B2B ad examples

Dataplor's Global Platform covers 370M+ locations across 250+ countries, with foot traffic, polygons, and trade areas at your fingertips. Ask it where markets are growing and see where your next move should be. 👉 Get an answer you can act on today.

Ask Dataplor's Global Platform about any CPG market on earth: 🔍where to invest 🔒where competitors are winning 📊where opportunity is hiding And get a definitive answer instantly. No technical teams required. No waiting.

We’ve supported mission-driven leaders from NGOs and foundations, as well as top academic researchers. Our work is built on clarity, precision, and trust. We treat your research like our own: with care, rigour, and an obsession for quality.

Find signals, prevent drop-offs, and build smarter re-engagement flows with actionable retention insights.

Learn what top LiveOps teams do to drive session frequency and keep users around longer.

I often get asked why local economy? The answer is simple - it’s a massively underserved market. 99% of sales tools are designed to sell to office workers. This is no knock on LinkedIn Sales Nav or ZoomInfo, those tools are great if you’re selling to tech companies or F500. The challenge is if you sell into restaurants, the trades, brick-and-mortar retail, healthcare providers, or any other mainstreet business - these companies and individuals simply do not exist on LinkedIn or in traditional databases. They are ghosts on the internet. As a result, sales reps in these industries spend 20-40% of their week on manual research - making it nearly impossible to hit ambitious revenue goals. The good news is it’s finally possible to solve this problem. Unstructured data algorithms are now intelligent enough to map an incredibly noisy web of online, offline, and proprietary data sources. The best companies are already automating this research away, freeing up reps to focus on selling. Over the next few weeks, I’m excited to start sharing more examples of how they’re doing it and what it means for the future of GTM.

10x Faster Spark. 80% Cost Reduction. 0 Code Changes. Yes, really. This isn't just another plugin that requires you to rewrite your pipelines. Drop-in DataPelago Nucleus which: - Integrates at the Spark Catalyst level. - Recompiles for end-to-end GPU execution. Your Data frame ops, SQL queries, and ML pipelines just got 10x faster and 80% cheaper. No code changes.

Yup, these were actual reactions to DataPelago demos. Both are now customers and have saved upwards of a million in Spark costs. You can too, just hit the button to start saving. The best part? You pay $0 for next 6 months :)

Number 1 reason sales reps selling to local businesses aren’t efficient? The data they are using in Salesforce is a complete mess. In the past month, we’ve onboarded 5 companies with 200+ sales reps and all of them had the same problem. When we map our real-time database to the static accounts in their Salesforce, over 50%(!) of their accounts aren’t addressable: - Out of business: turnover for local businesses is huge - Wrong industry: over the years bad data accumulates - Duplicate accounts: business hierarchies are extremely difficult to map And on top of that, companies are often missing thousands of good-fit accounts. These blindspots lead to incorrect claims about “exhausted TAM” and broken territory assignments. We’re working on a way to offer a 30 min Salesforce Health Check that securely and automatically builds this waterfall, without any data leaving your CRM. For one multi-billion restaurant SaaS company we discovered 60% of their accounts needed to be disqualified, but fortunately we simultaneously identified 2x new, qualified accounts. If you’re interested in getting an accurate picture for your company, send me or Miles Kane a message.

AI is moving fast. Want the shortcut to what really matters? Watch Episode 1 of Diffusion by Defined.ai.

3‑minute episodes on AI trends that matter.

Reduce exposure and control the risks of off-channel communication with CC1 Messaging. Keep every chat in one channel inside Teams or Webex. 💻📲

Are you confident that employee messaging remains compliant across off-channel apps? CC1 Messaging helps you close those compliance gaps.💻📲

Get a clear framework that will help you to evaluate data quality. 6 steps to better insights + a checklist

What are data providers hiding from you? Watch the full video and get a clear framework about data quality evaluation. 6 clear steps to better insights + a checklist.

If you ship apps on Huawei devices in China — and increasingly you have to — you've probably noticed something: most international product analytics platforms quietly skipped HarmonyOS. Mixpanel, Amplitude, Firebase, PostHog, Heap — none of them currently offer a native HarmonyOS SDK. Your options have effectively been Huawei Analytics Kit (locked into AppGallery Connect, data sits with Huawei) or domestic SaaS vendors like Sensors Data and GrowingIO. Today we're adding a real third option. Countly v26.1.0 for HarmonyOS is live on GitHub. It ships at near-parity with our Android SDK from day one: → Events, views, sessions → Crash reporting → User profiles → Consent management → Device ID, location → Remote Config → SDK Behavior Settings → Crash analytics Why this matters for teams shipping apps in China: 1️⃣ Self-hosted or private cloud. Run Countly on your own infrastructure inside China. Your HarmonyOS event data never leaves your servers. No third-party SaaS pipeline, no AppGallery Connect dependency, no cross-border data transfer concerns under PIPL. 2️⃣ One platform across Android, iOS, Web, and HarmonyOS. Same event taxonomy, same dashboards, same SDK API surface. No fragmented stack, no separate vendor just for HarmonyOS. 3️⃣ Product analytics + engagement in one place. Not just events and funnels — also crashes, user profiles, remote config, and (in upcoming releases) the rest of the Countly engagement layer. HarmonyOS is now China's #2 mobile OS, with 55M+ native devices and ~17% share. The teams who'll get ahead are the ones treating it as a first-class platform — not an afterthought. If you're a HarmonyOS developer or a data team responsible for understanding how Huawei-device users actually behave in your product, this is for you. Check the SDK: https://lnkd.in/d_ie-BXW See our Docs: https://lnkd.in/dBNGvThM #HarmonyOS #ProductAnalytics #MobileAnalytics #Huawei #DataPrivacy #OpenSource #Countly

Raadpleeg en archiveer alle bedrijfsinformatie die je nodig hebt voor KYC onboarding en monitoring makkelijk en snel in één tool.

The Kafka agent isn’t the moat. The context and permissioning layer around it is. A capable model is useful, but it doesn’t operate in a vacuum. In production, the hard part is the surrounding system: what the agent can observe, what it can reason over, and what it’s allowed to change. In Kafka, that means more than seeing a lag spike. It means understanding schemas, lineage, ownership, ACLs, recent changes, and how services depend on each other. Without that context, the agent’s guessing. Without the right permissions, it’s a faster path to an outage. That’s where agentic Kafka operations gets interesting: not just better agents, but better context and control around them.

Every team and AI agent touches your Kafka. Who controls what they access? Conduktor governs both, on the Kafka you already run.

The speed of cloud analytics. The control of self-hosting. For years, enterprises have been forced to choose: the performance of cloud analytics, or keeping customer data inside their own environment. Countly 26.01 is our answer to that false tradeoff. A new analytics engine built to analyze millions of users, power real-time personalization, and run AI-driven experiences — while behavioral data stays in your infrastructure. → Up to 100M monthly active users → Self-hosted or private cloud → GDPR, HIPAA, SOC 2, CCPA-ready by design Learn more about the new architecture here: https://lnkd.in/d-HM9K4W #analytics #dataprivacy #enterprise #selfhosted

What if your pipelines could keep running on a Global File System that stays current as data changes, without constant rebuilding?

What if compliance stayed visible as documents move through AI workflows?

If your data team spends more time fixing data than analyzing it, we know ho to solve this. We connect ERP, CRM, MES, HRIS, EHR systems plus external files into a governed AI-ready data warehouse, applying business rules, validations, and reconciliations for you. You get standardized dashboards and automated reports that finance, sales, and operations can rely on, without rebuilding your ERP landscape.

Looking to get started with Power BI or improve your current reporting? We’ll assess your data landscape and outline a clear path to building scalable, business-ready dashboards. Gain clarity on what to prioritize, how to structure your data, and how to turn it into a reliable reporting system that supports real decisions.