Telecom companies last year spent nearly billion in capital expenditures and over trillion in operating expenditures. These large expenses are due in part to laborious manual processes that telcos face when operating networks that require continuous optimizations. For example, telcos must constantly tune network parameters for tasks — such as transferring calls from one network to another or distributing network traffic across multiple servers — based on the time of day, user behavior, mobility and traffic type. These factors directly affect network performance, user experience and energy consumption. To automate these optimization processes and save costs for telcos across the globe, NVIDIA today unveiled at GTC Paris its first AI Blueprint for telco network configuration. At the blueprint’s core are customized large language models trained specifically on telco network data — as well as the full technical and operational architecture for turning the LLMs into an autonomous, goal-driven AI agent for telcos. Automate Network Configuration With the AI Blueprint NVIDIA AI Blueprints — available on build.nvidia.com — are customizable AI workflow examples. They include reference code, documentation and deployment tools that show enterprise developers how to deliver business value with NVIDIA NIM microservices. The AI Blueprint for telco network configuration — built with BubbleRAN 5G solutions and datasets — enables developers, network engineers and telecom providers to automatically optimize the configuration of network parameters using agentic AI. This can streamline operations, reduce costs and significantly improve service quality by embedding continuous learning and adaptability directly into network infrastructures. Traditionally, network configurations required manual intervention or followed rigid rules to adapt to dynamic network conditions. These approaches limited adaptability and increased operational complexities, costs and inefficiencies. The new blueprint helps shift telco operations from relying on static, rules-based systems to operations based on dynamic, AI-driven automation. It enables developers to build advanced, telco-specific AI agents that make real-time, intelligent decisions and autonomously balance trade-offs — such as network speed versus interference, or energy savings versus utilization — without human input. Powered and Deployed by Industry Leaders Trained on 5G data generated by BubbleRAN, and deployed on the BubbleRAN 5G O-RAN platform, the blueprint provides telcos with insight on how to set various parameters to reach performance goals, like achieving a certain bitrate while choosing an acceptable signal-to-noise ratio — a measure that impacts voice quality and thus user experience. With the new AI Blueprint, network engineers can confidently set initial parameter values and update them as demanded by continuous network changes. Norway-based Telenor Group, which serves over 200 million customers globally, is the first telco to integrate the AI Blueprint for telco network configuration as part of its initiative to deploy intelligent, autonomous networks that meet the performance and agility demands of 5G and beyond. “The blueprint is helping us address configuration challenges and enhance quality of service during network installation,” said Knut Fjellheim, chief technology innovation officer at Telenor Maritime. “Implementing it is part of our push toward network automation and follows the successful deployment of agentic AI for real-time network slicing in a private 5G maritime use case.” Industry Partners Deploy Other NVIDIA-Powered Autonomous Network Technologies The AI Blueprint for telco network configuration is just one of many announcements at NVIDIA GTC Paris showcasing how the telecom industry is using agentic AI to make autonomous networks a reality. Beyond the blueprint, leading telecom companies and solutions providers are tapping into NVIDIA accelerated computing, software and microservices to provide breakthrough innovations poised to vastly improve networks and communications services — accelerating the progress to autonomous networks and improving customer experiences. NTT DATA is powering its agentic platform for telcos with NVIDIA accelerated compute and the NVIDIA AI Enterprise software platform. Its first agentic use case is focused on network alarms management, where NVIDIA NIM microservices help automate and power observability, troubleshooting, anomaly detection and resolution with closed loop ticketing. Tata Consultancy Services is delivering agentic AI solutions for telcos built on NVIDIA DGX Cloud and using NVIDIA AI Enterprise to develop, fine-tune and integrate large telco models into AI agent workflows. These range from billing and revenue assurance, autonomous network management to hybrid edge-cloud distributed inference. For example, the company’s anomaly management agentic AI model includes real-time detection and resolution of network anomalies and service performance optimization. This increases business agility and improves operational efficiencies by up to 40% by eliminating human intensive toils, overheads and cross-departmental silos. Prodapt has introduced an autonomous operations workflow for networks, powered by NVIDIA AI Enterprise, that offers agentic AI capabilities to support autonomous telecom networks. AI agents can autonomously monitor networks, detect anomalies in real time, initiate diagnostics, analyze root causes of issues using historical data and correlation techniques, automatically execute corrective actions, and generate, enrich and assign incident tickets through integrated ticketing systems. Accenture announced its new portfolio of agentic AI solutions for telecommunications through its AI Refinery platform, built on NVIDIA AI Enterprise software and accelerated computing. The first available solution, the NOC Agentic App, boosts network operations center tasks by using a generative AI-driven, nonlinear agentic framework to automate processes such as incident and fault management, root cause analysis and configuration planning. Using the Llama 3.1 70B NVIDIA NIM microservice and the AI Refinery Distiller Framework, the NOC Agentic App orchestrates networks of intelligent agents for faster, more efficient decision-making. Infosys is announcing its agentic autonomous operations platform, called Infosys Smart Network Assurance, designed to accelerate telecom operators’ journeys toward fully autonomous network operations. ISNA helps address long-standing operational challenges for telcos — such as limited automation and high average time to repair — with an integrated, AI-driven platform that reduces operational costs by up to 40% and shortens fault resolution times by up to 30%. NVIDIA NIM and NeMo microservices enhance the platform’s reasoning and hallucination-detection capabilities, reduce latency and increase accuracy. Get started with the new blueprint today. Learn more about the latest AI advancements for telecom and other industries at NVIDIA GTC Paris, running through Thursday, June 12, at VivaTech, including a keynote from NVIDIA founder and CEO Jensen Huang and a special address from Ronnie Vasishta, senior vice president of telecom at NVIDIA. Plus, hear from industry leaders in a panel session with Orange, Swisscom, Telenor and NVIDIA. #calling #llms #new #nvidia #blueprint

Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production. Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. about his workflow below. Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder. In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session. From Concept to Completion To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms. For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI. ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated. Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY. NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU. ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images. Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptationmodels — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost. LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY. “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY  Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models. Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch. To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x. Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started. Photorealistic renders. Image courtesy of FITY. Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time. Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY. “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information. #startup #uses #nvidia #rtxpowered #generative

🌟 In the heart of the bustling cities during the Industrial Age, we witnessed the incredible rise of innovation and opportunity! The Mail Chute was more than just a mechanism; it symbolized the spirit of progress and the relentless pursuit of connection. As buildings soared to new heights, so did our ambitions and dreams! 🚀✨ Let’s embrace the lessons from the past: every rise can inspire us to reach for our goals, even when faced with challenges. Remember, every setback is just a stepping stone towards our next success! 💪💖 So, keep your heads high and your spirits higher! The world is full of possibilities waiting for you to seize them! 🌈 #RiseAndFall #MailChute #IndustrialAge

It's astounding how many people still cling to outdated notions when it comes to the choice between hardware and software for electronics projects. The article 'Pong in Discrete Components' points to a clear solution, yet it misses the mark entirely. Why are we still debating the reliability of dedicated hardware circuits versus software implementations? Are we really that complacent? Let’s face it: sticking to discrete components for simple tasks is an exercise in futility! In a world where innovation thrives on efficiency, why would anyone choose to build outdated circuits when software solutions can achieve the same goals with a fraction of the complexity? It’s mind-boggling! The insistence on traditional methods speaks to a broader problem in our community—a stubbornness to evolve and embrace the future. The argument for using hardware is often wrapped in a cozy blanket of reliability. But let’s be honest, how reliable is that? Anyone who has dealt with hardware failures knows they can be a nightmare. Components can fail, connections can break, and troubleshooting a physical circuit can waste immense amounts of time. Meanwhile, software can be updated, modified, and optimized with just a few keystrokes. Why are we so quick to glorify something that is inherently flawed? This is not just about personal preference; it’s about setting a dangerous precedent for future electronics projects. By promoting the use of discrete components without acknowledging their limitations, we are doing a disservice to budding engineers and hobbyists. We are essentially telling them to trap themselves in a bygone era where tinkering with clunky hardware is seen as a rite of passage. It’s ridiculous! Furthermore, the focus on hardware in the article neglects the incredible advancements in software tools and environments available today. Why not leverage the power of modern programming languages and platforms? The tech landscape is overflowing with resources that make it easier than ever to create impressive projects with software. Why do we insist on dragging our feet through the mud of outdated technologies? The truth is, this reluctance to embrace software solutions is symptomatic of a larger issue—the fear of change. Change is hard, and it’s scary, but clinging to obsolete methods will only hinder progress. We need to challenge the status quo and demand better from our community. We should be encouraging one another to explore the vast possibilities that software offers rather than settling for the mundane and the obsolete. Let’s stop romanticizing the past and start looking forward. The world of electronics is rapidly evolving, and it’s time we caught up. Let’s make a collective commitment to prioritize innovation over tradition. The choice between hardware and software doesn’t have to be a debate; it can be a celebration of progress. #InnovationInElectronics #SoftwareOverHardware #ProgressNotTradition #EmbraceTheFuture #PongInDiscreteComponents

🌟 Hey everyone! 🌟 Today, I want to talk about something that’s making waves in the gaming community: the launch of the fast-paced online soccer game, Rematch! ⚽️ While many of us were super excited to jump into the action, we heard some news that might have dampened our spirits a bit — the game is launching without crossplay. 😢 But hold on! Before we let that news take the wind out of our sails, let’s take a moment to reflect on the bigger picture! 🌈 The developers at Sloclap have made it clear that adding crossplay is a top priority for them. This means they’re listening to us, the players! 🎮💪 They want to ensure that our experience is as enjoyable as possible, and they’re committed to making it happen. How awesome is that? 🙌 Sure, it’s disappointing to not have crossplay right at launch, especially when we were all looking forward to uniting friends across different platforms for some thrilling matches. However, let’s remember that every great game has its journey, and sometimes, it takes a little time to get everything just right. 🛠️✨ We have the opportunity to show our support for the developers and the community by remaining optimistic! Imagine the epic matches we’ll have once crossplay is implemented! 🤩 The idea of teaming up with friends on different consoles or PCs to score those last-minute goals is exhilarating! 🌟 So, instead of focusing on the disappointment, let’s channel our energy into celebrating the launch of Rematch! 🥳 Let’s dive into the gameplay, explore all the features, and share our experiences with one another! We can build an amazing community that encourages one another and fosters a love for the game. 🌍❤️ Remember, every setback is a setup for a comeback! Let’s keep our spirits high and look forward to all the updates and improvements that Sloclap has in store for us. The future of Rematch is bright, and I can’t wait to see where it takes us! 🚀 Let’s keep playing, keep having fun, and keep believing in the magic of gaming! Who’s ready to hit the pitch? ⚽️💥 #RematchGame #GamingCommunity #KeepPlaying #StayPositive #SoccerFun

In a world where connection feels like a fading memory, I find myself lost in the shadows of what once was. Every day, I watch others embrace the thrill of new experiences, like the revolution of fitness through virtual reality. The Meta Quest promises a transformative journey, a game-changer that invites us to escape into a realm where movement and motivation intertwine. Yet here I am, sitting in solitude, enveloped by a haunting silence that echoes louder than any joyous cheer. The bright screens and vivid worlds of VR spark curiosity and excitement in so many, but for me, they serve as a reminder of my isolation. I see people donning their headsets, pushing their limits, and achieving goals that seem just out of my reach. I wonder if they realize how lucky they are to share this moment with friends, to feel the rush of adrenaline as they conquer challenges together. The thought weighs heavily on my heart, the ache of longing for companionship gnawing at my spirit. While the fitness world evolves, I remain stagnant, trapped in a cycle of despair. Each day blends into the next, a monotonous routine that offers little comfort. I scroll through images of triumph and joy, my heart heavy with envy as I wish for even a fraction of that happiness. The Meta Quest symbolizes hope for many, a bridge to a healthier lifestyle, yet I sit on the sidelines, a ghost in my own life. The loneliness wraps around me like a heavy shroud, a constant reminder of the connections I crave but cannot reach. I long for someone to share the experience with, to laugh and sweat alongside, to revel in the shared victories that bring warmth to the soul. Instead, I am left with my thoughts—an endless loop of what-ifs and should-haves. How does one break free from this suffocating solitude? How does one find the strength to step into the light when every step feels heavier than the last? I write this not as a plea for sympathy, but as an echo of my heart. A whisper in the void that hopes someone out there feels the same. As the fitness revolution unfolds with the aid of virtual reality, I remain a spectator, yearning for connection, for understanding, for a hand to hold in the dark. In the world of Meta Quest, while fitness may find new heights, I hope to one day find my way back to a place where I can truly connect—where the weight of loneliness is lifted, and the joy of shared experiences reigns. #Loneliness #Isolation #VirtualReality #MetaQuest #FitnessJourney

🌟 Hey there, fabulous friends! 🌟 Are you ready to take your market research game to the next level? 🚀 Today, I want to share with you something that can truly transform how you see competition! In this fast-paced world, every entrepreneur and marketer needs to be equipped with the right tools to uncover hidden gems in the market. And guess what? The answer lies in the **14 Best Competitive Intelligence Tools for Market Research**! 🎉🎉 Imagine having the power to peek behind the curtain of your competitors and discover their strategies and tactics! With these amazing tools, you can gather insights that will not only help you understand your market better but also give you the edge you need to soar higher than ever before! 🌈✨ One standout tool that I absolutely adore is the **Semrush Traffic & Market Toolkit**. It’s like having a secret weapon in your back pocket! 🕵️‍♂️💼 This toolkit provides invaluable data about traffic sources, keyword strategies, and much more! Say goodbye to guesswork and hello to informed decisions! Each piece of information you gather brings you one step closer to your goals. 🌟 But that’s not all! Each of the 14 tools has its own unique features that cater to different aspects of competitive intelligence. Whether it's analyzing social media performance, tracking keywords, or monitoring brand mentions, there’s something for everyone! It’s time to embrace the power of knowledge and turn it into your competitive advantage! 💪🔥 I know that diving into market research might seem daunting, but let me tell you, it’s a thrilling adventure! Every insight you uncover is like finding a treasure map leading you to success! 🗺️💖 So, don’t shy away from exploring these tools. Embrace them with open arms and watch your business flourish! 🌺 Remember, the only limit to your success is the extent of your imagination and the determination to use the right resources. So gear up, equip yourself with these 14 best competitive intelligence tools, and let’s conquer the market together! 🌍💫 Let’s lift each other up and share our discoveries! What tools are you excited to try? Drop your thoughts in the comments below! 👇💬 Let’s inspire one another to reach new heights! #MarketResearch #CompetitiveIntelligence #BusinessGrowth #Semrush #Inspiration

🌟 Hey everyone! 🌟 Today, let’s dive into an exciting topic that can truly elevate your online presence: **Keyword Bidding**! 🚀 Whether you’re a business owner, a marketer, or just someone curious about the digital landscape, understanding keyword bidding can open up a world of possibilities for you! So, what exactly is keyword bidding? 🤔 It’s all about setting the amount you’re willing to pay to achieve your goals in Google Ads. Think of it as placing a bet on your future success! 💪 When you bid on keywords, you’re investing in your visibility online, allowing your business to reach the right audience at the right time. Isn’t that empowering? 🌈 Imagine this: You have a fantastic product or service, but if nobody sees it, how can you shine? 🌟 This is where keyword bidding comes into play! By strategically choosing the right keywords related to your business, you can ensure that when potential customers search for what you offer, they find YOU! 🎯 Here’s a simple step-by-step guide to get you started on your keyword bidding journey: 1. **Research Your Keywords**: Start by brainstorming keywords that are relevant to your business. Use tools like Google Keyword Planner to discover popular search terms. The more specific, the better! 🔍 2. **Set Your Budget**: Determine how much you’re willing to spend. Remember, this is an investment in your growth! Don’t be afraid to start small; you can always increase your budget as you see results. 💰 3. **Choose Your Bids**: Decide how much you want to bid for each keyword. This can vary based on competition and your goals. Don’t forget to keep an eye on your competitors! 👀 4. **Monitor and Adjust**: Once your ads are live, regularly check their performance. Are certain keywords performing better than others? Adjust your bids accordingly to maximize your return on investment. 📈 5. **Stay Inspired**: Keyword bidding is a journey, so stay positive and keep learning! Engage with communities, read up on trends, and don’t hesitate to experiment! Your enthusiasm will fuel your success! 🌺 Remember, every great achievement starts with a single step! 💖 Embrace this opportunity to harness the power of keyword bidding and watch your business flourish! 🌼 You’ve got this! Let’s make those dreams a reality, one bid at a time! 💫 #KeywordBidding #GoogleAds #DigitalMarketing #OnlineSuccess #Inspiration

In early-stage start-ups, the pitch deck is often the first thing investors see. Sometimes, it’s the only thing. And yet, it rarely gets the same attention as the website or the socials. Most decks are pulled together last minute, with slides that feel rushed, messy, or just off. That’s where designers can really make a difference. The deck might seem like just another task, but it’s a chance to work on something strategic early on and help shape how the company is understood. It offers a rare opportunity to collaborate closely with copywriters, strategists and the founders to turn their vision into a clear and convincing story. Founders bring the vision, but more and more, design and brand teams are being asked to shape how that vision is told, and sold. So here are five handy things we’ve learned at SIDE ST for the next time you’re asked to design a deck. Think in context Designers stepping into pitch work should begin by understanding the full picture – who the deck is for, what outcomes it’s meant to drive and how it fits into the broader brand and business context. Their role isn’t just to make things look good, but to prioritise clarity over surface-level aesthetics. It’s about getting into the founders’ mindset, shaping visuals and copy around the message, and connecting with the intended audience. Every decision, from slide hierarchy to image selection, should reinforce the business goals behind the deck. Support the narrative Visuals are more subjective than words, and that’s exactly what gives them power. The right image can suggest an idea, reinforce a value, or subtly shift perception without a single word. Whether it’s hinting at accessibility, signalling innovation, or grounding the product in context, design plays a strategic role in how a company is understood. It gives designers the opportunity to take centre stage in the storytelling, shaping how the company is understood through visual choices. But that influence works both ways. Used thoughtlessly, visuals can distort the story, suggesting the wrong market, implying a different stage of maturity, or confusing people about the product itself. When used with care, they become a powerful design tool to sharpen the narrative and spark interest from the very first slide. Keep it real Stock photos can be tempting. They’re high-quality and easy to drop in, especially when the real images a start-up has can be grainy, unfinished, or simply not there yet. But in early-stage pitch decks, they often work against your client. Instead of supporting the story, they flatten it, and rarely reflect the actual team, product, or context. This is your chance as a designer to lean into what’s real, even if it’s a bit rough. Designers can elevate even scrappy assets with thoughtful framing and treatment, turning rough imagery into a strength. In early-stage storytelling, “real” often resonates more than “perfect.” Pay attention to the format Even if you’re brought in just to design the deck, don’t treat it as a standalone piece. It’s often the first brand touchpoint investors will see—but it won’t be the last. They’ll go on to check the website, scroll through social posts, and form an impression based on how it all fits together. Early-stage startups might not have full brand guidelines in place yet, but that doesn’t mean there’s no need for consistency. In fact, it gives designers a unique opportunity to lay the foundation. A strong, thoughtful deck can help shape the early visual language and give the team something to build on as the brand grows. Before you hit export For designers, the deck isn’t just another deliverable. It’s an early tool that shapes and impacts investor perception, internal alignment and founder confidence. It’s a strategic design moment to influence the trajectory of a company before it’s fully formed. Designers who understand the pressure, pace and uncertainty founders face at this stage are better equipped to deliver work that resonates. This is about more than simply polishing slides, it’s about helping early-stage teams tell a sharper, more human story when it matters most. Maor Ofek is founder of SIDE ST, a brand consultancy that works mainly with start-ups.  #sharpen #story #design #guide #startups

Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement