Sou Hu Cai Jing·2025-09-11 23:41Core Insights - The article discusses a transformative shift in the local life services sector driven by AI, particularly through Alibaba's Gaode Map launching the "Street Ranking" system, which aims to reconstruct the trust mechanism in offline consumption [1][4]. Group 1: Innovation in Evaluation System - Unlike traditional ranking systems that rely on user reviews and ratings, the "Street Ranking" incorporates behavioral data such as navigation, store visits, repurchase rates, and willingness to travel across cities [3][4]. - The system captures real consumer behavior through Gaode's daily 120 million life service searches and over 1.5 billion kilometers of navigation data, enhancing the accuracy of evaluations [3]. - The introduction of various sub-rankings like "Repeat Customer Ranking" and "Tire Wear Ranking" reflects user repurchase rates and cross-city consumption willingness, providing personalized guidance for different user needs [3][4]. Group 2: Impact on Businesses - This transformation signifies a complete shift in operational logic for businesses, moving away from a cycle of needing to "cheat the rankings" to gain traffic, allowing quality small businesses to build long-term credit assets through genuine user behavior [4][8]. - The "Street Ranking" system reduces marketing costs and enables the concept of "good products do not fear being hidden" to thrive [4]. Group 3: Strategic Development - Gaode's "Street Ranking" is part of a broader strategy to enhance Alibaba's local life services, complementing other business lines like Taobao's instant retail and Ele.me's food delivery, creating a comprehensive "buy, deliver, find" experience [8]. - The launch of the "Good Store Support Plan," which includes a 200 million yuan travel coupon package and 950 million yuan in consumption coupons, aims to lower user costs and support small businesses in establishing a sustainable digital credit system [8]. Group 4: Broader Implications - The deep integration of AI into the trust aspect of offline consumption marks a significant evolution, with potential applications extending beyond dining to retail, entertainment, and tourism [9]. - This shift could redefine industry rules by quantifying metrics like repurchase rates and cross-city visits, positioning AI as a rule-maker in the offline consumption ecosystem [9]. - For cities, this change reorganizes the supply of quality small stores, allowing them to gain visibility through long-term behavioral data rather than short-term traffic [9].