An AI-powered table supporting tens of millions of enthusiastic shoppers, taking over the 2025 Singles' Day shopping festival

A multi-trillion-scale shopping festival, for the first time orchestrated by a single spreadsheet.

After the "large and small models" war and the chaotic rise of Agents, the AI industry has finally delivered a proven, mature enterprise efficiency tool: the "AI spreadsheet." This spreadsheet saw its first large-scale application during the 17th edition of China's e-commerce Singles' Day in 2025.

On November 5, DingTalk announced a major technical breakthrough with Alibaba Cloud’s engineering team, launching the industry’s first intelligent spreadsheet capable of supporting over 10 million hot rows in a single table. Facing massive data surges like those during Singles' Day, brands no longer need to manually split data across multiple tables—now all data can run seamlessly on one sheet.

An Alibaba spokesperson previously stated that this year's Tmall Singles’ Day extensively leveraged AI technology to empower merchants, marking the first large-scale deployment of AI tools in the event’s history.

In the months leading up to Singles’ Day, usage metrics for products such as the DingTalk AI spreadsheet began to spike sharply. In response to urgent real-world market demands, the DingTalk and Alibaba Cloud ADB-PG database teams spent over 100 days overcoming technical challenges, ultimately scaling the AI spreadsheet’s capacity to support 10 million hot rows per table.

Why did the DingTalk AI Spreadsheet First Take Off in E-commerce?

Smart spreadsheets aren’t unique to DingTalk, so why is it that DingTalk’s AI spreadsheet gained popularity first in e-commerce? The answer lies not just in technology, but in who understands e-commerce better.

New technologies often emerge first in industries with the highest data density and shortest feedback cycles. The e-commerce sector handles trillions of transactions annually, manages thousands of SKUs, and runs hundreds of marketing campaigns. During events like Singles’ Day, real-time data volume and feedback needs surge to hundreds or even thousands of times normal levels. For example, during the 2024 Singles’ Day, Alibaba reported nearly 1.44 trillion yuan in total transaction volume—1.5 times the usual daily average.

Yet historically, e-commerce operations have been cobbled together from countless Excel files, CRMs, and ERPs: cumbersome to use, slow to update, inconsistent in data standards, and highly error-prone. Tools meant to boost efficiency instead became hidden drains on productivity.

First, e-commerce data is extremely fragmented—systems use different field definitions, inconsistent metrics, and isolated permissions. Getting an AI spreadsheet to integrate these heterogeneous data sources and update in real time is essentially equivalent to overhauling a company’s entire “data infrastructure.” Second, operational workflows are unstructured and vary widely across industries. Apparel and fast-moving consumer goods, for instance, operate very differently. During Singles’ Day, tasks like promotion scheduling, influencer collaborations, inventory transfers, customer service alerts, and post-sale compensation involve information scattered across chat groups and emails. Most decisions still rely on human judgment. Without deep e-commerce know-how, reconstructing a merchant’s backend is impossible.

DingTalk, backed by Alibaba’s ecosystem, stands out as one of the few global platforms in the AI form space that can directly connect to e-commerce’s underlying data architecture. It understands retail—integrating instantly with product shelves, inventory, user feedback, and marketing funnels—and grasps the flexible, evolving needs of Chinese merchants. These advantages make DingTalk’s AI spreadsheet inherently more “e-commerce-savvy” than competing platforms.

Therefore, when DingTalk used a single “AI spreadsheet” to manage the entire 2025 Singles’ Day campaign, the deeper goal was clear: to transform China’s outdated e-commerce backend systems. The vision is to let AI empower people to make smarter decisions, rather than letting humans be bogged down by complex coordination tasks and leaving vast data assets underutilized.

As the AI spreadsheet reshapes how e-commerce works, the industry itself is accelerating the evolution of DingTalk’s AI spreadsheet. Today, the AI spreadsheet has evolved into a lightweight Agent capable of thinking, acting, and collaborating. It’s no longer seen merely as a traditional SaaS tool, but as a gateway to an entirely new business operating system.

Currently, companies including Semir, Intime Department Store, and emerging fashion brand AlmondRocks are all using DingTalk’s AI spreadsheet to prepare for Singles’ Day.

In August this year, DingTalk CEO Wuzhao emphasized the platform’s AI strategy: first, build around AI and create AI-native products; second, help AI understand the real world so it can quickly take on work, freeing humans to focus on decision-making; third, stay humble and truly dive into diverse industries.

The DingTalk AI spreadsheet follows these three principles: building an AI-native product, solving real problems, and delivering tangible results for businesses.

AlmondRocks: A “Data Middle Platform” for Small and Medium Brands

AlmondRocks is a Chinese original designer streetwear brand focused on being “comfortable, stylish, and reasonably priced.” Starting with socks, it has expanded into loungewear and base layers. It operates both as a “design brand” and a “content brand,” growing primarily through social seeding on Xiaohongshu, live streaming on Douyin, and influencer partnerships—a classic omnichannel brand.

Zhang Qi, the founder, long struggled with “operational inefficiency.” The brand collaborates with over 6,000 influencers annually but has only 4–5 employees managing them. Data is scattered across platforms: pricing sheets in Excel, shipping orders in WPS, influencer scripts in WeChat documents. One salesperson might export seven or eight spreadsheets daily. Errors are routine.

After adopting DingTalk, they consolidated all influencer data—pricing, sample shipments, logistics, feedback, content output, conversion metrics—into the AI spreadsheet. What used to require manual entry of dozens of fields now needs only five or six inputs; the rest are automatically extracted by the AI. Additionally, the AI generates an influencer performance heatmap, using algorithms to identify which creators are worth long-term collaboration. Crucially, different roles—sales, legal, operations—can now collaborate on a single sheet with instant updates.

For example, when DingTalk detected strong sales of a particular sock style, back-end staff could immediately view real-time inventory turnover, channel sales distribution, and price elasticity. This allowed them to scale up production of the hit item—cutting a decision process that used to take three days down to just one.

Brands like AlmondRocks number in the tens of thousands within China’s e-commerce ecosystem, most lacking dedicated IT staff. With DingTalk’s AI spreadsheet, they now have access to their own “data middle platform.” Founder Zhang Qi put it simply: the DingTalk AI spreadsheet feels like a smart employee—“It’s the intelligent core driving data-based decisions, the key competitive advantage in every e-commerce battle.”

Intime Department Store: A Collaboration Revolution for a Thousand-Person Organization

AlmondRocks demonstrates how the DingTalk AI spreadsheet empowers smaller brands with stronger operations. Intime Department Store shows how the same tool enhances collaboration within a large, thousand-person organization.

Intime is one of China’s most traditional department store chains, with over 60 locations nationwide. Li Kai, head of content operations at Intime, decided in 2024 to use a single DingTalk AI spreadsheet to coordinate group-buy live streams across all 62 stores.

Li’s first step was getting all physical stores to work on the same AI spreadsheet: each store entered details about participating products—prices, inventory, coupon bundles. The system automatically aggregated, validated, and generated a master sheet, flagging anomalies, inventory gaps, and even pricing conflicts. Li built this entire live-streaming operation system himself using only DingTalk’s AI spreadsheet. “You could say the AI spreadsheet helped me turn into an MCN agency,” he remarked.

Before each live stream, the AI spreadsheet automatically sends reminders and pushes the project forward. Within two hours after the event ends, it automatically outputs key metrics: GMV, redemption rates, ROI comparisons. In traditional retail, completing such a workflow would require hundreds of communications, weeks of preparation, and dozens of Excel versions. Now, Li and one assistant can complete the entire process in five days. Previously limited to three group-buy live streams per month, they now average ten.

Semir: From User Feedback to Product Redesign

Domestic apparel leader Semir takes the AI spreadsheet a step further—applying it directly to product redesign.

Traditional apparel brands have long faced a dilemma: on one hand, the market continues to shrink—China’s clothing retail sales grew just 2.1% year-on-year in 2024, the lowest in a decade; on the other, consumer tastes shift rapidly. Social media has shortened fashion cycles, where a single viral video can redefine seasonal trends. As a result, competition is shifting from “channel capacity” to “market sensitivity.” The brand that captures user feedback fastest will produce more hits.

Before adopting DingTalk’s AI spreadsheet, a customer service agent could handle only 400–500 user feedback items per day. The job was tedious: copying screenshots, audio clips, and reviews into Excel, then categorizing and summarizing them. Different platforms (Tmall, Douyin, Xiaohongshu) had inconsistent formats and fields. During Singles’ Day, agents were often overwhelmed by messages.

"User feedback couldn't be structured, nor could it directly influence production," said Lu Wanlong, customer service supervisor at Semir, who has managed customer service for ten years and witnessed the transition from paper logs to Excel. "We also wanted to accumulate long-term user insights—over a year or even five years—but Excel made this extremely difficult."

DingTalk’s AI spreadsheet helped Semir turn user feedback into “product instructions” for the first time. It starts with “understanding what users are saying”: the AI form automatically collects cross-platform feedback daily. An AI semantic model identifies sentiment, issue types, and automatically tags negative feedback, triggering alerts when necessary. Daily updated visual dashboards help the brand quickly pinpoint problems.

For example, if one week before Singles’ Day the AI detects 87 new complaints about a women’s down jacket running “small in size,” mostly from northern regions, the system automatically generates an anomaly report. Ideally, the production team can adjust the pattern template the next day and, via the AI spreadsheet’s “supply chain linkage field,” send updated shoulder width and chest measurements to partner factories. Without changing materials, they can re-sample and ship modified versions in time for Singles’ Day, rather than waiting until after the sales peak.

Now, frontline roles like customer service and operations are no longer repetitive tasks but serve as critical interfaces for user data collection. Every human response helps train the AI to better understand consumers, ultimately freeing up staff to focus on strategic decision-making.

By August 2025, over 300,000 enterprises had adopted DingTalk’s AI spreadsheet, spanning e-commerce, manufacturing, retail, education, and real estate. Among them, e-commerce and retail saw the fastest growth, increasing 280% year-on-year. According to internal DingTalk forecasts, by the end of 2026, intelligent spreadsheet adoption in retail and e-commerce will reach 80%, with all high-frequency collaboration scenarios—including sales, customer service, production, and finance—being managed by smart spreadsheets.

This indicates that DingTalk’s AI spreadsheet has begun to achieve network effects—a growth mechanism unmatched by any point solution SaaS product.

DingTalk’s AI spreadsheet now fully covers core scenarios across e-commerce—from front-line customer service to back-end finance. Internal data shows it improves information flow efficiency by 10 to 15 times and shortens average decision cycles by over 60%.

In other words, the key determinant of a company’s success will no longer be scale, but speed. Beyond the traditional e-commerce “traffic wars,” a new competition is emerging, decided by two curves: the curve of decision speed and the curve of execution automation.

DingTalk’s AI spreadsheet is accelerating progress on both fronts.

In the future, organizations will no longer rely on hierarchical structures but increasingly on AI-driven intelligence: a user’s emotional shift, a live stream’s inventory change, or an SKU’s abnormal feedback will trigger new decisions within minutes.

Moreover, DingTalk’s AI spreadsheet has a unique advantage: it connects simultaneously to Tongyi Qianwen’s large model capabilities, Alimama’s marketing algorithms, Tmall’s transaction data, Cainiao’s supply chain network, and Alipay’s payment and credit systems.

If Microsoft’s Copilot excels at documents, Notion redefines knowledge organization, and Airtable simplifies app building, then DingTalk’s AI spreadsheet is rewriting how retail enterprises operate—it’s not just automating tasks, but dynamically orchestrating models, data, logistics, and finance across the e-commerce ecosystem, enabling the entire system to think and act at AI speed.

The spreadsheet was once humanity’s simplest computational tool. For decades, all business logic has been built upon those little cells—tracking inventory, calculating profits and losses, measuring growth.

Now that spreadsheets can compute, analyze, and decide on their own, humanity is entering a completely new mode of work.

This year’s Singles’ Day marks the first time DingTalk’s AI spreadsheet fought side-by-side with merchants, and the first time China’s e-commerce industry attempted to rebuild its operating system with AI: Can an intelligent core that understands users, products, and acts autonomously fully replace Excel and ERP?

The answer isn’t certain yet—but this transformation is accelerating toward reality.

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