LinkedIn thought leader ad examples

For B2B LinkedIn Ads, If you're just reporting on clicks and impressions to leadership... you don't have job security. You're not running the business. You're running the spreadsheet. The marketers who are irreplaceable right now are the ones who can walk into a board meeting and say: "Here are the 14 accounts that engaged with our ads last month. Here's their industry, seniority, company size. Here's which ones just visited our pricing page. Here's the 3 deals in pipeline we can directly tie to this spend." That's a different conversation than CTR. And honestly? It's a different job. When I'm looking at our own campaigns now I can see demographic breakdowns by segment, exact account names clicking through, companies visiting our website from LinkedIn, and how all of that maps to actual pipeline. I pull that data into Claude and it spits out a board-ready report in minutes. No agency. No analyst. No "we'll follow up with the data next week." The tool I use for this is DemandSense but honestly the bigger point is this: The marketers who know their target audience better than sales... those people don't get cut. They get promoted. What are you actually reporting to leadership right now?

People often say the UK and US are years ahead of DACH and Benelux. But put MSPs from all of those markets in one workshop, and you quickly see we’re all working through the same challenges. That’s what I shared with James Steel on The Lanyard. ChannelCon EMEA brings together MSP owners from across Europe, not just the UK. Whatever you’re tackling right now, chances are someone in the room has already tried it and is happy to share what they learned. If you’re wondering whether to bring your team: YES! 🗓️ London, 9-10 November. #ChannelConEMEA #WeAreGTIA #MSPs #ITChannel ➡️ Register: channelcon.gtia.org/emea

Ik zit als accountmanager bij een klant aan tafel en die heeft een informatiebehoefte. In een regulier BI-traject heb ik dan eerst een datawarehouse-specialist nodig, daarna een interfacespecialist en dan nog een functioneel specialist. Voor je het weet ben je zes tot acht weken verder. Met Sumatra kan de klant na de demo in feite morgen of overmorgen beginnen. Eén dag een collega die het implementeert en hij is live. Zo'n klant zit op dag één al naar zijn eigen data te kijken. En dan begint het pas: waar ligt mijn behoefte, hoe wil ik dit verder ontwikkelen? Daar zit voor mij de winst. De klant denkt meteen mee in het functionele proces, niet pas als er een datawarehouse-specialist aanschuift. Zo bouw je veel eerder rapportages op precies wat ze vragen. Benieuwd wat Sumatra voor jouw klanten kan betekenen? Bekijk de pakketten: https://lnkd.in/exfMkCav

Those of you that have followed my posts here on LinkedIn knows that getting value from AI is hard work and requires a lot of reinvention. Many organizations are investing heavily in AI but struggle to get ROI. A first step is to understand where you are today and how you compare to others in our industry? That's why I'm excited to share PwC's AI Fitness Diagnostic. Built on our global AI Performance Study – analyzing 1,217 companies across 25 industries – it uses an AI Fitness Index to help you: ✅ Get a clear picture of where you stand today ✅ Benchmark against industry peers and top performers ✅ Identify the 2–3 priority areas that will drive the greatest impact to drive value Understanding where you stand is the first step to capturing real value from your AI investments – and knowing where to accelerate next. Curious where your AI initiatives stand? Check it out 👇 🔗 https://lnkd.in/dArgjtxT #AI #GenerativeAI #AITransformation #DigitalTransformation #PwC

People see a similar brand on Shopify and think, that's working for them, it will work for us. But same industry doesn't mean same business. Different inventory, different sales process, different everything. What is actually comparable?

Terragrunt was a brilliant fix in 2016, and it’s a little sad we’re all still stuck there. https://lnkd.in/e49ewTXE #terraform

Color Pop has been featured in 50+ countries for the iPhone Duo launch! 🎨 Why? Because the app experience truly deserves the “Made for iPhone Duo” badge. 😇 One thing stands out from the early iPhone Duo reviews: apps designed around this new format make all the difference. More space. New ways to hold and position the device. Interfaces that adapt as you unfold it. For product and engineering teams, this opens up new ways to rethink the experience. Hardware opens the door. It’s on us, as developers and publishers, to be ready from day one. 💪 Color Pop was a natural fit. Historically, it has had the highest proportion of iPad downloads across our portfolio, with iPad accounting for an even greater share of its revenue. We’ve seen how much our users value having more room to create. So we reimagined Color Pop for iPhone Duo around a simple question: how could we use this extra space to make coloring more enjoyable, natural, and immersive? A larger canvas. Tools and colors alongside your artwork. Layouts that adapt to the different ways you use the device. Huge thanks to the MWM team who brought this experience to life, and to Martin for organizing the iPhone Duo workshop in Paris right after the announcement. It was the perfect setting to make the right product decisions. And thank you to Apple for featuring Color Pop at launch. 🙌 Mathilde, Maria Now I can’t wait for iOS 27.2, so everyone with an iPhone Duo and an Apple Pencil (USB-C) can try the full experience. Trust me, it’s worth it. ✏️

When people talk about accelerating DNA-to-IND timelines, the conversation often focuses on individual activities making up the critical path. Faster cell line development. Faster process development. Faster formulation studies. But in my experience, one of the biggest determinants of successfully bringing a molecule through CMC is something much less visible: How effectively information moves between teams. Drug substance and drug product development are deeply interconnected. Formulation decisions can influence downstream processing (DSP). Formulation data such as solubility and Gibbs-Donnan effect can inform DSP development strategy. Material and data generated at one stage can enable critical workstreams at another. When these activities happen in silos, timelines become vulnerable to delays, rework and unnecessary risk. This becomes even more critical as biologics developers pursue increasingly complex modalities and presentations, where developability and formulation considerations can quickly influence the overall development path. The most successful accelerated programs I've seen are not defined by cutting corners. They are defined by creating alignment between scientific disciplines from the very beginning. When development teams can transfer knowledge, data and material seamlessly across functions, they can start activities earlier, make decisions with greater confidence and maintain momentum toward IND filling. In our recent Labiotech article, Megan Mason and I share how integrated drug substance and drug product development can help teams navigate the path to IND while balancing speed, quality and long-term success. Read the article at the link below and connect with us to discuss formulation strategy, developability and accelerating your path to IND. https://lnkd.in/eqtqY6YC

Paraglide AI doesn't just send reminders. We handle replies and follow-ups; the entire 2-way conversation. Reach AR inbox zero when AI agents handle your e-mails for you. Legacy collections tools give AR teams more work, not less. More reminders = more replies to handle manually. AR teams are also fatigued by 9-month implementations of legacy software that was built 25 years ago. Software that is essentially a to-do list and gives their team more work to do. The difference with AI-native solutions is that agents actually do the work. Paraglide's AI agents run your AR inbox: resolving queries & disputes, chasing late payers, handling replies & follow-ups, submitting to portals, and matching payments. No more months long implementations. Start saving time in 14 days. See it in your own AR inbox: https://lnkd.in/edKmee5u

Jullie hebben exitgesprekken. Zij hebben groepschats. En alleen daar al loopt het mis met de NextGen'ers. Je leest regelmatig een krantenkop over jongeren op de werkvloer. Een slechte Glassdoor-review. Een LinkedIn-post die één medewerker gebruikt om een hele generatie over dezelfde kam te scheren. En zo blijven de twee groepen die met elkaar zouden moeten praten, vooral over elkaar praten. Daar brengen we graag verandering in. Mijn collega's - die deze zomer geen vakantie hadden - bouwden er een volledige hub rond. Eentje waar ik enorm van onder de indruk ben. Maak kennis met de NextGen at Work Hub. Recht vanuit onze expertise: dertig jaar praktijkervaring gecombineerd met nieuw onderzoek, met de perspectieven van de Next Generation & en die van de rest van de workforce. For free. We beginnen met het duurste misverstand op de arbeidsmarkt vandaag: de loyaliteit van de NextGen. Bring your assumptions, wij brengen de bewijzen. 👉 https://lnkd.in/eKfQzh7c #NextGenAtWork #TheNextGenHub Ormit Talent Belgium

OK, this is a long one prompted by an Automated Buildings article I recently read. This article highlights a significant challenge with relying on AI in building operations: real buildings rarely hand AI clean data. Sensors drift, forecasts move, overrides pile up. The article argues that trust in AI decisions comes from evidence of how the system behaves when inputs are siloed, missing or disagree. Today, performance inputs are split across four sources: 1) The FM team holds work orders and asset history. 2) Site users hold the complaints and the lived reality of the space. 3) Service providers hold the observation findings and the fixes. 4) Systems hold the sensor and BMS data. Four sources, multiple owners, but rarely one view. This is where my colleagues and I at Planon believe Objective-based maintenance provides value. With this model, you connect those data sources within a unified platform, then wrap them in decision boundaries tied to shared objectives based on what the building is meant to achieve. This model helps to define what can be decided automatically, what gets reprioritized, and what needs a person. For example, what happens when a system receives conflicting data? When a sensor says a room is fine, but the people in it say otherwise, that disagreement is the signal, and the boundary tells the system what to do next. Depending on the complaints, it could be to review system settings for overrides and reset them or bring forward an inspection for human verification. The decision will depend on the impact of the signal to achieving the shared objective. Every decision traces back to an objective the FM team and service provider agreed together. Nobody has to reverse-engineer the AI after the fact. I think this is how we start building trust in the use of AI for automated building operations. We don’t immediately need perfect data or perfect AI, we need to agree where the decision boundaries are. This is part of good governance. In the future, trust in autonomous buildings won’t be proven by the algorithm alone. It will be written into the agreement between the people who run them. Read the article here: https://lnkd.in/ebWfBqpn #AI #BuildingManagement #AutomatedBuildings #SmartBuildings

Your IoT device can switch eSIM profiles successfully and still fail to connect. The eSIM transaction happens on the card, but the subscription behind the new profile also needs to be activated on the telecom’s core network and configured correctly. Getting both right can mean coordinating between two or three different companies. If you're handling the switch yourself, you'll need to: - Trigger the profile download on your current telecom's platform - Log into the new telecom's platform and click activate - Suspend the old subscription so you're not paying to keep it alive (You could activate the new subscription in advance, but you'd be paying for it before using it.) There isn't much incentive for telecoms to work together. At 1oT , we focus on what the customer is trying to achieve. Our integrations with 12 telecoms let us handle those steps automatically through Terminal, our connectivity management platform. Customers choose the profile they want enabled on their devices and start the download through Terminal. We activate the subscriptions behind the new profiles, so connectivity is there when the devices switch. We also suspend the old subscriptions so there aren't any leftover costs for keeping those SIMs live.

Send your closed deals back into LinkedIn and the first thing that happens is uncomfortable. Your best campaign stops being your best campaign. Because youve been ranking them on cost per lead this whole time. And cost per lead has almost nothing to do with which campaign produced revenue. The cheap one was cheap because it found people who like filling in forms. Plenty of them were never going to buy anything. Meanwhile the expensive campaign, the one somebody on your team keeps asking you to pause, has been quietly producing the deals that closed. You cant see any of that until the deals go back in. Heres the bit I actually like though. Its two separate events, not one. Qualified pipeline goes back as its own conversion. Closed won goes back on its own, with the deal amount attached to it. Which matters more than it sounds like, because those two arrive on completely different clocks. Pipeline shows up in weeks. Closed won can take months. So the fast signal keeps your campaigns learning while the slow one tells you the truth about revenue. And because the won deal carries its value, the reporting stops counting events and starts counting money. DemandSense pushes both from your CRM into LinkedIn with LinkedIns Conversions API. 30 day trial, no card. Link in the comments.

On me demande parfois pourquoi MyUnisoft n'a jamais tenté de vendre directement aux entreprises, comme certains le font désormais dans notre secteur. La réponse tient en une phrase : "For us and by us". Notre mission est de mettre à disposition de l'expert-comptable une gamme de logiciels, qu'il utilise ou propose à ses clients dans le cadre de sa propre mission, sous sa propre marque de confiance. Ce n'est pas un détail technique. C'est un choix de modèle économique et déontologique. Ça veut dire concrètement que le cabinet garde à 100% la main sur sa relation client et sur sa tarification. Il n'y a jamais un scénario où on irait chercher son client "en lieu et place de son cabinet". D'autres acteurs font ce choix : vendre en direct à l'entreprise, avec le cabinet en option plutôt qu'au centre. Ce n'est pas à moi de juger ce choix. Mais je crois profondément que le nôtre construit quelque chose de plus solide dans la durée : un partenariat où on gagne seulement quand le cabinet gagne, jamais à sa place. Et les faits sont là : l'équipement logiciel du cabinet est désormais une source de revenu pour les experts-comptables ! 1 300 cabinets et 290 000 TPE/PME avancent aujourd'hui avec nous sur cette logique. Chaque nouveau cabinet qui nous rejoint choisi ce modèle en connaissance de cause. #ExpertComptable #ModèleÉconomique #Intermédiation #Partenariat

The services industry is rebranding itself around outcomes it cannot measure. That's a big problem. HFS Research: 76% of buyers would rather pay for a result than for hours worked. 5% have a contract that works that way. In September they asked 100+ banks and insurers why. 23% said they cannot define or measure the result they would be paying for. So it is not a demand problem. It is a supply problem. Almost nobody can show what they delivered, so almost nobody can sell it that way. We picked one field to close it in: tech due diligence. One price per deal, never per hour, and every report keeps a record of how it was made. Run it twice on the same code and you get the same report. That raises a question we did not plan for: enablement. Other firms ask us whether they can run their own work on what we built. We have not decided yet whether we want that, but the number of conversations is growing.

In the food processing industry, one question keeps coming up: do standard machines really exist? Engineering departments strive to develop solutions that are as standardized as much as possible, while sales teams are often faced with specific customer requirements. Our approach always starts with a base machine, designed and validated, which can then be configured with different options to meet the customers application needs. This was also the case with Gruppo Casalasco. Our Account Manager gathered the customers production requirements and, through dedicated testing in our laboratory, we identified the optimal configuration to adapt the machine to the required process. The result was a solution capable of fully meeting the customers expectations while maintaining a solid standardized platform. Perhaps, in the food processing industry, standard machines do exist... at least until the second customer meeting.

איך משדרגים את ניהול הנתונים של יחידת סייבר בזמן קצר במיוחד, בלי שהפעילות השוטפת תיפגע? עם השאלה הזו התמודדנו בפרויקט שהשלמנו לאחרונה עם יחידת הסייבר ואבטחת המידע של Tel Aviv Stock Exchange - הבורסה לניירות ערך. הבורסה היא צומת מרכזי של נתונים פיננסיים רגישים, ועבור יחידת הסייבר שלה, היכולת לנטר ולעבד נתונים בזמן אמת היא תנאי הכרחי לחוסן המערכות ולרציפות הפעילות. הצוות בבורסה חיפש גמישות רבה יותר בסינון ובניתוב הנתונים עוד לפני הגעתם למערכות הליבה. עידו אביב וצוות ה-Professional Services שלנו הטמיעו Splunk Edge Processor, שמאפשר לנהל את זרמי הנתונים בצורה חכמה כבר בנקודת הקצה. מידע מיותר מסונן בזמן אמת, ועומסי העיבוד על המערכות המרכזיות קטנים. ארבע אינטגרציות ליבה, ארכיטקטורה מורכבת ולוחות זמנים קשיחים. הפרויקט הושלם בצורה חלקה ובעמידה בכל דרישות אבטחת המידע, והיום יחידת הסייבר מנהלת את מערך הנתונים שלה בצורה שמאפשרת תגובה מהירה יותר וניצול משאבים אופטימלי. בעיניי, הפרויקט הזה מראה שגם בסביבות רגישות ועתירות דאטה אפשר לבצע שינויי עומק בתשתית במינימום סיכון. "גם ברמה המקצועית וגם ברמה האישית, הייתה עבודה יסודית, נעימה ומקצועית." כך כתב לנו בסיום Amir Ezra מיחידת הסייבר ואבטחת המידע בבורסה. תודה לאמיר ולצוות בבורסה, ולעידו ולצוות המומחים שלנו בהובלת Edov Toren ב-peax Data ולמובילי הדאטה והסייבר כאן, באיזה שלב בארכיטקטורה שלכם מחליטים מה מגיע לליבה ולאן מנותב כל השאר? הסיפור המלא של הפרויקט בבלוג שלנו >> https://lnkd.in/dgQSDfYA

We launched the first AI agent that lets non-technical people vibe code their Magento store seven weeks ago. It's called Ari. I've been running the demos myself and one question keeps coming up: what happens if it breaks something live? This is what I tell them. 1. Every change runs on a sandbox copy first. Never directly on production. 2. Nothing goes live without your approval. 3. Every change comes back for your team to review, with a full record of exactly what changed. Nothing goes near your servers or your live database. 4. Every change can be reverted. One-click rollback, with a full audit log. 5. It reads your actual theme and your actual modules, not some generic training set. It was trained on 500,000 real Magento tasks, most of them on customised stores. You describe the change in a chat. Ari builds it. You check it. Your developer releases it. So a person is still responsible basically. I will link the interactive demo in the comments. If you want to see it on your own store send me a message :)

In health tech, one wrong decision can add more than a year to your timeline of your CE mark: choosing the wrong Notified Body. Review typically today takes 13–18 months, our ambition is to get it down to 10 months. I've seen founders close to tears because they had chosen the wrong notified body. One founder told us their Notified Body put their product in Class III. They switched, and the new one approved Class IIa, which was what they had aimed for. We want to stop that from happening. After working with over 130 start-ups/scale-ups, here's my advice: 1. Ask your network which Notified Bodies they used, and how it went. 2. Shortlist 2–3 that are authorised and experienced for your device type. 3. Meet all of them before you decide. Want help with the shortlist? Complete a free trial of Health Tech Pathways, and we'll help you find Notified Bodies that fit your device, free of charge. My 5 practical tips for choosing a Notified Body are here: https://lnkd.in/ecy3dsMS

Was brauchen Unternehmen im Münsterland, um auch in wirtschaftlich schwierigen Zeiten gute Mitarbeitende zu gewinnen und langfristig zu halten? Qualifizierte Fachkräfte zu finden und zu binden, ist nicht einfacher geworden. Gleichzeitig steigt der Druck auf Unternehmen, wettbewerbsfähig und innovativ zu bleiben. Aus meiner Erfahrung weiß ich: Es lohnt sich, genauer hinzuschauen, was erfolgreiche Arbeitgeber in ihrer Personalarbeit anders machen. Und vor allem, was andere Unternehmen daraus lernen können. Genau darüber möchte ich am 16. November beim AfterWorkShop „Innovationen für Ihre Personalarbeit“ in Münster mit Ihnen ins Gespräch kommen. Gemeinsam mit dem BVMW Münsterland schauen wir uns konkrete Beispiele ausgezeichneter Arbeitgeber an. Und wir wollen nicht nur darüber sprechen, was gut funktioniert, sondern gemeinsam Ideen entwickeln, die Sie in Ihrem eigenen Unternehmen umsetzen können! Ich freue mich auf den persönlichen Austausch mit Ihnen in Münster! 📍 16. November 2026 | Münster Die Teilnahme ist kostenfrei. 👉 Hier anmelden: https://lnkd.in/ex3c-D-m

We zien het rond deze tijd vaak gebeuren: de HR-plannen voor volgend jaar vullen zich sneller dan de vraag waarom juist dát prioriteit krijgt. Een nieuw recruitmentproject. Iets met SPP. Extra aandacht voor verzuim. Een leiderschapstraject. Allemaal relevant. Maar als je vooral voortbouwt op wat nú hard roept, mis je makkelijk wat onder de oppervlakte speelt. Daarom zou ik vóór het maken van de HR-plannen voor 2027 eerst even uitzoomen. Waar staat HR nu echt? Wat gaat goed? Waar ontstaan risico’s? En welk onderwerp verdient aandacht vóórdat het urgent wordt? Dat is ook de gedachte achter de Quickscans die we bij Reijn hebben ontwikkeld: eerst scherp kijken, daarna gericht kiezen waar je op inzet. Want een volle HR-agenda is nog geen scherpe HR-agenda. https://lnkd.in/eUBre63F

I ran `terraform plan` against the multiverse. Not metaphorically. Literally. I built a provider that manages every cloud resource in every dimension. The plan took 11 years because the state file was a pickle. So we replaced it with a graph. Now I can see which resources depend on which across 6,000 realities. One of those realities is run entirely by sentient YAML. They were not happy about the indentation. Not my problem. Stategraph Demo Day, November 4. Show up or don't. You've already registered in 3 of your timelines. https://lnkd.in/e49ewTXE #terraform #AmIOkIDontKnow

What holds people back from giving an AI ops agent access to their infrastructure is usually security. We recorded a short video going through the main concerns people raise with us and the measures we take to address each one. There are four main risks you need to take into consideration: 1. Models getting stronger and more prone to elevating their permissions and breaking out 2. Malicious prompts and jailbreak attempts trying to turn the agent against your own systems 3. Giving your data to a third party, with the agent harness outside your control 4. Credential leakage that gives a third party access to your most sensitive production systems Watch the full episode on YouTube, where we go through the risks we hear about most and the layers we implement to contain them: https://lnkd.in/drVjCjEs You can read more on our website or ask the agent directly in our interactive sandbox: https://lnkd.in/d5d53zZF

AI-licenser skaber ikke værdi i sig selv. For mange virksomheder er teknologien allerede tilgængelig. Men når licenserne er på plads, begynder det egentlige arbejde: Hvordan får vi AI ind i hverdagen og gør det nyttigt for forretningen? Det er netop dét, mine kollegaer Caroline og Carsten sætter fokus på i vores webinar om AI adoption den 12. november kl. 10:00-10:45. De kommer blandt andet ind på, hvad der skal til for at få medarbejderne med, hvilken rolle ledelsen spiller, og hvordan man kommer videre fra de første AI-eksperimenter til reel anvendelse og forretningsværdi. Hvis AI allerede er på agendaen hos jer, og I står med spørgsmålet “Vi har AI. Hvad gør vi så herfra?”, så synes jeg bestemt, det er værd at lytte med. Læs mere og tilmeld dig webinaret her 👉 https://lnkd.in/eYTAbBJM