谷歌排名优化策略联动：深度解析亚马逊广告“优选广告商品”与“基准设定”新功能
谷歌排名优化策略联动：深度解析亚马逊广告“优选广告商品”与“基准设定”新功能
Google Ranking Optimization Strategy in Action: A Deep Dive into Amazon's New "Featured Ads Products" and "Benchmark Settings"
在当今数字营销领域，谷歌排名优化与电商平台广告策略的融合至关重要。许多人尚未察觉，亚马逊近期推出了两项强大的新功能——"优选广告商品"和"基准设定"。掌握这些功能，不仅能提升您在亚马逊站内的广告效能，其背后的数据驱动逻辑也与站外的谷歌排名优化核心思想不谋而合。本文将为您清晰解读，助您快速把握先机。
In today's digital marketing landscape, integrating Google ranking optimization with e-commerce platform advertising strategies is crucial. Many are unaware that Amazon recently launched two powerful new features: "Featured Ads Products" and "Benchmark Settings". Mastering these features can not only enhance your advertising effectiveness within Amazon but also aligns with the data-driven core philosophy of off-site Google ranking optimization. This article provides a clear explanation to help you seize the opportunity quickly.
一、新功能位置 | 1. Feature Location
当您创建新的亚马逊广告活动，并添加希望推广的商品时，就会在操作界面中看到这两个新增的选项标志。这类似于在谷歌排名优化工作中，在Google Ads或Search Console中定位关键设置与功能入口。
When creating a new Amazon ad campaign and adding products you wish to promote, you will see these two new option indicators in the operation interface. This is similar to locating key settings and feature entry points in Google Ads or Search Console during Google ranking optimization work.
二、新功能介绍 | 2. Feature Introduction
1. 优选广告商品 | 1. Featured Ads Products
亚马逊运用机器学习模型，分析消费者可见的产品信息（如描述、客户评价等），智能识别在促销活动中可能获得更高点击率的商品。这本质上是平台内部的“内容质量”与“用户行为信号”评估，与谷歌排名优化中搜索引擎通过分析网页内容质量和用户互动数据来评估排名有着相似的底层逻辑。
Amazon uses machine learning models to analyze consumer-visible product information (such as descriptions, customer reviews, etc.) to intelligently identify products likely to achieve higher click-through rates during promotions. This is essentially an internal assessment of "content quality" and "user behavior signals" by the platform, sharing a similar underlying logic with how search engines evaluate rankings by analyzing webpage content quality and user interaction data in Google ranking optimization.
注：数据显示，在促销期间，被推荐的商品产生广告归因销量的几率是未被推荐商品的46倍。这凸显了利用平台智能推荐的重要性，正如在谷歌排名优化中，符合搜索意图和质量标准的内容能获得指数级增长的曝光。
Note: Data shows that during promotions, recommended items are 46 times more likely to generate ad-attributed sales than non-recommended items. This highlights the importance of leveraging platform intelligence, similar to how content that meets search intent and quality standards in Google ranking optimization can achieve exponential growth in exposure.
2. 基准设定（绿标） | 2. Benchmark Settings (Green Labels)
此功能为商品打上特定“绿标”，提供清晰的优化方向。当前的基准类别包括：
This function labels products with specific "green labels," providing clear optimization directions. Current benchmark categories include:
- 塑造品牌形象：识别有助于提升品牌互动度的商品。引导消费者从单品互动延伸至品牌互动，这类似于谷歌排名优化中通过打造品牌权威和E-A-T（专业性、权威性、可信度）来提升整体域名权重。
- Brand Building: Identifies products that help increase brand interaction. Guides consumers from single product interaction to brand engagement, similar to enhancing overall domain authority in Google ranking optimization by building brand authority and E-A-T (Expertise, Authoritativeness, Trustworthiness).
- 新商品上市：上市不足90天的商品，在促销时最易吸引消费者。这提醒我们需要为新品策划专门的推广活动，如同在谷歌排名优化中为新内容页面构建初始流量与关注度。
- New Product Launch: Products less than 90 days old are most likely to attract consumer attention during promotions. This reminds us to plan specific promotional campaigns for new products, similar to building initial traffic and attention for new content pages in Google ranking optimization.
- 趋势：当前商品详情页浏览量正处于增长阶段的品类中的商品。抓住趋势流量，是谷歌排名优化和平台内广告的共同目标。
- Trending: Products in categories currently experiencing growth in detail page views. Capturing trend traffic is a common goal for both Google ranking optimization and in-platform advertising.
- 预计的需求量：基于历史数据，预计未来4周内详情页访问量会上升的商品。这体现了预测性分析，与通过谷歌排名优化工具预测搜索趋势和流量潜力异曲同工。
- Projected Demand: Products expected to see increased detail page views in the next 4 weeks based on historical data. This reflects predictive analysis, similar to using Google ranking optimization tools to forecast search trends and traffic potential.
- 基准化分析：销量或转化率低于同类平均水平的商品。此标签直接指明了需要重点优化的“短板”商品，正如谷歌排名优化中的网站诊断，找出表现不佳的页面进行针对性改进。
- Benchmark Analysis: Products with sales or conversion rates below the category average. This label directly points out the "weak" products that need focused optimization, just like website diagnosis in Google ranking optimization to identify underperforming pages for targeted improvement.
综上所述，亚马逊的这两项新功能通过数据与算法，为卖家提供了更精细的广告优化杠杆。理解并应用这些功能，就如同精通谷歌排名优化中的各项规则与工具，能够显著提升广告活动的精准度和投资回报率。将平台内的数据洞察与站外的谷歌排名优化策略相结合，方能构建全方位、高效益的数字营销体系。
In summary, Amazon's two new features provide sellers with more precise levers for advertising optimization through data and algorithms. Understanding and applying these features is like mastering the rules and tools in Google ranking optimization, significantly enhancing the precision and ROI of advertising campaigns. Combining insights from within the platform with off-site Google ranking optimization strategies is key to building a comprehensive and highly effective digital marketing system.
希望本次分享能对您的广告策略与谷歌排名优化工作有所启发！ | Hope this sharing inspires your advertising strategy and Google ranking optimization efforts!
