Improving Customer Experience

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!

I'm excited to announce the launch of AI Refinery for Sovereign and Agentic AI, a groundbreaking platform that deepens our partnership with NVIDIA. This first-of-its-kind platform champions data sovereignty and operational resilience through physical AI, paving the way for enhanced competitiveness in the journey toward agentic AI.   As I've mentioned before, I firmly believe that AI presents a unique opportunity for Europe to reinvent its economy, drive productivity, resilience, and competitiveness, and support future growth. I'm incredibly proud to see the momentum our clients are gaining, including Public Power Corporation, Roche, Kion Group, Noli, and Nestlé.   Nestlé, for instance, is launching a new AI-powered in-house service that will generate high-quality product content at scale for eCommerce and digital media channels. This initiative exemplifies the transformative potential of AI in driving business efficiency and innovation. The expansion of our AI Refinery platform is particularly significant for European organizations, enabling them to accelerate the deployment of AI agents while addressing their sovereignty concerns. This is especially crucial for the public sector and critical infrastructure industries, such as energy, telecommunications, and defense.   We continue to support our clients in maintaining control over their critical data and leveraging innovative AI solutions through this expanded AI Refinery platform. More details here: https://lnkd.in/dvekqfB6 #Noli #Nestle #PublicPowerCorporation #KionGroup #Roche #AgenticAI #AI #Accenture

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

Chaayos cut their marketing budget to zero. Not because they ran out of money. Because they realized something most brands miss. Last year, they stopped all ads, Meta campaigns, billboard spends, and influencer marketing. Instead, they invested everything into the actual experience: comfortable seating, better music, ceramic cups, Wi-Fi that works. The result? Customer acquisition matched their previous ad-driven levels. But now people stayed longer, spent more, and returned more often. Their VP of Marketing put it simply: "Marketing can only take you up to a point. Without fixing the brand experience first, nothing works long-term." This isn't anti-marketing. It's recognizing that in a world drowning in ads, the product itself is the best marketing. While competitors spent crores on performance marketing, Chaayos spent on making every visit memorable. Customers became their advertisers. The lesson isn't "don't do marketing." It's "fix what people experience before you tell them about it." Word-of-mouth scales better than paid ads when the experience is genuinely worth talking about. Sometimes the boldest marketing move is to stop marketing and start building something people can't help but share. #BrandBuilding #CustomerExperience #Startup #Growth

There's something almost nobody is talking about in AI - but it affects everything from asking ChatGPT for advice to companies deploying AI globally. A fascinating study tested major AI Models - the foundations powering tools millions use daily - against cultural values from 107 countries worldwide. The result? Each one reflected the same assumptions - those of English-speaking, Western European societies. None aligned with how people in Africa, Latin America, or the Middle East actually build trust, show respect, or resolve conflicts. Why does this matter? Imagine you're a global company rolling out AI customer service. Your system learns "best practice": when customers complain about late orders, "apologise briefly, offer a discount, and focus on quick resolution". In Germany, the direct, efficient approach works perfectly. Customer satisfied. But in Japan, that brief apology violates meiwaku - the cultural need to deeply acknowledge when you've caused someone inconvenience. Your "efficient" response feels dismissive and damages customer relationships. And in the UAE, the discount offer backfires completely. It feels like charity rather than respect. One AI system, similar contexts, completely different cultural outcomes. This isn't intentional though - it's inevitable. LLMs absorb embedded patterns about communication from their training data, and most of that data comes from billions of English web pages and content. The result? AI systems that, unless thoughtfully shaped, are blind to the diversity of human interaction. Klarna, the global payments company, made headlines in 2024 when they introduced an AI system that "did the work of 700 customer service reps", handled 2.5 million conversations in 35 languages, and cut response time by 82%. Technical triumph. 14 months later: "Klarna reverses AI strategy and is hiring humans again". Their CEO admitted it had led to "lower quality". Some reports said they'd seen a 20%+ decrease in customer satisfaction. What I think really happened: Klarna optimised for 35 languages while completely missing 35 different ways humans expect to be treated. The challenge? Most companies are focusing on technical integration and completely missing cultural intelligence. We measure response time and cost savings, but never ask, "which human complexities are we overlooking?" The goal isn't neutrality though - that's impossible and undesirable. It's conscious awareness. Understanding that the output from AI models is filtered through a specific cultural lens. For companies building AI strategies, key questions worth asking: * Which cultural assumptions are embedded in our AI systems? * How do we test cultural intelligence alongside technical performance? * Who provides this expertise in our AI teams? The individuals and organisations that develop this conscious awareness will make better decisions, while others unknowingly apply one-size-fits-all approaches to beautifully diverse human contexts.

If your CEO asks for deal updates in Slack, don’t expect reps to update Salesforce. You can throw all the tech, training, and sales ops resources you want at CRM adoption - but if leadership isn’t leading by example, none of it will stick. Here's the tl;dr: Reps don’t hate updating Salesforce because they’re lazy. They hate it because they know no one actually uses it. When leaders bypass the CRM - asking for updates in Slack, emails, or meetings - they send a clear message: “This system doesn’t matter. Your notes don’t matter. Just tell me directly.” And that’s how $100k+ Salesforce investments turn into glorified Rolodexes. So, how do you fix it? 1. Top-down adoption Start with the CEO. If they want deal updates, they need to ask for them in Salesforce. Chatter, Slack integrations, whatever it takes...but it has to flow through the system. 2. Make sales managers accountable Reps won’t change unless their managers enforce it. Run pipeline reviews directly from Salesforce dashboards. No exceptions. If it’s not in Salesforce, it doesn’t exist. 3. Quantify the pain Show reps how missing data costs them deals. Lost follow ups, misaligned hand offs, deals slipping through the cracks...all because the CRM isn’t up to date. 4. Reward the right behaviors Sales culture loves to celebrate closers. But what about the reps who close and keep a clean pipeline? Make data hygiene part of what gets recognized (and compensated). The reality is that CRM adoption isn’t a sales ops problem - it’s a leadership problem. If the top isn’t setting the example, the bottom won’t follow. And until that changes, you’ll keep throwing money at Salesforce while your reps keep their real pipeline in a Google Doc.

My API was dying. 500ms response times. Angry users. My manager asking "why is everything so slow?" I thought I was a decent developer. But my API performance? It was embarrassing. That's when my senior taught me something that changed everything: "𝗦𝗽𝗲𝗲𝗱 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗮𝗯𝗼𝘂𝘁 𝘆𝗼𝘂𝗿 𝗰𝗼𝗱𝗲. 𝗜𝘁'𝘀 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗲𝗻𝘁𝗶𝗿𝗲 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮." Here are the 7 game-changing strategies that took my APIs from embarrassing to lightning-fast: 𝟭. 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 𝗶𝘀 𝘆𝗼𝘂𝗿 𝘀𝗲𝗰𝗿𝗲𝘁 𝘄𝗲𝗮𝗽𝗼𝗻 The day I added Redis, my database queries dropped by 80%. Suddenly, the same data wasn't being fetched 1000 times a minute. 𝟮. 𝗬𝗼𝘂𝗿 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗶𝘀 𝗽𝗿𝗼𝗯𝗮𝗯𝗹𝘆 𝘁𝗵𝗲 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 One missing index was costing me 300ms per query. One `EXPLAIN` command saved my career. (Pro tip: If you're doing N+1 queries, you're doing it wrong) 𝟯. 𝗘𝘃𝗲𝗿𝘆 𝗯𝘆𝘁𝗲 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗮𝘆𝗹𝗼𝗮𝗱 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 Switched from JSON to Protocol Buffers. 40% smaller responses. Users stopped complaining about loading times. 𝟰. 𝗖𝗼𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝗶𝘀 𝗳𝗿𝗲𝗲 𝘀𝗽𝗲𝗲𝗱 Enabled Gzip compression. Boom. 70% smaller responses. Literally a one-line config change. 𝟱. 𝗔𝘀𝘆𝗻𝗰 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝘀𝗮𝘃𝗲𝗱 𝗺𝘆 𝘀𝗮𝗻𝗶𝘁𝘆 Stopped making users wait for background tasks. Email sending? Background job. Image processing? Background job. Response times went from 2s to 200ms. 𝟲. 𝗣𝗮𝗴𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗶𝘀𝗻'𝘁 𝗼𝗽𝘁𝗶𝗼𝗻𝗮𝗹 Returning 10,000 records in one response? Recipe for disaster. Paginate. Filter. Sort. Your servers will thank you. 𝟳. 𝗠𝗼𝗻𝗶𝘁𝗼𝗿 𝗹𝗶𝗸𝗲 𝘆𝗼𝘂𝗿 𝗷𝗼𝗯 𝗱𝗲𝗽𝗲𝗻𝗱𝘀 𝗼𝗻 𝗶𝘁 (Because it does) Set up alerts. Profile slow endpoints. Fix problems before users notice them. The brutal truth? Most developers write code first, optimize later. But the best APIs are designed for performance from day one. Your users don't care about your elegant code structure. They care about speed. My API now: - 50ms average response time - 99.9% uptime - Happy users - Happier manager Your turn: What's the one API performance mistake you wish you could warn your younger self about? Drop it below 👇 Let's help each other avoid these painful lessons.

Elevating Service in Food & Beverage: Keys to Hospitality Excellence The food and beverage industry thrives on delivering exceptional experiences. Whether in a fine-dining restaurant, a bustling café, or a luxury hotel, hospitality staff play a crucial role in shaping guest satisfaction. Here’s a guide to refining service standards and excelling in your role. 1. Understanding Guest Expectations. Guests expect more than just a meal—they seek a holistic experience. This includes ambiance, attentiveness, and personalized service. A warm greeting and sincere engagement can transform an ordinary visit into a memorable one. 2. Mastering Product Knowledge. Knowing the menu inside and out is essential. Staff should be able to recommend dishes confidently, suggest pairings, and address dietary restrictions. It builds trust and enhances the guest experience. 3. Efficiency & Attention to Detail. Precision matters—whether it's setting tables, timing orders, or ensuring that every dish meets quality standards. Attention to small details, such as napkin placements and proper glassware, elevates the overall experience. 4. Clear Communication & Teamwork. Strong communication between staff members ensures seamless service. Efficient teamwork reduces errors and enhances guest satisfaction. Kitchen coordination, order accuracy, and proactive problem-solving are key. 5. Handling Complaints Gracefully. Not every interaction will be smooth, but professionalism is paramount. When guests voice concerns, active listening and prompt solutions demonstrate commitment to service excellence. A well-handled complaint can turn an unhappy guest into a loyal customer. 6. Upselling Without Being Pushy. Strategic recommendations of premium items or combos benefit both guests and the establishment. The key is offering value rather than forcing sales—suggesting a wine pairing or a chef’s special enhances the dining experience. 7. Maintaining Hygiene & Presentation.. Cleanliness is non-negotiable. Proper attire, grooming, and hygienic practices contribute to a professional image and reassure guests of food safety standards. Consistency in presentation reflects a strong brand identity. 8. Staying Motivated & Engaged. A positive attitude makes a difference. Passionate and dedicated employees create an inviting atmosphere. Continued learning—whether through training sessions or observing industry trends—keeps service fresh and dynamic. Hospitality staff in food and beverage are more than servers—they are experience architects. By refining skills, embracing guest engagement, and upholding excellence, professionals can leave lasting impressions that turn first-time visitors into regular patrons.

What if your biggest growth opportunity isn’t in your sales pipeline, but in your post-sale experience? While most revenue teams obsess over lead volume and top-of-funnel performance, high-performing organizations are reallocating resources toward the one area most overlooked (and most profitable): customer retention. You’re not losing revenue because you can’t acquire customers; it’s because you can’t keep them. Customer experience, loyalty, and client services are no longer “support” functions. They’re strategic growth levers. And the cost of ignoring them is compounding: - Customer acquisition costs (CAC) are rising 60–75% - Churn is erasing pipeline gains before they hit the forecast - Siloed orgs are failing to act on critical post-sale insights Here’s how growth leaders are operationalizing customer-centricity to outpace competitors: ✅ Shift GTM strategy from funnel-filling to journey stewardship. Map the full customer lifecycle, then build cross-functional ownership for every phase beyond the sale. ✅ Hardwire retention into revenue models. Redefine revenue metrics: CLV, NRR, and CSAT become as critical as quota attainment. ✅ Turn customer success into a revenue function. Enable CS teams to identify expansion triggers, churn signals, and feedback loops that inform both product and GTM. ✅ Engineer feedback into daily operations. Surface real-time insights from support, community, and product usage–not quarterly surveys or lagging indicators. The companies doing this right see up to a 25% lift in renewals, 35% higher LTV, and customer referrals that shorten sales cycles by 30–50%. Want to build a revenue engine that scales and sustains? Start by asking: How are we designing for the customer after the contract is signed? Read the full post: https://lnkd.in/dY3Rxsc9 __________ For more on growth and building trust, check out my previous posts. Christine Alemany Join me on my journey, and let's build a more trustworthy world together. #Fintech #Strategy #Growth

If your CX Program simply consists of surveys, it's like trying to understand the whole movie by watching a single frame. You have to integrate data, insights, and actions if you want to understand how the movie ends, and ultimately be able to write the sequel. But integrating multiple customer signals isn't easy. In fact, it can be overwhelming. I know because I successfully did this in the past, and counsel clients on it today. So, here's a 5-step plan on how to ensure that the integration of diverse customer signals remains insightful and not overwhelming: 1. Set Clear Objectives: Define specific goals for what you want to achieve. Having clear objectives helps in filtering relevant data from the noise. While your goals may be as simple as understanding behavior, think about these objectives in an outcome-based way. For example, 'Reduce Call Volume' or some other business metric is important to consider here. 2. Segment Data Thoughtfully: Break down data into manageable categories based on customer demographics, behavior, or interaction type. This helps in analyzing specific aspects of the customer journey without getting lost in the vastness of data. 3. Prioritize Data Based on Relevance: Not all data is equally important. Based on Step 1, prioritize based on what’s most relevant to your business goals. For example, this might involve focusing more on behavioral data vs demographic data, depending on objectives. 4. Use Smart Data Aggregation Tools: Invest in advanced data aggregation platforms that can collect, sort, and analyze data from various sources. These tools use AI and machine learning to identify patterns and key insights, reducing the noise and complexity. 5. Regular Reviews and Adjustments: Continuously monitor and review the data integration process. Be ready to adjust strategies, tools, or objectives as needed to keep the data manageable and insightful. This isn't a "set-it-and-forget-it" strategy! How are you thinking about integrating data and insights in order to drive meaningful change in your business? Hit me up if you want to chat about it. #customerexperience #data #insights #surveys #ceo #coo #ai