Guan Cha Zhe Wang·2025-10-11 11:40Core Insights - Offline dining merchants have unexpectedly become the focal point in this year's local lifestyle battle, with the launch of Gaode's "Street Scanning List" injecting new vitality into the market [1][3][10] - The "Street Scanning List" has achieved over 400 million users within 23 days of its launch, indicating strong acceptance from both merchants and consumers [7][10] - The competition in the local lifestyle market is evolving into a battle for new infrastructure, focusing on building a credible offline service credit system [6][10][11] Summary by Sections Market Dynamics - During the recent National Day and Mid-Autumn Festival holidays, Gaode's initiatives drove over 100 million customer visits to offline dining establishments [3][8] - Over 70% of the "must-eat" restaurants saw a more than 200% increase in traffic compared to the pre-holiday period, with many being long-established local eateries [3][11] Competitive Landscape - Gaode's "Street Scanning List" is positioned as a new type of infrastructure, akin to logistics networks and payment systems, enhancing its commercial and social value [5][6] - The competition between Gaode and Meituan is not just about market entry but also about establishing a new service credit system that can serve various industries [6][10] User Engagement and Growth - The "Street Scanning List" has rapidly gained traction, with a user base exceeding 400 million shortly after launch, reflecting a shift in consumer habits and preferences [10][11] - Gaode's promotional strategies, including a support plan for merchants and waiving annual fees for restaurant listings, have led to a 631% increase in new merchant registrations within 24 hours of announcement [8][10] Future Outlook - The local lifestyle market still holds significant untapped potential, as evidenced by the growth in dining consumption in cities like Hangzhou, which saw a 17.1% increase in spending during the holiday period [11] - The competition in the local lifestyle sector is expected to intensify, focusing on AI-driven recommendations and governance to filter out low-quality information [10][11]