中国零售消费行业生成式AI及数据应用研究报告

Core Viewpoint - The retail industry is transitioning from high-speed growth to stock competition, necessitating the digital transformation of "people, goods, and venues" through the integration of generative AI and data applications to reshape growth trajectories [1][2][44]. Group 1: Digital Transformation in Retail - The shift from a demand-driven economy to a member-based economy is evident as consumer rationality increases, prompting companies to focus on user retention and value extraction [4]. - Retailers must leverage digital technologies to enhance consumer insights, expand touchpoints, and optimize product selection and promotion based on data [2][6]. Group 2: Generative AI and Data Applications - Generative AI and data governance are crucial for maximizing AI value, with 71% of companies planning to strengthen data-driven decision-making [20][23]. - The integration of generative AI in marketing and customer service is leading to significant efficiency improvements, with over 90% of companies adopting these technologies [48][51]. Group 3: Sector-Specific Insights - In the beauty sector, domestic brands are rapidly increasing market share from 43.7% in 2022 to 55.7% in 2024, utilizing KOLs and UGC to establish a marketing loop [9]. - The footwear and apparel industry faces intense competition, requiring companies to develop proprietary product capabilities and brand recognition to stand out [11]. - The home goods sector is shifting towards overseas expansion, with companies focusing on building their own brands rather than merely exporting [14][66]. Group 4: Global Market Expansion - 93% of retail companies are pursuing overseas business, with Asia-Pacific, Europe, and North America as primary targets due to their high purchasing power and mature channels [66]. - Generative AI is facilitating localization efforts by overcoming language and cultural barriers, enabling efficient marketing and customer service in foreign markets [69]. Group 5: Supply Chain and Decision-Making Enhancements - Generative AI is optimizing supply chain efficiency by improving demand forecasting and real-time decision-making, with efficiency improvements ranging from 10% to 30% [62]. - The integration of generative AI in internal decision-making processes is transforming traditional experience-driven approaches into data-driven strategies [42][56].