一、品牌

小米汽车上市后首个周末：门店客流近万，试驾排至凌晨3点

小米汽车上市开售后风头不减。3月30日，在SU7上市后的首个周末，上海小米汽车门店有店长透露了最近的“日程表”：“试驾到凌晨3点结束，4点下班，6点到家睡觉，9点又要开始上班。从发布会到现在，每天只能睡两小时。”。几乎所有门店的都挤满了大量观众，门口则排起长龙，有店员坦言，试驾排到凌晨2、3点是常态。

俞敏洪：已要求河南新东方文旅全面停止直播并进行整顿

3月30日晚间，新东方创始人俞敏洪在其抖音账号发文，回应提前去河南直播是为抢董宇辉风头的传言。俞敏洪表示，从未有过要去河南直播的计划，“早在一个月前，东方甄选就已经安排了我4月1日要到武夷山直播。”

俞敏洪称，新东方文旅在每个省都有子公司，都有一个专门传播当地文旅的直播平台，由当地新东方主播进行文旅直播。河南新东方所宣传的直播，是当地直播，并不是他去直播。为消除大家的误解，他已要求河南新东方文旅全面停止直播，并进行整顿。

华为2023年营收7042亿元，净利润870亿元

3月29日，华为发布2023年年报。整体经营情况符合预期：全年实现营业收入7042亿元，净利润870亿元。其中，ICT基础设施业务保持稳健，终端业务表现符合预期，云计算和数字能源业务实现了良好增长，智能汽车解决方案业务开始进入规模交付阶段。

新款iPad计划5月初发布

3月29日电，据知情人士透露，苹果公司的海外供应商已加紧生产该公司期待已久的新款iPad，并计划于5月初发布。此次发布的重点是iPad Pro和iPad Air的改进版本。iPad Pro机型将配备更清晰的新型OLED显示屏，而iPad Air将首次提供12.9英寸屏幕的选项。此举标志着iPad史上最长的无新机型时期结束。

哪吒汽车CEO张勇：接受批评，营销向雷军学习

二、互联网

微信豆和腾讯广告各自推出全域投流产品

微信豆和腾讯广告各自推出了一个全域投流产品，正在做灰度测试。微信豆的产品名叫“全域订单”，腾讯广告的产品名叫“3.0投放端”。这两个产品都具有对视频号账号和视频号直播进行“全域投流”的功能，但外界原本期待的是一个由两个团队合作的产品，而不是两个独立的产品。

微软和OpenAI据悉计划投资1000亿美元建设数据中心项目

3月30日消息，微软、OpenAI正在为一个数据中心项目制定计划，该项目耗资可能高达1000亿美元，其中包括一台名为“星际之门”（Stargate）的人工智能超级计算机，将于2028年启动。

PingPong发起首个TikTok Shop服务商联盟

由PingPong与TikTok Shop携手举办的“2024 TikTok Shop跨境招商大会”在厦门召开。会上成立了首个聚焦TikTok Shop商家的生态服务联盟，并开设生态资源联动和现场对接会，助力企业快速开启TiKTok Shop商机。PingPong合伙人束建琴表示，该联盟将为商家提供覆盖运营全场景在内的一站式生态服务，助力商家以更快的速度、更低的成本、更高的效率开辟增量市场。

支付宝：3月份境外宾客支付宝消费同比涨近10倍

三、广告片

闲鱼推出海鲜市场系列香水

4月1日，闲鱼玩梗推出限定款香水，海鲜市场°5、昆仑煮虾、无人区蛤蜊、鼠尾草与海螺，香水名称分别对应了香奈儿5号、昆仑煮雪、无人区玫瑰、鼠尾草与海盐等知名香水。此外，闲鱼还特地给每款香水像大牌一样做出了调香师点评。

阿迪达斯恶搞鞋盒

最近阿迪达斯在“Confirmed”应用程序上架了一款真鞋盒。根据产品描述，Box Shoe 这款鞋子 模糊产品和包装之间的界限。这款“运动鞋”本质上是传统的蓝色阿迪达斯盒子，前掌处有穿孔和粗鞋带。中足处还有一个翻盖，您可以将脚固定在鞋内。 Clot 创始人兼阿迪达斯合作者陈冠希也分享了 Box Shoe 的宣传图片，但没有迹象表明他的品牌参与了此次发布。

四、趋势洞察

近一年短剧搜索量激增48倍

根据相关数据显示，近一年短剧的搜索量激增48倍，搜索热度呈现指数级增长，尤其在午间及晚间时段成为追剧高峰。年轻人与职场白领成为短剧消费主力，爱情、现代与穿越题材短剧备受欢迎。

相关数据显示，近三年微短剧备案数量和上线数量均远超长剧。2023年，市场共上线超1400部微短剧，连续两年同比增速超50%；微短剧年备案数量保持了近3000部的增长。据不完全统计，微短剧市场产值规模近400亿元，已达到2023年全年电影票房市场70%的“水位线”。

五、海外营销

用AI提升你的零售媒体策略

Harnessing the power of artificial intelligence (AI) is becoming increasingly crucial for crafting effective media strategies that drive results. But how can retail media professionals start integrating AI into their decision-making processes to optimize media plans and achieve their objectives?

Here are some key strategies and considerations for leveraging AI in media decision-making.

Clarify your desired output

At the heart of effective media planning lies a clear understanding of your media parameters and how they work together to achieve results for the product category you are advertising.

Whether increasing brand awareness, driving sales or attracting new customers, defining your media goal is essential as it will inform the combination of media parameters needed to deliver a successful program.

Those parameters can constitute which audiences you should target, the best channels to reach them, how long should you be in market based on desired reach and your available budget, and what type of creative messaging resonates with these groups. By isolating these key media building blocks (i.e., decision points) for your product category, you can align your media strategy with your overarching business objectives.

Leverage the power of data

Data serves as the backbone of AI-driven media decision-making. By analyzing vast datasets encompassing buying patterns, campaign performance metrics and market trends, AI can provide valuable insights to inform the right combination of media parameters for the product category and your objective.

However, to make the takeaway on that combination effective, it requires a comprehensive and consistent media dataset covering dimensions such as product category, campaign objective, channel, audience segment, creative messaging, creative format and start and end dates—or your media building blocks/decision points tied to your product category and objective. Collaborating closely with your data analysts and engineering teams is essential to curating a high-quality dataset that fuels AI-powered insights.

Model plan output

With a robust dataset in hand, AI can analyze various combinations and extrapolate trends to generate recommended media plans tailored to your specific objectives and product categories. From identifying optimal channels and audience segments to isolating creative messaging most likely to resonate with the targeted audiences, AI-driven output can enhance the effectiveness of your media plan. That said, it is still recommended to supplement AI-generated output with new tactics and channels, balancing innovation with proven strategies.

Mitigate pitfalls

While AI offers unprecedented capabilities in media decision-making, it’s crucial to remain mindful of potential pitfalls. The quality and granularity of your data directly impact the accuracy of AI-generated insights. Therefore, conducting thorough quality assurance checks and validating plan outputs against historical performance can help mitigate risks.

Additionally, embracing a culture of continuous testing and learning is essential for refining AI models and optimizing media strategies over time.

Embrace the future of retail media

In an era characterized by rapid technological advancements, AI presents unparalleled opportunities for retail media professionals to elevate strategies and drive meaningful outcomes. By using the power of AI-driven insights and data-driven decision-making, retailers can stay ahead of the curve and deliver compelling experiences that resonate with consumers.