W32 - New Thinking on Merchant Business

Recently, the PM’s field research visits to merchants for the second half of the year concluded. After reviewing some visit notes and initial conversations with the PM, I have gained some new insights into the business.

Large B (enterprise merchants) and small B (small merchants) are different and must be treated separately.

Large B needs office efficiency, standardization, and enterprise process management.Some examples from the visits: multi-location merchants prefer to withdraw pending settlement funds from Meituan and consolidate transaction flows from different channels into a single account for unified management, so large B has a stronger need to withdraw funds. Large B’s management is more granular; on the merchant app, operations are typically performed by finance or operations roles. Finance cares only about reconciliation, while operations focuses on marketing and customer traffic. They are often not the restaurant owners, so interest in interest-bearing services like Shengyibao is limited.

The biggest need for small B is customer acquisition, followed by wealth management.They also have funding and enterprise process needs, but not as strong as large B. We observed that many small B purchase small-scale promotion packages, but their operational capabilities vary widely. With fewer locations, merchants pay more attention to interest-bearing settlement funds. From feedback, most people confuse the two products “Shengyidai” and “Shengyibao,” which presents a valuable point of entry.

On the funding need side, both small B and large B have varying degrees of demand; compared to large B, small B’s demand for capital is looser. Due to working capital turnover needs and disruptions from the pandemic—especially for merchants with strongly cyclical revenue, such as those tied to travel or events—access to financing is an absolute necessity. Shengyidai has huge potential; as the flagship product of financial services, it should be positioned as a profit-capturing tool, while other financial services are more about operating traffic. It’s like paid search to Baidu, or games to Tencent. However, feedback shows Shengyidai has exposed painful shortcomings: inability to lend, lending too little, and inability to dynamically grant credit based on a merchant’s basic operating information and scale. Externally, its credit model still relies on pure personal information and feels somewhat “traditional,” which of course relates to our current business stage—this is just a snapshot. Below I’ll share some thoughts on Shengyidai’s future evolution.

I recently read Professor Zeng Ming’s Intelligent Commerce. His methodology for judging future commerce is particularly applicable to the Shengyidai business model. Ant Microloan is the product we benchmark against, and Ant Microloan can share a wide range of potential customer data beyond merchants’ basic operating information, including many behavioral data points. All data are dynamic “live data.” For example: what items these Taobao sellers are currently selling, whether their business is doing well; how diligent a seller is in managing a store (customer service response speed on Wangwang, daily operating hours, etc.); whether there have been past integrity issues, and so on. Credit lending, an ancient and complex commercial activity, has been abstracted and minimally expressed as a human–computer input box. We have 7 million merchants and tens of millions of daily orders—massive bilateral marketplace data that creates enormous data pressure. But in financial products like Shengyidai, that has not been converted into powerful momentum—“intelligence” is still in its infancy.Figuring out how to integrate data, algorithms, and product into a single whole should be an important iteration direction for Shengyidai.