B2B ad examples

"The experience was seamless" Check out how we saved Koalafi 33% on their Snowflake bill, seamlessly👇 https://lnkd.in/eyrHyunv

Starbucks' $29.95 bear-shaped #Bearista cup sold out nationwide in hours – sparking overnight lines, customer brawls, and eBay listings of up to $50,000. But did the viral frenzy translate to real sales? 🐻 Our transaction data says…definitely. 📊 The Numbers: Launch day: +50.4% transactions YoY, $74.7M in spend Two weeks: $64M incremental revenue, 5M additional transactions YoY Sustained impact: Week 1 (+$53M), Week 2 (+$11M) So…why did it work? - Genuinely desirable (Instagram-worthy 'collectible') - Authentic scarcity (real demand, not manufactured) - Social currency (status symbol) - Perfect timing (holiday season) Now – two weeks later, Starbucks just launched a Target-exclusive Frozen Peppermint Hot Chocolate across 2,000 locations. The goal: drive Target foot traffic through beverage ‘exclusivity’. The problem? This collaboration lacks the Bearista's core success factors: - Commodity seasonal flavor (not distinctive) - False scarcity (widely available) - Distribution play vs. true demand creation Two struggling retailers partnering doesn't create new demand – especially if they share the same declining customer base. What’s the lesson? Exclusivity alone doesn't drive results. The Bearista created genuine desire through authentic scarcity and content virality. The Target drink redistributes existing demand – and likely creates minimal new. Real demand creation shows up in the data immediately: +50% transaction growth and $64M in incremental revenue . Distribution plays generate buzz but probably won't move the needle meaningfully – but time (and the data) will tell 👀 #Starbucks #Target #ExclusiveOffer #ConsumerData #ShoppingBehavior #Bearista #HolidaySpending Check out our full take on this in our newest blog 👇

🔄 Incrementally Incremental Computation Incremental View Maintenance has always felt a bit sci-fi to me: a record changes in a SQL table, and the system instantly ripples that update through hundreds of SQL operators, refreshing every affected view. But what if not just the data could change incrementally… but the queries themselves? Traditionally, modifying queries meant throwing away all prior computation and starting from scratch. Not anymore. Feldera now supports incremental query modifications. This is an incredibly powerful capability. You can make arbitrary changes to your program — add, delete, or modify views — even if other views depend on them. Feldera will: 🔍 Identify all affected views ♻️ Discard any state invalidated by the modification, while preserving all other state 🧮 Use existing state in the system to compute new and modified views. The result is that many pipeline reconfigurations can be performed in a fraction of the time it would take to backfill the pipeline from scratch. One of our customers described this as "incrementally incremental computation." What a nice way to summarize a complex feature in three words! Learn more here: https://lnkd.in/gNSZY2j8

Discover the power of FineBI 7.0, FanRuan Software's latest innovation in business intelligence and analytics. AI sits at the core of FineBI 7.0. We’ll showcase the latest AI-powered analytics capabilities and how they streamline decision-making, from asking a question to acting on the answer, while keeping your data and governance under control. Click to learn more.

If your leadership meetings still start with “Wait, why does your number not match mine?”, you’re not alone. Most teams aren’t suffering from a lack of data. They’re suffering from Metrics Chaos, too many definitions, too many versions of the truth, and too little shared context. The latest version of FineBI might be built exactly for that. FineBI 7.0 Metrics Hub is not just a new feature. It’s a shift from “every team has its own version of the truth” to “we share one metrics language across the business.” Click to learn more.

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📈 Automatisez vos plannings, réduisez les erreurs et gagnez en sérénité grâce à une planification RH fiable et conforme avec EURODECISION et IBM.

🔥 Libérez-vous des contraintes de planning : conformité, précision et gain de temps grâce à une solution RH intelligente avec EURODECISION et IBM.

Used by world-class product teams, from early-stage saas to global enterprises. Embeddable does the heavy lifting behind the scenes as your analytics grow. Share your project overview and start your poc today →

Whether you’re scaling your first saas product or operating at enterprise level, embeddable has you covered. We handle the heavy lifting so analytics never slow you down. Share your project overview and start your poc today →

Is your checkout process losing customers due to inaccurate or incomplete addresses? Egon Data Quality offers the ideal solution for your eCommerce checkout, with advanced address validation and geocoding. ✔ Reduce delivery errors ✔ Enhance customer satisfaction ✔ Boost conversion rates Integrate Egon and make every address count.

Egon Data Quality integrates effortlessly into any CRM, offering: Real-Time Address Cleansing – Instantly validate and enrich addresses. Autocomplete & Error Correction – Simplify data entry. Batch Address Validation – Verify entire databases in minutes. Geocoding & Mapping – Compatible with top mapping services. Easy REST API Integration – Get started quickly and seamlessly. Enhance your CRM with precise address validation and geocoding today!

It’s time to rethink your data platform The architecture you rely on today may not be ready for the demands of tomorrow. Modern demands require a unified foundation for cloud scalability, AI enablement, and resilient, governed data flows.

Things evolve. So should your data platform. To keep pace with changing demands, your data foundation needs to be flexible, scalable, and built for real-time insights, AI readiness, and smarter decisions. Epical helps you modernize your platform – making it easier to manage, adapt, and deliver business value over time.

Breng structuur in complexe dataomgevingen. Download gratis onze reference architectures voor moderne dataplatformen.

Wil jij de toekomst van je data-ecosysteem bepalen? FabricCompass helpt je met een no-nonsense whitepaper: van de kern van Microsoft Fabric tot een slim advies voor waardecreatie. Voor strategische denkers die het verschil maken. 🚀https://lnkd.in/ecNrkBaJ

How do you migrate to TcX without disrupting the business? At Realize LIVE Europe 2026, eQ Technologic’s on-demand session, presented by Gareth Webb, Vice President – EMEA Customer Engagements, showcases a proven approach to large-scale PLM migration and modernization. ✔ Legacy Teamcenter to TcX ✔ On-premise to cloud transformation ✔ Scalable architecture for high-volume metadata and files ✔ Enterprise-wide digital thread enablement And the proof? ⚡ Entire migration completed in 3 days using 500 parallel threads. If TcX, cloud transformation, or PLM modernization is on your roadmap, join us at Realize LIVE Europe 2026: 📅 June 29 – July 1, 2026 📍 RAI Amsterdam Convention Centre, Amsterdam, NL 📌 Booth #D24 Discover how eQube®-DaaS helps organizations transform with speed and confidence. https://hubs.la/Q04lQQLt0 #1eQ #eQTechnologic #eQubeDaaS #PLM #DigitalThread #CloudTransformation #RealizeLIVE

Amsterdam, we're coming. The eQ team is heading to Realize LIVE Europe 2026 and we're ready to talk PLM modernization, digital thread, Closed Loop Manufacturing, and Industrial AI. Meet our experts at Booth #D24: 👤 Gareth Webb – Vice President, EMEA Customer Engagements 👤 Alan Walker – Vice President, Strategic Engagements 👤 Martin Michel – Senior Manager, Business Development 📍 Booth #D24 📅 June 29 – July 1, 2026 📍 RAI Amsterdam Convention Centre, Amsterdam, NL Whether you're planning a TcX migration, connecting enterprise systems, or preparing for AI-driven transformation, we'd love to hear about your challenges and goals. Explore what eQ has in store at #RealizeLIVE Europe: https://hubs.la/Q04lyglm0 #1eQ #eQTechnologic #eQubeDaaS #DigitalTransformation #DigitalThread

No rebuild. No proprietary glue. Add your Honeycomb API key inside Embrace and your frontend metrics, logs, and traces forward automatically. Join Honeycomb + Embrace on July 14 for a look at the architecture behind user-focused observability, and how frontend sessions and backend traces finally live in one connected workflow. 💬 Bring your toughest questions for the live Q&A 📅 July 14 | 10 a.m. PT / 1 p.m. ET

Your dashboards are all green. ✅ Your users are abandoning checkout anyway.❌ That gap, between what backend monitoring reports and what users actually experience, is where most incidents hide. On July 14, Honeycomb and Embrace show how to close it: follow one user session from the device all the way to the backend trace, without rebuilding your stack. 💬 Bring your toughest questions for the live Q&A 📅 July 14 | 10 a.m. PT / 1 p.m. ET

𝗘𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗲 𝘁𝗵𝗲 𝗵𝗶𝗴𝗵 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗵𝗶𝗻𝗱𝘀𝗶𝗴𝗵𝘁 Learn about the value of near real-time data processing in our free white paper. #Industryinsights

Explore AskISI, AI-powered, conversational research assistant built exclusively on EMIS proprietary & differentiated intelligence. Thirty years of proprietary and licensed company and industry intelligence, now just a question away.

Most organisations already have the data. Most already have some AI in place, too. What's missing is the layer in between: the context that connects them, and the orchestration that turns that context into action. Issue 11 of The Data Advantage picks up where our last issue left off. If Issue 10 was about why context matters, this one is about what you actually do with it, how workforce management becomes workforce intelligence, why the contact centre stopped being the edge of customer experience, and what it takes to scale an AI pilot into something that actually lasts. Grounded in what Gartner, Forrester and McKinsey are seeing across the industry, as well as the latest conversations from Genesys Xperience 2026, not just our own view of it.

A frontline manager and a CFO can ask your AI system the exact same question — and both need a different, correct answer. If your system can't tell the difference, that's not a model problem. It's a context problem. We built a free 20-question self-assessment for data and analytics leaders, covering: → Semantic foundations — does every core metric actually have one agreed definition? → Context ownership — who's accountable if an AI answer is wrong because the context behind it was? → Persona & role awareness — does the same question get the right answer for the right person? → Validation & governance — can you trace and defend how an AI-generated answer got made? Score yourself out of 20. Most organisations land somewhere in the middle — the gap is usually process, not technology. Download: The AI Context Readiness Checklist #emite #datacontext #aireadiness