由于数据零散,澳大利亚品牌在AI个性化方面落后,但社区发展方案和清洁数据有助于早期采用者在AI驱动的购物增加的情况下取得成功。 Australian brands lag in AI personalization due to fragmented data, but CDPs and clean data help early adopters succeed amid rising AI-driven shopping.

由于客户数据支离破碎、专业知识有限和数据统一投资不足,澳大利亚和全球品牌在扩大个人化的AI方面面临着障碍。 Australian and global brands face hurdles in scaling AI for personalization due to fragmented customer data, limited expertise, and underinvestment in data unification. 只有8%的澳大利亚品牌使用人工智能优化,5%的品牌使用人工智能优化,5%的品牌用于个性化,受到客户观点不完全和身份分辨率差的影响。 Only 8% of Australian brands use AI for optimization, and 5% for personalization, hampered by incomplete customer views and poor identity resolution. 82%的零售业领袖表示他们才刚开始有效地激活数据。 Despite growing interest, 82% of retail leaders say they’re only beginning to activate data effectively. 客户数据平台(CDPs)通过制作统一、实时的概况来提供帮助,用户了解客户的可能性是客户的两倍,采用以客户为主的AI的可能性是客户的三倍。 Customer Data Platforms (CDPs) help by creating unified, real-time profiles, with users twice as likely to understand customers and three times more likely to deploy AI in customer-facing roles. 像New Look这样的早期应用者通过解决重复的个人资料取得了成功. Early adopters like New Look have seen success by resolving duplicate profiles. 与此同时,购物者越来越多地使用AI工具,如ChatGPT和Google的AI概览,以发现产品,在2025年总理日期间,AI产生的流量猛增了3,300%。 Meanwhile, shoppers increasingly use AI tools like ChatGPT and Google’s AI Overviews to discover products, driving a 3,300% surge in AI-generated traffic during Prime Day 2025. 然而,过时的系统很难提供所需的结构化、实时的AI代理数据,这有可能降低能见度。 However, outdated systems struggle to deliver the structured, real-time data AI agents need, risking reduced visibility. 将清洁、机器可读目录和测试性对话商务列为优先事项的品牌,随着AI重塑电子商务,其地位要好一些,目前价值接近1.5万亿美元。 Brands that prioritize clean, machine-readable catalogs and test conversational commerce are better positioned as AI reshapes e-commerce, now nearing $1.5 trillion in value.