Ecom: The Future. AI, Innovation
رفتن به کانال در Telegram
A channel about the future of marketplaces: innovations and artificial intelligence. Аdvertising placement @SellerDenPR https://telega.io/channels/ecommerce_AI/card
نمایش بیشتر
شبکه:📈 تحلیل کانال تلگرام Ecom: The Future. AI, Innovation
کانال Ecom: The Future. AI, Innovation (@ecommerce_ai) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 58 560 مشترک است و جایگاه 800 را در دسته تجارت و رتبه 467 را در منطقه الولايات المتحدة الأمريكية دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 58 560 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 25 اوت, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -3 391 و در ۲۴ ساعت گذشته برابر -125 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 0.94% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.44% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 550 بازدید دریافت میکند. در اولین روز معمولاً 259 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 1 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند insidead, mining, 1win, seller, shein تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“A channel about the future of marketplaces: innovations and artificial intelligence.
Аdvertising placement @SellerDenPR
https://telega.io/channels/ecommerce_AI/card”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 26 اوت, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته تجارت تبدیل کردهاند.
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| 3 |  Instacart is turning conversational AI into a retail media shelf
Instacart’s ad business topped $1 billion in 2025 and now reaches nearly 100,000 stores across more than 2,200 retail banners. It is extending that engine into Cart Assistant, an AI shopping tool built on more than 1.6 billion lifetime orders and live inventory data. Instacart says the assistant has already rolled out to millions of US shoppers, and orders placed through it are running above the company’s $115 average order value.
The next move matters even more: Instacart is testing ad formats designed for conversation, including sponsored recipes, occasion-based recommendations, deal surfacing, and product exploration while a shopper is still deciding what belongs in the basket. It has also connected the cart experience to Google Gemini.
The commerce signal is clear: AI is becoming the place where discovery, merchandising, and basket-building happen before a shopper ever types a SKU. | 276 |
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| 6 |  Stripe and Ramp are turning AI model routing into a commerce infrastructure layer
Ramp launched Router.com after running it internally for three years. Instead of locking a workflow into one model, Router chooses the cheapest model that is still good enough for each request. Ramp says that cut its own AI costs by about 30%, while early customers are seeing average savings of 40%.
Stripe is making the same bet at a larger scale by buying OpenRouter for at least $7.5 billion. OpenRouter gives developers access to more than 400 models from over 80 providers, processes more than 10 trillion tokens a day, and serves more than 10 million developers.
The commerce signal is that AI is starting to look less like a single assistant and more like an operating layer behind support, payments, and internal tooling. Once model choice itself becomes programmable, cost and reliability turn into workflow features, not just engineering concerns. | 386 |
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| 9 |  Airbnb is extending AI from support into search, listing comparison, and host onboarding
Airbnb says its AI customer-service assistant now resolves nearly 45% of user inquiries without a human agent, up from about one-third at the end of last year. The system already works in more than 50 languages, and voice-call support is planned for later this year.
The company is now pushing AI further upstream in the booking flow. Airbnb is testing a natural-language search toggle that returns personalized listing highlights and conversational titles, and it plans to add AI-powered home comparison later this year. It is also using AI to speed up host listing onboarding and internal product delivery, with CEO Brian Chesky saying AI has cut the time from concept to feature launch by as much as 60%.
Seller takeaway: AI becomes commercially meaningful when support, discovery, comparison, and onboarding connect into one measurable booking workflow. | 414 |
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| 12 |  Alibaba says Taobao merchants are moving listing, ads, and service into one agentic stack
Alibaba says Taobao merchants now have skill-based agentic tools that automate product listing, store management, advertising, and customer service inside one operations layer. On the shopper side, Qwen Shopping Assistant is also expanding, covering the flow from discovery to after-sales service.
The scale behind that push is meaningful. Alibaba reported $39.6 billion in quarterly revenue, AI Cloud and Compute Services revenue of $7.1 billion, up 45% year over year, and AI-related product revenue of $1.8 billion with triple-digit growth for the twelfth straight quarter.
Seller takeaway: the next AI advantage in commerce may come less from a chatbot alone and more from putting catalog, marketing, and service actions into one merchant workflow. | 479 |
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| 15 |  Walmart’s Sparky is turning AI shopping into a fuller marketplace workflow
Walmart’s latest quarter suggests AI shopping is moving past product discovery and into measurable transaction lift. Shoppers using the company’s Sparky assistant are spending 40% more per order, while total Sparky users are up 70% year over year. In the same quarter, Walmart reported 23% global eCommerce growth.
The bigger signal is where that demand goes next. Walmart said nearly 50% of its marketplace business now flows through fulfillment services, which means more of the path after the AI prompt stays inside one operating system. Discovery, seller selection, order routing, and delivery are getting tied together instead of being handed off between separate tools.
Seller takeaway: AI becomes commercially meaningful when it is attached to fulfillment capacity, not just to better search results. | 547 |
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| 18 |  Freightos shows AI logistics value starts when freight buying becomes machine-readable
Freightos’ second-quarter results suggest the AI opportunity in commerce is moving deeper into execution, not just recommendation. The company said its marketplace handled 458,000 transactions in Q2, up 15% year over year, while gross booking value rose 33% to a record $422 million. Platform revenue increased 19% to $2.9 million.
What stands out is the operating mix. Freightos reported about 21,000 unique buyer users, only 4% more than a year earlier, yet transaction activity grew nearly four times faster. That means more actual procurement is moving onto digital rails where rates, capacity, and bookings can be queried continuously instead of checked manually.
Seller takeaway: AI cannot optimize cross-border replenishment or landed-cost decisions if freight quotes, capacity shifts, and booking status still live in spreadsheets instead of machine-readable workflows. | 603 |
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| 20 |  Malachyte is turning anonymous shopper behavior into a live storefront signal
Malachyte says it can infer intent from a shopper’s live behavior in under 200 milliseconds, without waiting for a login, saved history, or declared preferences. The startup applies the same behavioral logic its founders built at Spotify, where they say the recommendation infrastructure powers more than 90% of recommendations across 800 million users and 1 billion items.
In commerce, that means the storefront can keep rewriting itself during the session. Search results, product listings, banners, and recommendations change as a shopper scrolls, hovers, filters, clicks, or backs out. Merchants can also adjust the model with their own priorities around inventory, margin, promotions, and discovery.
Seller takeaway: AI personalization is becoming an in-session decision layer, so product attributes, inventory state, and promotion rules need to be usable in real time, not just in overnight merchandising logic. | 619 |
