Baidu AI Drives the Second Growth of "Deep Distribution"

-01- Baidu AI Cloud Accelerates Industrial Intelligence Upgrades This year, Baidu AI Cloud upgraded its architecture: at the bottom is Baidu Brain, Baidu's core technology engine, including the basic layer, perception layer, cognitive layer, and security. Baidu Brain has served over 2.1 million developers, with daily calls exceeding one trillion. In the middle is the platform, including the general basic cloud platform, AI middle platform, knowledge middle platform, as well as scenario-specific platforms and other key components. On the top, intelligent applications and solutions empower various industries, driving the implementation of smart cities, intelligent transportation, smart finance, smart energy, smart healthcare, intelligent vehicles, industrial internet, and intelligent manufacturing. For the fast-moving consumer goods (FMCG) industry, with its trillion-yuan market scale and the pain points in marketing management, channel management, and the demand for digital transformation, Baidu AI Cloud's AI technologies and product solutions can properly address and respond to these needs.

-02- The Current State and Future of Deep Distribution In today's highly developed e-commerce environment, 80% of sales for most FMCG manufacturers still come from offline channels. The distribution points of offline channels are mostly in third-tier and below markets. Given this channel characteristic, "deep distribution" has long become the mainstream model for FMCG companies to achieve sales and performance growth in offline channels. How to better implement "deep distribution"? In the past, the traditional approach required building a relatively complete frontline team to conduct blind market sweeps and product placement, which involved significant human resources and cost investment. The current market's competition from job opportunities in other industries also affects FMCG companies' ability to build a stable and effective sales force. Secondly, in the sales process of frontline sales representatives, issues such as false visits, effective working hours, and the quality of promotion plan execution generally suffer from low personnel efficiency, which is an indisputable fact. Beyond "personnel efficiency," "cost-effectiveness ratio" is also an urgent issue for FMCG manufacturers. Data shows that sales and expense investment do not grow proportionally. Whether it is the human-wave tactic reflected in deep distribution or the high channel and distribution expenses, "efficiency and effectiveness" are the eternal core pursuits of FMCG companies. Baidu AI Cloud's artificial intelligence technology and services can effectively help companies transform from traditional "large-scale distribution" to "precise deep distribution," by helping manufacturers uncover more potential uncovered outlets, thereby achieving "targeted store expansion" and "targeted distribution." Ultimately, it assists manufacturers in shifting from the traditional business model of "seeking growth from channels" to a new deep distribution model of "seeking growth from personnel efficiency and cost-effectiveness," driving a second wave of performance growth!

-03- Around the Logic of Offline Channel Performance Growth Using AI PaaS to Help Manufacturers Succeed The performance growth of FMCG in offline channels involves four core process indicators: store coverage, visits, display, and sell-through. Baidu AI Cloud has launched a "FMCG Industry Solution" based on AI PaaS and data services to address this logic. In short, Baidu AI Cloud's FMCG industry solution aims to help FMCG manufacturers "find the right stores," "go to the right stores," and "hold the position," ultimately achieving efficient and precise distribution, as well as effective terminal sell-through through more refined in-store execution management.

1. Intelligent Store Expansion: Helping FMCG Companies "Find" the Right Stores for Precise Distribution First, sales growth comes from product placement in stores. There are over 6 million outlets in China's offline channels. Given such a large number, not all stores can be covered by FMCG companies, nor is every store valuable for their products. At the same time, against the backdrop of severe staff turnover, how to maximize store coverage and distribution with existing manpower, and improve overall distribution efficiency and effectiveness, is a question every FMCG manufacturer must consider. Baidu AI Cloud's "Intelligent Store Expansion Product" can effectively solve these problems. First: Obtain a precise database Baidu AI Cloud, based on Baidu Maps' POI basic database, performs secondary classification for FMCG distribution channel types, providing manufacturers with a more precise list of outlets in target areas. Second: Deduplicate the store database Using Baidu Brain's NLP technology, it can quickly deduplicate and clean the outlets captured by Baidu Maps within a region/city against the outlets already covered in the manufacturer's system. Third: Score store potential At the same time, based on Baidu's big data capabilities, it can perform potential analysis and evaluation for each uncovered store after deduplication and cleaning, ultimately calculating a "store sales potential value ranking" to help manufacturers reasonably and effectively carry out store expansion and performance planning.

2. Intelligent Scheduling: Let Sales Reps "Go" to the Right Stores to Improve Visit Efficiency After expanding new outlets, the next step is outlet visits and sales work. Using Baidu Maps' travel planning capabilities and Baidu's deep learning algorithms, it helps companies solve the optimal person-store correspondence plan at the technical level. Combined with rolling sales data, the algorithm is optimized to finally obtain not only the planning and methods of visit routes, but also how many people need to be deployed in the market to meet market demand, maximizing personnel efficiency.

3. Intelligent In-Store Insights: Making Outlet Data Real and Effective, Enabling Intelligent Market Decisions After finding the "right stores" and "going to the right stores," the next step is how to do well in in-store execution management to achieve the core purpose of terminal sell-through. Baidu AI Cloud's Intelligent In-Store Insights product, through AI capabilities such as product recognition, photo recognition, and shelf stitching, effectively helps brands manage the visit-sales process in a refined manner, obtain real-time and accurate outlet data, guide personnel at all levels, and complete business store decision planning. In the "Intelligent In-Store Insights" solution, EasyDL Retail Edition plays a crucial role. EasyDL Retail Edition is a self-service model training platform for in-store execution objects in the FMCG industry. The objects include but are not limited to: detection models for own-brand SKUs, competitor SKUs, cut boxes/stack displays/freezers/end caps and other paid or visual merchandising scenarios, as well as detection models for various POSM promotional materials. At the same time, the small-scale training data mode on which EasyDL Retail Edition is based perfectly matches the real-time market rhythm of FMCG manufacturers, quickly training commercially usable AI detection models. Finally, EasyDL Retail Edition can also output key business indicators for in-store display and execution, such as shelf share, display position, distribution rate, and empty spaces. The above are Baidu's solutions for the FMCG industry, including intelligent store expansion, intelligent scheduling, and intelligent in-store insights. Currently, Baidu AI Cloud has cooperated with multiple FMCG system service providers and brand customers, using artificial intelligence and big data to help companies achieve digital transformation and improve the efficiency and effectiveness of deep distribution in offline channels.

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