LinkedIn video ad examples

How many people genuinely visit an asset, and how many are passing through? Christian shows why visit counts become more useful when paired with dwell time, potential bounce rates and competitor comparisons. Watch the full discussion.

When an asset's market changes, the choice is rarely limited to carrying on as usual or starting again. This clip looks at how owners can use evidence about local consumers to make more targeted changes. See the full interview.

First reply time rose, but that doesn’t necessarily mean the team got slower. In this example, an AI assistant uses the Geckoboard Metrics MCP to investigate eight weeks of support data. It finds that part of the increase came from a shift toward email, a slower support channel. After accounting for that change, the remaining delay is concentrated in early-morning Tier 1 email. Breaking the metric down turns a broad concern about team speed into a focused investigation of one channel, tier and time of day.

Claude can investigate why CSAT fell. It shouldn’t have to calculate CSAT from thousands of Zendesk tickets first. But that’s what often happens when an AI assistant only has access to raw records. This week, we launched the Geckoboard Metrics MCP, a connector that gives AI assistants like Claude and ChatGPT access to accurate, real-time, pre-calculated Zendesk metrics. You can ask: “Why did CSAT fall last week?” “Which queue is driving the increase in first response time?” “How does this quarter compare with the previous one?” Geckoboard calculates the metrics. Your AI assistant investigates what changed, combines the numbers with context about your business and creates the report, briefing or resource you asked for. It can also bring in metrics from platforms like Aircall, HubSpot, Pipedrive and Shopify, giving it a broader view of the customer journey. It’s like having a support data analyst inside your AI assistant. The Geckoboard Metrics MCP is now live and is included on every Geckoboard plan. See it in action. Link in comments.

Places tell a story: where activity gathers, when it peaks, and how it changes week to week. Audience Composer turns that story into audiences. Choose your places, set a time window, and compose. Then send the audience to your DSP, SSP, or social platform. Bring one brief to a 20-minute call and we'll scope the audience and its estimated size with you.

Luciq captures what generic tools miss: battery health, network switching, and thermal data. Built for mobile from the ground up.

𝐊𝐈? 𝐂𝐡𝐞𝐜𝐤. ✅ 𝐃𝐚𝐭𝐞𝐧? Ä𝐡𝐦 … Das KI-Projekt ist beschlossen. Die Technologie steht bereit. Der Use Case ist definiert. Und dann liegen bei Ihnen Kundendaten, Verträge und interne Korrespondenz. Dazu kommen DSGVO, DORA und der AI Act. 𝐖𝐞𝐥𝐜𝐡𝐞 𝐝𝐚𝐯𝐨𝐧 𝐬𝐨𝐥𝐥 𝐝𝐢𝐞 𝐊𝐈 𝐧𝐮𝐭𝐳𝐞𝐧? Und welche davon darf sie überhaupt sehen? Genau hier wird aus einem KI-Projekt plötzlich ein Datenprojekt. Warum das oft erst viel zu spät auffällt, zeigen wir im Video. 👇

GPU costs are high enough, your storage bill shouldn't be why margins shrink. No egress fees. No lock-in. Just S3-compatible storage built for Neoclouds.

Your storage needs grow with every model you train. Backblaze B2 Cloud Storage scales with you, without the vendor lock-in.

Your AI never hedges. It answers everything with total confidence - including the things it gets wrong. Certainty is a must, not an option.

Your AI sounded certain. Your boardroom wants a source. Lineage, context, and governance are what turn a confident answer into a defensible one.

We are heading to Cologne, and DMEXCO is the part we have been building up to. Book twenty minutes at [email protected], or find James, Huw and Heidi on the stand. DMEXCO, 23 and 24 September. Hall 6.1, stand D010a. Book a meeting via the app: https://lnkd.in/ek_QuhgV #DMEXCO hashtag#AdTech hashtag#ProgrammaticAdvertising hashtag#AgenticAI hashtag#Identifiers

What brings 51Degrees to DMEXCO? Meeting people. Talking challenges. Removing friction. Add letting the tech provide the wow factor. James explains it better. Find us in Hall 6 Stand D010a. #DMEXCO #DeviceDetection #Identifiers #51Did

ITRS Agentic AI brings intelligent SRE agents to mission-critical operations, where transparency and control aren’t optional. Connect signals across your stack, uncover evidence-backed root causes faster, and reduce MTTR.

💯 You know exactly what web data you need. Getting it is the part that needs a developer. Not anymore. Infatica Data Platform is a browser-based workspace. Upload URLs, keywords, a spreadsheet, or just describe what you need in plain language, pick a method, and get structured results in a dashboard. No code, no proxies to manage. A retail team can upload 2,000 competitor URLs, set country and device, turn on JavaScript rendering, and schedule daily price checks, all running on Infatica's ISO-certified network of 40M+ IPs across 195 countries. It's brand new, and we're looking for beta testers. Early access in exchange for your honest feedback. If you'd rather launch a run than file a dev ticket, we want you in. See how it works in detail: https://lnkd.in/ehMvMW_m Join the beta: https://lnkd.in/eVTN_CqF

Generally, AI systems look simple from the outside. At least that's what they're often polished up to appear: a model, some data, a prediction, and perfect output. By now most are catching on that the engineering reality is different. Google's research on hidden technical debt in machine learning systems showed that the actual ML code is a small piece of what a production system needs. Configuration, data verification, feature extraction, resource management, monitoring, serving infrastructure: all of it sits around the model, and all of it needs to be maintained. Nearly a decade later, this hasn't changed. If anything, it's proven more relevant than ever. In this video, Martin does a short walkthrough of that framework and what it means for teams scoping AI work. Worth watching to make sure you avoid technical debt in your AI project. If you're interested to learn more about what our team has developed in terms of papers, guides, and more, feel free to reach out.

Google's research on hidden technical debt in machine learning systems showed that the actual ML code is a small piece of what a production system needs. Configuration, data verification, feature extraction, resource management, monitoring, serving infrastructure: all of it sits around the model, and all of it needs to be maintained. Nearly a decade later, this hasn't changed. If anything, it's proven more relevant than ever. Generally, AI systems look simple from the outside. At least that's what they're often polished up to appear: a model, some data, a prediction, and perfect output. By now most are catching on that the engineering reality is different. In this video, Martin does a short walkthrough of that framework and what it means for teams scoping AI work. Worth watching to make sure you avoid technical debt in your AI project. If you're interested to learn more about what our team has developed in terms of papers, guides, and more, feel free to reach out.

𝗖𝗲𝗹𝗲𝗯𝗿𝗮𝗺𝗼𝘀 𝗷𝘂𝗻𝘁𝗼𝘀. Festejamos não só o que somos hoje, mas também a história que nos trouxe até aqui: 120 anos de evolução, inovação e compromisso com os nossos clientes. 120 anos apoiar as decisões de negócio Imagine Next — O futuro tem passado

Every call counts. Make sure your workforce is ready when it matters most. Let AI forecast, schedule and optimize your workforce for flawless CX every time.

For more than a decade, Import.io has been a leader in Web Data Extraction, Automation & Intelligence. We’re proud to announce that Import.io has joined Neuralogics and together, we’re unlocking a new chapter in data intelligence with AI. This is where the future begins! #Importio #Neuralogics #AI #DataIntelligence #WebData #DataExtraction #Innovation #FutureOfData

In CX, timing is everything. Empower your workforce with FLOW WFM — the AI-driven forecasting and scheduling platform that ensures you’re always ready when it matters most.

🚸 Over the next 20 years, Australia’s education system will need to find space for an extra 720,000 children. One factor impacting this number is fertility rates (the average number of children born to each woman). The pandemic disrupted the downward trend in Australia's fertility rate, creating a COVID baby blip that is now rippling through the population. Over the next few years, we will see the impact as these children start arriving at the school gate. In this video, Ielyzaveta Ivanova from our population forecasting team explains how these shifts are playing out and why they matter for anyone planning schools and childcare. However, fertility is just one piece of the puzzle. In our new report, launching on Monday, we present the full picture of post-pandemic population trends, showing how they are reshaping demand for schools and childcare at the local level over the next 20 years. 📘 Pre-register for your copy: https://lnkd.in/gDz4UP2E #schools #childcare #planning #education #population #demographics

This one hits different. I grew up playing hurling. To the uninitiated, it’s Ireland’s somewhat lawless, reckless-looking cousin of baseball, and the fastest field sport in the world. If you haven’t seen it before, look it up on YouTube. You’ll see what I mean. While I’m no Billy Beane, I am a sports fanatic, so when a team as legendary as the Boston Red Sox scheduled a call with our team, they had my attention right away. From the very first conversation, everything clicked: ✅ Clear, high-impact use case ✅ Smart, motivated team ✅ Perfect fit for our platform ✅ Instant rapport between both teams When everything aligns like that, it’s not just a customer <> vendor relationship, it’s a partnership. Shoutout to Ben, Sukriti, Jon and the rest of the Red Sox team for being such a delight to work with. And to our own team, who knocked it out of the park (sorry, I had to!!) once again.