Intime Retail: One Person, One DingTalk AI Sheet, Building an MCN

Recently, Intime Department Store launched a large-scale group-buying coupon livestreaming event on Douyin, covering more than 60 malls, over a dozen international beauty brands, and more than 80 different coupons.

In traditional work models, such events require repeated communication among multiple parties, involving numerous steps such as product information collection, price review, coupon bundling, and process verification—often taking a full team several weeks to coordinate, with extremely high coordination costs.

However, Li Kai, head of content operations at Intime, managed the entire information alignment and collaboration process within just a few days using only one person and one tool: DingTalk's AI Spreadsheet.

"DingTalk’s AI Spreadsheet is like a small ERP system. You could say it enables me, as an individual, to function like an entire MCN company." Li Kai said.

Starting from Scratch: Building the First Success Story

In August 2024, Li Kai joined Intime Department Store to lead its new online group-buying business. While the team generally believed in its potential, there was no clear path for implementation.

He determined that the core value of group buying lies in driving foot traffic to physical stores, increasing customer visits and conversion rates. As performance owners, mall managers were naturally most concerned about this.

He chose Intime Hefei Zhengwu Mall as a pilot site, combining dining vouchers, retail coupons, and parking passes into an “X+Y” package sold via Douyin livestreams. Nearly 10,000 packages were sold within a week.

By analyzing redemption data and cost inputs, he found that the customer acquisition cost through Douyin group buying was only 0.5% of that from advertising channels like WeChat Moments or Xiaohongshu—making it extremely cost-effective.

This case quickly gained traction internally, leading to a surge in group-buying requests for Li Kai.

Scaling Challenges: One Person Handling Full Operations

As the business expanded, Li Kai faced increasingly complex management challenges: collecting product information from various malls, scheduling livestreams, managing host performance—workloads equivalent to those of a small team.

These tasks relied heavily on repetitive communication, resulting in low efficiency and frequent errors. He urgently needed an efficient collaboration tool.

Intime has been fully using DingTalk since 2020. During a chance encounter with a pop-up window, Li Kai discovered DingTalk's AI Spreadsheet and immediately recognized its potential.

First Try with AI Spreadsheet: Automating Information Collection

In December 2024, he built the first version of his AI Spreadsheet to centrally collect product details, prices, and promotional offers from all participating malls.

Previously relying on Word or Excel templates led to inconsistent formats, time-consuming consolidation, and difficulty synchronizing updates. Now, each party simply fills in their section, and data is automatically aggregated.

More importantly, the AI Spreadsheet supports bidirectional linked fields: when one dataset is updated, all related tables are automatically refreshed, ensuring real-time consistency.

"It’s like everyone is collaboratively creating together—the efficiency improved rapidly," Li said. After experiencing these benefits, he further developed a more sophisticated system in January 2025.

Building an MCN Middleware: Integrated Management of People, Goods, Venue, and Finance

Today, Li Kai single-handedly manages a livestreaming network across 62 malls, handling monthly transaction volumes exceeding 20 million yuan. At the heart of this operation is turning DingTalk’s AI Spreadsheet into an MCN-level middleware system covering "people, goods, venue, and finance."

To each mall, Li functions like a third-party MCN agency, signing contracts and charging virtual fees for every collaboration.

In traditional workflows, contract execution and reconciliation processes are cumbersome, requiring constant follow-ups. With the AI Spreadsheet, deliverables and payable amounts can be tracked in real time, with automatic system reminders for pending actions.

For host management, he created a personnel database recording resumes, contracts, and livestream durations. Through multi-table associations, salaries are automatically calculated, eliminating manual Excel checks.

Prior to livestreams, the system automatically schedules sessions and pushes time, location, and product lineup details to hosts and malls. New hosts also receive training materials. After broadcasts, hosts upload screenshots and other materials directly into the spreadsheet for post-event analysis.

In inventory management, the AI Spreadsheet not only allows collaborative input from multiple parties but also uses AI-powered fields to automatically correct non-compliant text and generate mall prefixes based on city names, preventing misclassification.

He also pre-trained an AI analytics model by feeding in industry benchmark data, enabling the system to automatically evaluate each livestream’s performance and generate actionable insights.

"In the past, we’d do a retrospective days or even weeks after a stream—if we had time at all. Now, data is instantly updated and pushed out. Sometimes, malls receive recap reports at midnight and assume I’m still working late, but actually it’s the system sending them automatically under my name," Li joked, adding that colleagues now call him the "king of hustle."

In reality, it’s the AI Spreadsheet driving continuous progress—that’s where its true value lies.

From Tool to Mindset: Restructuring Retail Operations Logic

Li once considered developing a low-code MOS system but abandoned the idea due to complicated approval procedures and lack of autonomy. The emergence of DingTalk’s AI Spreadsheet gave him the key to solving retail management challenges.

"If you're in retail, you must use this," Li emphasized.

Retail operations involve complex data and frequent multi-party interactions. The AI Spreadsheet is designed precisely for collaborative creation, interconnected information, and synchronized teamwork—and it’s simple enough for anyone to use.

For example, when new clothing arrives at a physical store, managers used to manually track sales velocity over 30 days and report upward layer by layer—a lengthy process that often missed optimal restocking windows. Now, the AI Spreadsheet automatically analyzes data and generates restocking recommendations.

This reflects the current state of Intime’s group buying: real-time updates on product lineups, applicable malls, pricing, sales, and inventory allow malls to instantly decide whether to replenish stock or adjust coupons.

Previously, building such systems required expensive outsourcing. Now, a single AI Spreadsheet can achieve the same. It can even integrate external variables like weather and temperature to forecast demand changes.

For instance, T-shirt sales naturally decline as temperatures drop. The system can automatically suggest reducing restock orders—directly addressing the fashion industry’s chronic pain point of mismatched supply and demand.

With years of retail experience, Li deeply understands the difficulties of managing "people, goods, and venues." Today, the AI Spreadsheet acts as a "digital hub," making scheduling, attendance tracking, performance evaluation, and promotions fully online, automated, and visible.

He showed the AI Spreadsheet on his phone: voucher registration happens instantly, livestream schedules are clearly laid out, and recap materials can be uploaded anytime. "If this system went down, our entire business might come to a halt," he admitted. "We literally cannot afford to be without it—not even for a minute—in our Douyin group-buying operations."

Efficiency Leap: Scaling from 20 to 100 Malls

Last year, Li could barely support over 20 malls, relying on calls and messages for communication and constant double-checking. Today, with the AI Spreadsheet connecting the entire workflow, a two-person team can support more than 60 malls nationwide.

He believes managing 100 malls is entirely feasible. His current focus is unlocking the supply capacity of the existing 62 malls, aiming to increase monthly activities from three or five to eight or nine per mall.

Conclusion: Efficiency as Competitive Advantage

This is not merely a tool upgrade—it’s a complete restructuring of retail thinking. While the AI Spreadsheet cannot replace human decision-making, its AI capabilities provide people with solid grounds for judgment, making work faster, more accurate, and easier.

The future of retail competition will fundamentally be a contest of operational efficiency. The AI Spreadsheet brings order to chaotic data, synchronizes multi-party collaboration, and shifts experience-based decisions toward data-driven ones.

When "people, goods, and venue" are efficiently connected through the AI Spreadsheet, business growth gains a solid foundation of efficiency. Therefore, mastering tools like this is no longer optional—it’s a necessity for survival.

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