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Placer.ai:五大策略释放零售媒体网络的潜力(2023)(英文版)(17页).pdf

上传人: Kell****reet 编号:118694 2023-03-16 17页 1.35MB

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1、February 2023Five Strategies toUnlock the Potential ofRetail Media NetworksRetail media networks are taking the advertising world by storm.We dove into the data to see how retailers and advertisers canleverage foot traffic analytics to win at the retail media game.Table of ContentsFebruary,20231Tabl

2、e of Contents2The Rise of Retail Media31.Finding the Right Markets with C-Stores47-Eleven and Caseys Take the Retail Media Plunge4Unique Visitors=Ad Impressions?4Matching Campaigns to Local Markets5Zooming in on Individual Stores72.Optimizing Advertising in an Omnichannel World8Reaching Home Improve

3、ment Fans with Home Depot9The Suburban DIY Advantage9Creating Hyper-Local Audience Segmentations113.Comparing Venues Captured and Potential Audiences12Diving in with Kroger and Albertsons12Pinpointing Venues that Draw Health or Beer Enthusiasts124.Keeping Tabs on Prime Time14Different“Prime Times”Fo

4、r Different Retailers155.Unlocking Advertising Potential With Cross-Shopping Data16Leveraging Location Intelligence to Optimize Retail Media Network Performance17Key Takeaways17 2023 Placer Labs,Inc.|More insights at placer.ai|2The Rise of Retail MediaRecently,a new innovation has taken the advertis

5、ing world by storm:retail medianetworks(RMNs).These advertising platforms allow third-party brands to market toretailers customers through the retailers various sales and marketing channels.Andwhile companies like Amazon that pioneered the trend focused on offering theire-commerce channels to advert

6、isers,a growing number of businesses are discoveringthe vast untapped potential of their brick-and-mortar fleets.Indeed,the growing embrace of omnichannel marketing has contributed to a blurringof the line between on-and offline shopping experiences.And many large retailchains still receive most of

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本文主要探讨了零售媒体网络(RMN)在广告领域的兴起,以及如何利用位置智能优化零售媒体网络的表现。主要观点包括: 1. 零售媒体网络通过利用零售商的物理店面和在线渠道,为品牌提供了一个接触消费者的平台,尤其是在消费者购物和购买意愿高涨时。 2. 位置智能数据,如人流量分析,可以帮助零售商和广告商更好地理解不同市场和行业中的消费者行为,从而优化广告策略。 3. 文章通过分析7-Eleven、Casey's、Home Depot、Kroger和Albertsons等零售商的案例,展示了如何利用位置智能数据来匹配广告活动与特定市场,以及如何根据消费者的交叉购物习惯来定制广告。 4. 文章还强调了不同零售商有不同的“黄金时段”,例如Hy-Vee在周末下午和BJ's在周末中午时段人流量较大,这为零售商提供了调整广告策略的依据。 5. 总的来说,位置智能数据对于零售媒体网络的成功至关重要,它为零售商和广告商提供了深入理解消费者行为所需的洞察力。
零售媒体网络如何利用位置智能优化广告效果? 不同零售商如何通过分析人流量数据来定制广告策略? 零售商如何利用消费者跨店购物数据来提升零售媒体网络效果?
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