continuous learning be structured to keep pace with rapid technological advancements and evolving customer expectations?   This dialogue is part of McKinsey’s ongoing series exploring how leaders steer their companies through transformations. Stay tuned for more insights shaping today’s business landscape. Full interview: https://lnkd.in/gtjphW2s   #Leadership #DigitalTransformation #CustomerCentricity #InsuranceIndustry #AI