Hybrid Customer Experience Techniques

On this fine Friday, allow this VC to pitch you a business idea born out of personal frustration. I’m a dedicated DAU (only because we don’t yet track Hourly Active Users), and yet these models barely know me. At this point, I feel like a traveling salesman from the 1800s, lugging a little suitcase of context from one AI to the next: “Here are my preferences. My priorities. My professional history. Please remember me.” And I do it. Because when you feed these tools the right context, they’re remarkable. But that potential - so close you can practically taste it - remains just out of reach. Instead, we’re stuck in a Groundhog Day loop of contextless first dates with memoryless machines. The intelligence is there. It’s the memory that fails you. What we need is a Personal Memory Vault: 🔐 Secure, encrypted, private by default 🔄 Portable across models - plug-and-play with any LLM, agent, or assistant 🧩 Composable and modular - you choose what to share, with whom, and for how long 📜 Versioned and auditable - full transparency into how and when your data is used We can build: 🔑 APIs that give developers secure, permissioned access to memory bundles - like professional context, health profiles, or travel preferences 📈 A user dashboard to track which apps have access, what they know, and when they’ve used it 💵 A freemium model for consumers - and licensing options for apps or agents that want to deliver memory-powered experiences Think: a personal OS that updates passively through your interactions. Plaid, but for context - storing a growing, contextual understanding of your life. Yes, it’s about making AI more useful. But it’s more about control. We need the memory layer to be model agnostic and platform independent, because Big Tech’s next move is obvious: offer “personalized memory” - and use it to lock you in tighter than ever. Sam Altman has already said he wants ChatGPT to remember your whole life. Look, I’m an OpenAI fan. But I reserve the right to change my mind the moment Google DeepMind, Anthropic, or xAI drops something better. What I don’t want is to spend my weekends migrating my digital soul like it’s an IBM mainframe in 1986. I don’t want a hundred context engines. I don’t want to be platform-loyal out of sunk-cost guilt. I just want to stop going on first dates with my own data. I’m just a girl, standing in front of an AI, asking it to remember her. 💔

Loyalty is failing. Gen Z & long-term commitment. 22% of Gen Z consumers consider themselves loyal to one brand is a clear warning for legacy loyalty strategies. Unlike previous generations, Gen Z doesn’t see brand loyalty as a long-term commitment, they’re loyal to moments, not just names. +43% increase in engagement and sales conversions among Gen Z Beauty brands offering "limited-edition drops" and collaborative experiences. +71% Gen Z say they would rather spend money on an experience than a product. >>Loyalty is FAILING, but why<< +Transactional systems feel outdated: Point-based rewards for repeat purchases don’t excite this audience. They expect more than discounts or free samples. +They’re brand-agnostic but experience-driven: Gen Z freely switches between brands if the experience, aesthetic, or values feel fresher or more aligned with their identity. +They buy into stories, not just products: They want to align with brands that represent something, social causes, cultural movements, or communities they relate to. >>DYNAMIC LOYALTY<< What’s this? as it name indicates its a system that rewards interaction, aligns with their values, and constantly evolves. And that is what your brand needs. → Create experience-driven loyalty programs: Offer early access to limited drops, invite-only events, or backstage content. Think like a fan club, not a punch card. +Example: A loyalty tier that unlocks tickets to a pop-up experience or an exclusive AR filter. →Let them co-create: Invite Gen Z customers to co-develop product ideas, designs, or campaign themes. Give them ownership in your brand’s creative journey. +Example: Voting on packaging designs or joining beta tester groups. →Align with their values: Sustainability, inclusivity, and social good aren’t nice-to-haves. they’re expectations. Use loyalty programs to reward actions too, like recycling, sharing causes, or supporting small creators. +Example: “Earn loyalty points by returning empties or attending a sustainability workshop.” →Deliver constant novelty: Rotate limited editions regularly. Use scarcity and surprise to create FOMO and buzz. +Gen Z doesn’t commit to a single brand, but they’ll keep returning if each visit feels fresh and share-worthy. →Go omnichannel but social-first. Should live across TikTok, Instagram, pop-ups, and web. Let them earn or unlock rewards through social engagement, not just purchases. +Example: A user gets exclusive content or perks for creating UGC with your brand. Bottom Line. Loyalty must be earned over and over through experience, relevance, and emotional connection. Think dynamic loyalty: a system that rewards interaction and go for it. Find my curated search of examples and get ready for your next HIT. Featured Brands: Balmain Benefit Chanel Charlotte tilbury Cerave Fennty L’Oreal OGX YSL #beautypackaging #beautybusiness #beautyprofessionals #experienceretail #luxuryexperiences #genz

In customer experience (CX), the closed-loop feedback (CLF) model has been a cornerstone for over two decades, originally designed to ensure responsiveness and adaptation. It's time for a change. With the advent of artificial intelligence, it's clear that merely adapting this model isn't enough. It's old tapes. It needs to evolve. Here's what's next: Real-time Interaction Management: Traditional CLF reacts to feedback after the fact. And, traditionally, closing the "inner loop" requires a human to follow up. AI turns this on its head. Imagine a system that adjusts the customer journey in real-time based on predictive analytics, reducing friction points before they affect the customer experience. Large Action Models: We all know that AI can dive deep into data lakes to instantly identify patterns and root causes of customer dissatisfaction. This rapid analysis allows companies to not only close the feedback loop faster, but also implement more effective solutions. This will come in the evolution of Large Language Models, or LLMs, to LAMs, or Large Action Models. Continuous Learning Systems: AI transforms CLF from a loop that ends into continuous cycle of improvement. These systems learn from each interaction, constantly updating and refining strategies to enhance the customer experience. This means that the feedback loop is ever-evolving, driven by AI's ability to adapt to new information and complex variables, seamlessly. CX leaders have to embrace AI's potential to redefine our foundational practices. It's time to innovate beyond the traditional CLF and leverage AI to deliver personalized experiences, and at scale. How are you thinking about adaptive, predictive, and personalized CX strategies? Your answer can't be to hire more people to close more loops. #customerexperience #ai #journeymanagement #survey #CLF

If more of your store sales start on TikTok lately, you might wanna read this. 𝘛𝘩𝘦 𝘴𝘢𝘭𝘦 𝘪𝘴 𝘥𝘦𝘤𝘪𝘥𝘦𝘥 𝘣𝘦𝘧𝘰𝘳𝘦 𝘺𝘰𝘶𝘳 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘦𝘷𝘦𝘯 𝘦𝘯𝘵𝘦𝘳𝘴 𝘺𝘰𝘶𝘳 𝘴𝘵𝘰𝘳𝘦. The checkout happens in-store. But the sale happens everywhere else. Here's the reality: This year 60%+, and in 2027, 70% of retail sales will be digitally influenced. I can't emphasize this enough; here's what most brands miss—digital influence isn't just about online sales. It's about shaping every moment before the customer even walks into your store. L'Oréal cracked this code: 100M+ AR try-on sessions driving real conversions. 31 brands orchestrating seamless experiences across 72 countries. No.1 in beauty influencer marketing (29% market share), 20-80% higher conversion rates through enhanced digital experiences. The new customer journey isn't linear—it's layered: - They discover you on social - Research you through reviews and UGC - Try your product virtually through AR - Get retargeted with personalized content - Finally purchase in-store (feeling confident they're making the right choice) Every touchpoint matters, and every interaction influences the final decision. The brands winning today aren't just selling products—they're orchestrating experiences across owned, paid, and earned media that guide customers from curiosity to checkout. Digital discovery is increasingly pay-to-play and shoppers are paying attention. ++ Tactical Recommendations for CPG / FMCG Brands ++ 1. Beyond just having perfect, high SOV product pages, create discovery ecosystems. - Optimize for "zero-moment-of-truth" searches. - Activate shoppable content at scale. - Leverage user-generated content as social proof. Brands that do these see a 35% higher conversion rate from digital touchpoints to in-store purchases. 2. Connect digital engagement directly to retail execution. - Geo-target digital campaigns to drive foot traffic - Create "store-specific" digital content CPG brands using geo-targeted social ads see a 23% higher in-store sales lift in targeted markets. 3. Most important one; stop flying blind—measure digital influence on offline sales. - Implement unique promo codes for each digital touchpoint to track conversion paths. - Use customer surveys at point of purchase. - Partner with retailers on shared data insights Brands with proper attribution see 15-25% improvement in marketing ROI within 12 months. 𝗧𝗼 𝗮𝗰𝗰𝗲𝘀𝘀 𝗮𝗹𝗹 𝗼𝘂𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗼𝗹𝗹𝗼𝘄 ecommert® 𝗮𝗻𝗱 𝗷𝗼𝗶𝗻 𝟭𝟰,𝟲𝟬𝟬+ 𝗖𝗣𝗚, 𝗿𝗲𝘁𝗮𝗶𝗹, 𝗮𝗻𝗱 𝗠𝗮𝗿𝗧𝗲𝗰𝗵 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝘄𝗵𝗼 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲𝗱 𝘁𝗼 𝗲𝗰𝗼𝗺𝗺𝗲𝗿𝘁® : 𝗖𝗣𝗚 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗚𝗿𝗼𝘄𝘁𝗵 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. #CPG #FMCG #AI #ecommerce Procter & Gamble PepsiCo Unilever The Coca-Cola Company Nestlé Mondelēz International Kraft Heinz Ferrero Mars Colgate-Palmolive Henkel Bayer Haleon Kenvue The HEINEKEN Company Carlsberg Group Philips Samsung Electronics Panasonic North America

Empathy-powered. Digitally enabled. Patient connected In today’s fast-evolving healthcare landscape, connected care isn’t just about tech—it’s about enhancing human connection at every touchpoint. Key insights from Deloitte ’s 2025 Global Health Care Executive Outlook show how we can harmonize digital transformation with the human-centric care our patients deserve: 1. Prioritize integrated digital platforms • ~70% of global C‑suite leaders are investing in digital tools and services to enable seamless patient journeys . • This connectivity supports continuous care—whether in-hospital, remote, or at home. 2. Modernize core systems while keeping the human anchor • 60% are upgrading EMRs and ERP systems . • When clinicians can access integrated data swiftly, they spend less time documenting and more time connecting with patients. 3. Embed empathy into every digital interaction • Cybersecurity (78% prioritize) builds trust—patients feel cared for when their data is protected . • A secure, respectful environment is the foundation for truly human-centered care. 4. Enhance clinician well-being to improve connectedness • 80% of leaders recognize workforce strain; digital tools can reduce burnout and foster deeper patient engagement . • When staff feel supported, they show up both professionally and emotionally. 5. Expand virtual and hybrid care with a personal touch • 65% of consumers find virtual care more convenient —but scaling it successfully means integrating empathy and follow-up. • Reimagining care pathways ensures consistent human connection, whether digital or face-to-face. ⸻ 🎯 Managing connected care with humanity means: • Leveraging interoperable systems that share real-time insights across care teams. • Training clinicians in digital empathy—listening through the screen, addressing emotional cues. • Designing secure, intuitive platforms that empower patients without overwhelming them. • Supporting staff with AI-driven admin relief, enabling them to focus on people. • Creating holistic care pathways that blend telehealth, in-clinic, and home-based services under one cohesive plan. By weaving technology into our care systems thoughtfully, we can create a healthcare experience that’s efficient, personalized, and emotionally resonant. Looking forward to your thoughts: how is your organization balancing connectivity with compassion? Sara Siegel Link to the report: https://lnkd.in/etDPEc3a #connectedcare

“Going digital” did not cost pharma its HCP relationships. What hurts relationships is fragmented execution: sporadic pilots, vanity dashboards, and weak field–medical–marketing coordination. When orchestrated, digital amplifies human connection: it extends reach between visits, carries scientific context forward, and helps reps/MSLs show up with precisely what that clinician needs next. Industry data—and our own work—bear this out. Hybrid, connected engagement outperforms “field‑only” and “digital‑only". Connected field + digital drives adoption. Veeva Systems Pulse shows that when you sequence touchpoints (e.g., rep visit → timely digital exposure), prescribing likelihood rises; pairing rep meetings with brand web visits or speaker program exposure substantially increases treatment starts. That’s not digital “crowding out” humans; it’s digital supporting humans. Pre‑launch scientific engagement matters. Field medical education before launch increases adoption (reported at ~1.5×–1.6× within six months). This depends on coordination across medical and commercial—exactly the “connected model” critics say we should abandon. HCPs aren’t rejecting digital, they’re asking for the right mix. Across 20,000+ HCPs in 38 countries, IQVIA’s finds ongoing preference for hybrid: face‑to‑face remains important but has steadily ceded share; email and on‑demand formats continue to play material roles. The signal is not “go back to field‑only,” but “align channel mix to each HCP’s preference and specialty.” Inside our own material engagement at The Palindromic, we’ve documented the same reality and built plays to act on it (journey mapping, consent‑aware 360s, and Next Best Action / AI agents to trigger the next meaningful interaction for each clinician). One may say: “Only reps/MSLs know what lands”? Marketing can—and should—know too! The fix is not “less digital,” it’s better content governance and activation at the point of need. The real problem is short‑horizon “shiny objects,” not digital itself. Indeed, chasing tools without operating‑model change fails. But the remedy is to mature orchestration, not to “stop chasing digital.” Trust scales when medical and commercial operate with shared goals. My take is: define a North‑Star HCP value score (not vanity web metrics): did we solve a clinical question, reduce time‑to‑treatment, or shortcut a workflow? Then align incentives for reps, MSLs, and marketers around that score. Make reps the quarterback of omnichannel. Equip them with consent‑aware 360s, NBA prompts, and one‑to‑one approved email so they can pull digital into the relationship. Measure sequences, not channels. Run lightweight experimentation every quarter; reallocate from bulk email to rep‑triggered content when ROI warrants. Right‑size content. Fewer, higher‑value assets that field actually uses. Pulse data shows activation—not volume—drives outcomes.

India's retail landscape is rapidly transforming as brands blend physical and digital (“phygital”) experiences to meet changing consumer expectations. Urban and rural shoppers are engaging across touchpoints, driving unique trends in the country. Indian consumers are among the world’s most active on mobile phones, and 65% of urban shoppers start their buying journey online before visiting stores. Major Indian retailers are focusing on their apps and loyalty programs, allowing seamless offline-online transitions. E-commerce adoption is growing fastest in non-metro cities, but many consumers still value in-store experiences to touch and try products before buying. Retailers combine digital price comparisons with local fulfillment. India’s rapid UPI (Unified Payments Interface) adoption enables effortless in-store or online payments, further blending channels. QR code payments and “buy-online-pick-up-in-store” (BOPIS) are increasingly common. Key Indian Trends Indian retailers are use AI-powered chatbots in Hindi and regional languages on WhatsApp and apps, tailoring offers and support for millions of users—even in small towns. Flagship sales (Amazon, Flipkart Big Billion Days) create both digital and in-store excitement, with brands aligning pricing and stock to handle surges. The phygital revolution is reshaping how Indian consumers shop. With UPI and WhatsApp at their fingertips, even shoppers in smaller cities now expect seamless online-offline experiences—from inventory checks to in-store pick-up. Indian brands combining local flavor, digital innovation, and sustainability are leading the way. How is your retail strategy harnessing India’s unique digital spirit? #retail #digital #omnichannel #userexperience #ecommerce

In marketing, choosing the right campaign strategy — such as whether to reach customers through SMS or email — is critical. These decisions shape how effectively brands connect with their audiences. In a recent tech blog, Klaviyo’s data science team shared how they used uplift modeling and counterfactual learning to help marketers deliver more personalized campaigns at scale. The team began with a simple but powerful insight. Instead of defining audience segments first and then randomizing within each group to test different strategies, it’s mathematically equivalent to randomizing treatments first and segmenting afterward. In practice, this means you can run a single randomized experiment — for example, comparing SMS versus email — across the entire audience, and later analyze how different subgroups responded to each treatment. Building on this foundation, the team applied uplift modeling to estimate how each recipient would respond under different treatments. The result is a system that predicts which customers are more likely to engage via SMS versus email — and automatically personalizes campaign delivery accordingly. The team ultimately turned this approach into a product feature, empowering marketers to design smarter, data-driven strategies with minimal manual testing. It’s a great example of how causal inference and machine learning can go beyond analysis — directly shaping how real-world marketing decisions are made. #DataScience #MachineLearning #UpliftModeling #CounterfactualLearning #Personalization #Marketing – – –  Check out the "Snacks Weekly on Data Science" podcast and subscribe, where I explain in more detail the concepts discussed in this and future posts:    -- Spotify: https://lnkd.in/gKgaMvbh   -- Apple Podcast: https://lnkd.in/gFYvfB8V    -- Youtube: https://lnkd.in/gcwPeBmR https://lnkd.in/gBgBiTJj

Your marketing playbook just expired. AI has rewritten every rule while most brands are still playing by 2019 strategies. The companies adapting fastest aren't the ones with bigger budgets or better tech teams. They're the ones who understand how AI has fundamentally changed customer behaviour. Here's what the winners are doing differently: 1. The New Search Landscape: SEO meets LLM Traditional keywords are the past. Conversational queries are everything. Example: REI shifted from keyword-stuffed descriptions to contextual content addressing specific use cases, increasing AI-summarised results visibility by 47%. Reality check: Google's AI Overviews now appear in nearly half of all search results. 2. AI Assistants as Gatekeepers Your brand must be recognised by AI as a category leader to enter consideration sets. Example: Best Buy organised product attributes to match natural customer questions, achieving 35% increase in organic traffic from voice searches. The shift: AI now filters options before consumers see them. 3. Attention Compression Consumer attention spans shrink as AI summarises everything instantly. Action point: Front-load your value proposition in all communications. The pattern: Customers want to digest information about products quickly, not hunt to understand what’s in it for them. 4. Hyper-Personalisation Without Creepiness AI enables true 1:1 marketing at scale, but only if you balance customisation with transparency. Example: Sephora's Skin IQ tool provides personalised skincare recommendations, driving 35% growth in skincare sales. The principle: Use preference-based content sequencing with full transparency about data usage. 5. Multi-Modal Content Strategy AI-driven consumers expect seamless experiences across text, voice, and visual channels. Example: Domino's "AnyWare" approach allows ordering through voice assistants, text, social media, and apps. The requirement: Build centralised content hubs ensuring consistent messaging across all channels. 6. The Human Advantage As AI handles transactions, authentic human connection becomes your competitive edge. Example: Lululemon's in-store community events resulted in 25% higher repeat purchase rates compared to online-only shoppers. The opportunity: Community-building programs generate 23% higher customer lifetime value. The brands that thrive won't be those with the most sophisticated AI tools. They'll be the ones that use AI to enhance human connection rather than replace it. Which of these shifts will you implement first? ♻️ Found this helpful? Repost to share with your network.  ⚡ Want more content like this? Hit follow Maya Moufarek.

The rapid development of artificial intelligence (AI) is outpacing the awareness of many companies, yet the potential these AI tools hold is enormous. The nexus of AI and emotional intelligence (EQ) is emerging as a revolutionary game-changer. Here’s why this intersection is crucial and how you can leverage it: 🔍 AI can handle data analysis and repetitive tasks, allowing humans to focus on empathetic, creative, and strategic work. This synergy enhances both productivity and the quality of interactions. Imagine a retail company struggling with high customer churn due to poor customer service experiences. By integrating AI tools like IBM Watson's Tone Analyzer into their customer service process, they could identify emotional triggers and tailor responses accordingly. This proactive approach could transform dissatisfied customers into loyal advocates. Practical Application: AI-driven sentiment analysis tools can help businesses understand customer emotions in real-time, tailoring responses to improve customer satisfaction. For example, using AI chatbots for initial customer service interactions can free up human agents to handle more complex, emotionally charged issues. Strategy Tip: Integrate AI tools that provide real-time sentiment analysis into your customer service processes. This allows your team to quickly identify and address customer emotions, leading to more personalized and effective interactions. By integrating AI with EQ, businesses can create a more responsive and human-centric experience, driving both loyalty and innovation. Embracing the combination of AI and EQ is not just a trend but a strategic move towards future-proofing your business. We’d love to hear from you: How is your organization leveraging AI to enhance emotional intelligence? Share your thoughts and experiences in the comments below! #AI #EmotionalIntelligence #CustomerExperience #Innovation #ImpactLab