DataOx

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DataOx

DataOx

@Data_Ox

Delivering data that leads since 2015. We extract data on demand from any public source - even complex websites. DM us

Katılım Eylül 2020
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DataOx
DataOx@Data_Ox·
Since 2015, we've helped businesses turn data chaos into advantage. We build custom data pipelines around your goals — not templates. Tailored to your workflow, transparent and scalable as you grow. Need help with web scraping or data extraction? DM us: bit.ly/499XEIM
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DataOx
DataOx@Data_Ox·
@jasonlk Right, and the same applies to the data feeding that agent. Teams spend months picking the platform, then plug in stale or unstructured data and wonder why outputs are off. Training matters - but so does what you're training on. Garbage in, confident garbage out.
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Jason ✨👾SaaStr.Ai✨ Lemkin
Jason ✨👾SaaStr.Ai✨ Lemkin@jasonlk·
The most common AI agent mistake: spending 3 months evaluating platforms instead of picking one and training it. Here's what we've learned: training matters more than the vendor. A great training job on a B+ platform beats a lazy deployment on an A+ platform every time. Pick a leader. Go deep. Stop the bake-off.
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DataOx
DataOx@Data_Ox·
Same logic applies to data pipelines. Nobody cares about the architecture debate - they care whether the data is there when the decision needs to be made. Latency in your pipeline = latency in your strategy.
JP Demas@jpdemas

People talk about local-first as a data-ownership debate. To me it's a latency and feel decision, and the UX difference is the whole point. The "philosophy" framing glosses over what it actually changes in Spondr: every read operation, search, thread load, body fetch, runs against local SQLite. 50ms, not 500ms. No spinner. No API in the critical path. Users don't care about the philosophy. They care about speed.

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DataOx
DataOx@Data_Ox·
@vishal_v06 Exactly where we live. Messy data workflows, manual collection, broken pipelines - that's not just a ops problem, it's a signal. The messier the process, the bigger the opportunity to build something that actually holds at scale.
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Vishal
Vishal@vishal_v06·
I’ve spent years building inside enterprise systems. One thing it taught me - messy workflows are where the best B2B products hide.
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DataOx
DataOx@Data_Ox·
@SamuelWill30746 Automated - manual doesn't scale. By the time you've checked 50 competitor pages, the data's already outdated. We work with teams who've made that switch - not through another tool to manage, but a service that runs it for them. The difference shows up in decisions :)
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Excel.w.Samuel
Excel.w.Samuel@SamuelWill30746·
@Data_Ox Good point I usually combine competitor pricing tracking, offer positioning, and on-site behavior data, because strategy works best when market signals and customer actions align. I’m curious, do you rely more on manual research or automated tracking tools?
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DataOx
DataOx@Data_Ox·
@SamuelWill30746 Competitor pricing in real time - hands down. Customer behavior tells you what happened. Competitor data tells you what to do next. The gap between those two is where most e-commerce teams lose. What's your current source for competitor positioning?
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Excel.w.Samuel
Excel.w.Samuel@SamuelWill30746·
@Data_Ox Exactly Data removes the guesswork. I usually look at customer behavior, competitor positioning, and conversion patterns, because the best offers come from understanding what buyers are already responding to. Curious , which data point do you personally trust the most?
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DataOx
DataOx@Data_Ox·
@AlexHormozi Add 6) : built on assumptions, not real market data. Wrong pricing, wrong positioning, wrong audience - all because nobody checked what competitors are actually offering right now. Offer strategy without data is just expensive guessing.
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Alex Hormozi
Alex Hormozi@AlexHormozi·
5 reasons your offer isn't converting: 1) Targeting poor people 2) Not enough Proof 3) Too little friction 4) Big outcome not fast enough 5) "Sounds like work"
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DataOx
DataOx@Data_Ox·
@MoviSvami And every orchestra needs a score to follow. In product - that's data. Real-time data is what lets the whole system play in sync. Without it, even the best conductor is just waving their hands.
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MoviSvami
MoviSvami@MoviSvami·
The musicians play their instruments. I play the orchestra." —Steve Jobs Product leadership = systems orchestration, not solo performance. 🎵 Make tech, design & UX harmonize. Conduct, don't just play. 🎯 #movisvami #ProductManagement #Leadership #Innovation
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DataOx
DataOx@Data_Ox·
This is exactly why real-time competitor data matters. If your pricing strategy depends on what you think competitors are doing - you're already behind. The companies that spotted Amazon's moves early had one thing in common: automated data monitoring, not manual checks.
Jérôme MONANGE @JeromeMONANGE

#eCommerce 💻AMAZON accusé de manipuler les prix : un rapport accablant lève le voile sur les pratiques commerciales du géant comment Amazon aurait mené des stratégies pour augmenter les prix chez ses concurrents juste avant le Prime Day, soit une période de soldes organisée par Amazon. L’entreprise américaine aurait également incité ses fournisseurs à rendre certains produits en rupture de stock, ou indisponibles à un prix inférieur, chez ses concurrents. buff.ly/z7eBzAE

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DataOx
DataOx@Data_Ox·
@StoreOperators Exactly this. And there's a step even before the workflow - the data feeding it. AI scales your processes, but if the input data is stale or inaccurate, you're scaling noise. What's your data source look like behind these workflows?
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Store Operators
Store Operators@StoreOperators·
Why do most e-commerce AI tools fail? They replace processes instead of strengthening them. The best AI doesn't create workflows from scratch – it learns and scales your existing ones. Like onboarding a new employee that can scale infinitely. #Ecommerce #AI
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DataOx
DataOx@Data_Ox·
@AliciaMaciasON 10 ideas to boost conversion - solid list. One thing that often gets missed: most of these strategies only work when the data behind them is accurate and fresh. Competitor pricing, demand trends, customer behavior - how are you collecting that data today?
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DataOx
DataOx@Data_Ox·
@via_marketing_ Speed is table stakes. The real question: what decisions does the data actually feed into? Salary benchmarks sitting in a spreadsheet nobody opens, same problem, different format. Curious what's the biggest gap you see: access to data, or the process that turns it into action?
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Via Marketing
Via Marketing@via_marketing_·
@Data_Ox Most HR teams collect data religiously but rarely act on it fast enough to matter. Automation without strategy just creates faster irrelevance.
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DataOx
DataOx@Data_Ox·
You're not slow at hiring. You're slow at getting the data to hire. 3+ boxes = data collection is quietly killing your speed: look in thread for list! #TalentAcquisition #HR #Recruitment #HRTech
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DataOx
DataOx@Data_Ox·
☐ Manual weekly candidate list downloads ☐ Two recruiters researching the same companies ☐ No “last updated” in your talent pool ☐ Learning about competitor hires 2 weeks late ☐ Salary data from last year’s PDF ☐ Headcount decisions based on gut, not signals #HR #HRTech
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DataOx
DataOx@Data_Ox·
B2B teams lose deals talking to the wrong people. Stale lists. Outdated contacts. Dead databases. Web scraping fixes it: fresh targeted prospects from job boards & directories auto-matched to your ideal buyer. Short practical guide → Link in comments #B2BSales #LeadGeneration
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Keşfet

@jasonlk @vishal_v06 @SamuelWill30746 @AlexHormozi @MoviSvami @StoreOperators @AliciaMaciasON @elonmusk