Innovation in Service Design

AI that can’t handle unknown alerts is just a (smart) rules engine with better marketing. Most AI SOC platforms today are built on pre-trained models. They can effectively automate triaging known phishing, malware, and endpoint alerts, but the second something unfamiliar shows up, it's back to manual. In this new piece with The Hacker News, we break down the difference between AI built to think and AI built to follow. Radiant Security's Adaptive AI SOC was developed from the ground up to do what pre-trained models can't: - Investigate previously unseen alerts, just like your best analyst would. - Pull relevant threat intel, vendor docs, and behavioral patterns for research. - Build a tailored triage and remediation path without human input. - Deliver full-spectrum triage across every alert type, without waiting on model updates or static playbooks. This is what makes Adaptive AI a true force multiplier and differentiates Radiant from other AI SOC platforms. Not just faster. Not just smarter. Actually scalable. Full article: https://hubs.li/Q03wbXQ60 #CyberSecurity #AI #SOC #SecurityAutomation

Jumping straight into solutions without truly understanding our customer's pain points? Reminded me of my early days when I'd create designs that looked great but didn't resonate with the audience. The missing piece? A Value Proposition Canvas. Here's what I learned: Start with customer jobs, pains, and gains BEFORE thinking about your product features Map your solutions directly to specific customer problems (I was shocked to find only 40% of our features actually solved core pain points) Test and validate assumptions regularly. What worked 6 months ago might not work today The marketing landscape is shifting towards hyper-personalization, and generic value propositions just don't cut it anymore. What's your process for understanding your customer's true needs? PS: Building a small community of marketers and AI enthusiasts to discuss these insights regularly. DM if you'd like to join our conversations! #MarketingStrategy #CustomerInsights #ValueProposition

Navigating the Top Drivers of Service Provider Switching: Embracing Innovation and Digital Transformation. In today's fast-paced business environment, service providers are essential partners for organizations aiming to modernize technology, streamline operations, and enhance strategic planning through IT outsourcing. Yet, despite longstanding relationships, companies regularly reevaluate the value delivered by their service providers. Why do organizations switch service providers? According to IDC's Services Path data, the drive towards rapid digital transformation is a leading reason. As the digital landscape evolves, businesses demand accelerated transformation and modernization to maintain competitiveness. This shift is about leveraging innovative technologies to stay in the game and lead it. For IT professionals, the top motivators include enabling rapid digital transformation, improving service quality, and reducing costs. Line-of-business leaders, meanwhile, seek improved service quality, decision support through enhanced data analytics, and are increasingly focused on sustainability. The Role of Innovation in Retaining Clients For service providers, understanding and addressing these priorities is crucial. Here’s how you can leverage innovation to strengthen your client relationships: 1 - Champion Digital Transformation: Establish yourself as a strategic ally dedicated to achieving impactful digital transformation results. This means proactively identifying new technologies and processes that align with and propel your clients' business objectives. 2 - Enhance Service Quality: Consistently innovate in service delivery to surpass expectations. Employ techniques like automation and artificial intelligence to enhance efficiency and customize solutions that meet changing client needs. 3 - Showcase Tangible Value: Quickly establish worth by delivering measurable results. By showcasing your impact, clients will see you as an indispensable partner rather than an optional supplier. By focusing on these key areas, service providers can ensure they remain invaluable to their clients, minimizing the risk of switching. In this transformative era, those who innovate and adapt will retain clients and help them lead their industries. Let's continue driving forward with innovation. What transformation strategies are you implementing to retain and enhance long-term client relationships? #DigitalTransformation #Innovation #ClientRetention #ServiceQuality

Welcome to this edition of the Fintech Wrap Up Newsletter! In today’s deep dive—crafted with insights from Activant Capital—we explore why usage-based billing (UBB) is emerging as one of the most impactful pricing models in modern software and services. UBB isn’t exactly new—it’s how we’ve long paid for utilities, rides, and phone bills. But in the era of SaaS, AI, and automation, it's making a powerful comeback. As software eats the world and machine-to-machine consumption surges, the traditional subscription model is losing ground. A recent report shows that 3 out of 5 SaaS companies already use some form of UBB, and that figure is expected to rise to 80% in the next few years. With SaaS growing at 7.3% CAGR and AI accelerating usage complexity, pricing is no longer a static lever—it’s a data challenge demanding flexibility and customer-centricity. The advantages are compelling: better net revenue retention (up to 9% higher than subscription-only peers), reduced churn, expanded total addressable markets, and higher customer satisfaction. But UBB isn’t without pitfalls—monitoring usage metrics accurately, managing billing systems, and ensuring revenue predictability remain key hurdles. That’s why many companies are now embracing hybrid pricing models, combining UBB with subscriptions to align value with customer behavior throughout the user journey. Underpinning this shift is a growing ecosystem of pricing infrastructure—from legacy ERP integrations to nimble UBB platforms like Metronome, M3ter, and Amberflo. Industry giants like Stripe and Zuora have jumped in through acquisitions, signaling confidence in UBB’s strategic value. And with pricing increasingly seen as a tech and data play, companies that nail dynamic, transparent, and usage-aware models will be the ones that thrive. In short, usage-based billing is no longer optional—it’s a strategic imperative. And whether you’re a SaaS founder, pricing strategist, or investor, now is the time to pay attention to how usage is reshaping value. #fintech #payments #billing

🚀 How AI is Transforming Service Business Models for OEMs and Service Providers is now becoming a reality. Artificial Intelligence is stepping up from a buzzword — the first use cases are demonstrating the strategic enablement that’s reshaping how Original Equipment Manufacturers (OEMs) and service providers deliver value. Traditionally, OEMs relied on reactive or preventive service models — waiting for failures or following fixed maintenance schedules. Today, AI is unlocking proactive, predictive, and even prescriptive service models, driving a complete shift in how businesses operates up to complete outcome or OEE based contracts. Here’s how AI is redefining the service landscape: 🔹 Predictive Maintenance: Machine learning models forecast potential failures before they occur, reducing downtime and improving asset reliability. 🔹 Remote Diagnostics & Automation: AI-driven analytics enable real-time issue detection and automated service recommendations — often fixing issues before customers even notice. 🔹 Outcome-Based Service Models: OEMs are transitioning from selling products to delivering outcomes — like uptime guarantees or performance-as-a-service — supported by data-driven insights. 🔹 Enhanced Customer Experience: Personalized service recommendations, intelligent chatbots, and faster resolutions are redefining customer expectations and loyalty. 🔹 Data Monetization: Service data becomes a strategic asset, enabling OEMs to create new revenue streams through analytics and optimization services. The result? AI isn’t just making service smarter — it’s making it strategic. Those who embrace it will evolve from service providers to value partners, driving efficiency, resilience, and sustainable growth. I have seen thw first real business cases working special for small and Medium sized companies. 💡 Is your organization ready to reimagine its service model with AI? #AI #OEM #DigitalTransformation #ServiceInnovation #PredictiveMaintenance #SmartServices #Industry40

How can we create a multi-generational customer experience strategy? The customer base today is not one generation, it’s five. And each generation brings a different definition of what “experience” means. ● Baby Boomers and Gen X value trust, familiarity, and human interaction. ● Millennials prioritize speed, convenience, and consistency. ● Gen Z demands personalization, purpose, and authenticity. ● Gen Alpha expects immersion, intuition, and instant gratification. So how do you build an ecosystem that works for all? 𝟭. 𝗗𝗲𝘀𝗶𝗴𝗻 𝗷𝗼𝘂𝗿𝗻𝗲𝘆𝘀, 𝗻𝗼𝘁 𝗱𝗲𝗺𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰𝘀 Each generation navigates your brand differently. Don’t build experiences around age, build them around behaviors. Understand what motivates action, what frustrates users, and what they value most. Then build modular journeys adaptable enough to flex between high-touch human support and seamless digital interactions. 𝟮. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗯𝘆 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿, 𝗻𝗼𝘁 𝗮𝗴𝗲. A Gen X who uses WhatsApp to shop has more in common with a GenZ-digital native than you think. Data should reveal how people behave, not just who they are. 𝟯. 𝗕𝗹𝗲𝗻𝗱 𝗵𝗶𝗴𝗵-𝘁𝗲𝗰𝗵 𝘄𝗶𝘁𝗵 𝗵𝗶𝗴𝗵-𝘁𝗼𝘂𝗰𝗵. Technology can deliver speed and scale, but emotion creates connection. While Gen Z loves automation, every generation still values empathy. The winning formula is when your AI systems understand intent, and your people understand emotion. 𝟰. 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗹𝗼𝗼𝗽 𝘁𝗵𝗮𝘁 𝗲𝘃𝗼𝗹𝘃𝗲𝘀. CX is not a one-time project; it’s a living ecosystem. The moment your data, teams, and technology stop learning your experience stops growing. 𝟱. 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝗶𝘁 𝘁𝗼 𝗰𝘂𝗹𝘁𝘂𝗿𝗲. In Saudi Arabia, customer experience is deeply tied to trust, community, and shared progress. Multi-generational strategies thrive when they reflect local values not just global best practices 𝟲. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗳𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝗻 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁. 
Some customers want a chatbot while others want a person. Some want self-service and others want a relationship. Offer choice and let the customer decide. If your CX strategy focuses on only one of these generations, you’re already losing another. We must as companies connect generations, not divide them, understanding that experience is universal, but the path to it is personal. #CustomerExperience #DigitalTransformation #CX #Customer #business

A CEO of the big IT & outstaffing company asked me this recently, and he was surprised by my answer. - How is AI affecting your remote teams business? - Very positively, we are getting even more requests - How? Most players in this market are worried because they built their business around one fixed offer. 🚫 A narrow tech stack 🚫 Specific frameworks 🚫 One tool, one trend, one-time hires But from day one, we took a different approach. We didn’t build our model to be a coding agency. We didn’t promise niche dev expertise in one language. We didn’t sell ourselves as a solution for just one tool. Instead, we made a strategic decision To become a platform A one-stop solution for building, scaling, and managing remote teams. Not just devs. Not just designers. But full-service operational power across functions and roles. We decided to meet clients where they are on their tech stack in their market at their speed This means… - If they need a frontend dev today and a growth marketer tomorrow, we got them. - If they shift from WordPress to Webflow or from HubSpot to custom CRMs, no problem. - If their product roadmap changes, we adapt. This flexibility is what allowed us to: ✅ Scale with our clients ✅ Maintain moderate but sustainable margins ✅ Retain 95% relationships for more than 5+ years ✅ Build trust, not just supply resources Being a platform means we don’t rely on trends. We build infrastructure. We integrate with the future, instead of chasing it. And honestly, the more time passes, the more I realize that we chose the right model for this business. Because one thing is guaranteed in this market: Demand for skills will always change. But if your model is adaptive, your mindset is service-oriented, and your execution is fast… You won’t just survive. You’ll grow with the change. #RemoteTeams #ArtificialIntelligence #AI #Platform #FutureOfWork

Static paywalls are leaving money on the table; intelligent pricing is how publishers reclaim it. Fixed paywalls block access and revenue potential. Relying on static pricing risks falling behind competitors like Schibsted, which saw a 19% increase in average revenue per user (ARPU) after adopting dynamic pricing (INMA, “Dynamic Paywalls Gain Momentum”, 2023). Traditional paywalls offer the same deal to every user, but not all readers are the same. Behaviour, loyalty, and content value vary, and a one-size-fits-all approach ignores these critical factors. This rigidity limits revenue yield and risks losing high-value audiences to more agile publishers. How AI-Driven Paywalls Maximise Revenue Yield Dynamic pricing, powered by AI, allows publishers to adjust subscription offers based on real-time user behaviour and perceived content value. Here’s how: ✅ Behavioural Targeting:  The Dallas Morning News increased conversions by 28% by offering discounts to frequent readers and trials to casual visitors (INMA, 2023). ✅ Content Valuation: The Financial Times uses dynamic pricing to align fees with content value, a strategy that contributed to a 14% YoY digital subscription growth (FT Group Annual Report, 2023). ✅Predictive Adjustments: Amedia reduced bounce rates by 18% using AI-driven exit-intent discounts (Reuters Institute, “Journalism, Media, and Technology Trends”, 2023). Instead of setting prices in stone, publishers use intelligent signals to flexibly match user willingness to pay, unlocking hidden revenue pockets. Three Practical Steps to Smarter Paywall Monetisation ✓ Audit Current Paywall Performance: Identify weak points like high drop-off rates or low conversion on high-value articles. ✓ Implement AI Segmentation: Use machine learning models to predict engagement and optimise when and how offers are shown. ✓ Define Dynamic Pricing Rules: Allow prices to shift based on real-time behaviour, content consumption trends, and traffic patterns. AI-driven dynamic paywalls aren’t about squeezing users—they're about aligning subscription offers with actual user value and intent. Early adopters have seen 20–35% higher conversion rates and up to 15% lift in average revenue per user (ARPU).Static pricing is no longer sustainable for publishers aiming to maximise revenue yield. Intelligent pricing strategies are the future. Here are key takeaways: 1. Static paywalls limit potential revenue growth. 2. AI-driven paywalls tailor offers based on user behaviour and content value. 3. Dynamic pricing improves both conversion rates and ARPU. 4. Publishers must audit, segment, and dynamically adjust pricing strategies to stay competitive. It’s time to audit your pricing model. If it can't adapt, your revenue won't, either. Is your paywall strategy optimised to maximise revenue yield in 2025? Share your thoughts with me in the comment section. #AIMonetization #DigitalPublishing #PaywallStrategy #SubscriptionRevenue #PublisherRevenue

AI is killing the hourly-billing revenue model (here's the fix) The 2,200 billable hours problem isn't just a law firm thing. Most professional services operate with the same structural misalignment. You bill by the hour. Your client wants their problem solved efficiently. The faster you work, the less you earn. After two decades in law, Gwen Griggs, JD, CEPA® spent the last 10 years building ADVOS Legal around a different model: outcome-based pricing adapted from Agile Scrum. Here's how it works: Every project gets broken into granular steps. Each step gets points based on four factors: time, criticality, value, and urgency. Standard NDA review? 2 points. Same NDA but you need it in 4 hours? 4 points. Mission-critical for your biggest customer? 3 points. The result? AI adoption becomes an advantage instead of a revenue threat. Client relationships transform from transactional to strategic. Projects that used to stall because clients worried about "running up the meter" actually reach completion. The broader principle: Your business model either aligns your success with your clients' success, or it puts them in opposition. Most professional services operate in opposition without thinking about it. Read the full breakdown of ADVOS Legal's 10-year experiment with outcome-based pricing 👇

The usual thinking often goes, "We're changing the website/platform, so there's no point optimizing what we already have." This perspective, while common, can inadvertently equate experimentation solely with optimisation, potentially overlooking the enormous benefits of integrating a truly experimental approach into development and innovation. A replatforming or redesign project typically involves a complex decision-making and MoSCoW-style exercise centered around a set of features. It's often impossible to exactly replicate old features on a new platform, meaning crucial decisions must be made about what's essential and what might be dropped. Likewise, new platforms can introduce various potential new features, but are they truly worth the investment? These decisions can become complex, political, and increasingly stressful as deadlines loom. The risk is that choices are made based on internal influence rather than what will genuinely serve the customer, which is inherently difficult to guess. How can you better manage this process? How can you genuinely know what will deliver the best customer experience and commercial outcomes? EXPERIMENTATION! When done properly, experimentation (including but not limited to A/B testing) can fast-track this entire process and help you deliver a project that actually works. Consider starting by creating a comprehensive list of all feature disparities that need to be addressed. Then, establish an initial prioritization. Next, plan and run experiments for each consideration. Finally, assess the likely benefit. Some experiments are remarkably straightforward. If a new platform won't include a particular feature "out of the box," you could A/B test removing it from your existing site to understand its true importance. Others might be more challenging. If a new platform offers recommendations but at additional cost, you could conduct more rudimentary experiments on your existing site to test the core concept. Moreover, these features don't have to be front-end; the same process can be applied to backend operational features if you have the right expertise. Experimentation isn't just optimisation; it's a critical tool for informed innovation. #experimentation #cro #productmanagement #growth #digitalexperience #experimentationledgrowth #elg #growthexperimentation