推荐与广告区别

The Difference between a Recommendation and an Ad

A quick thought regarding Facebook’s new Social Adsplatform.

recommendation is something you get from someone who knows something about you. They have seen an item of interest and thought that you might gain some use by it. They give their recommendation freely, knowing that it may do you some good, expecting nothing in return other than perhaps a “thank you”. Recommendations are thus social capital.

The primary reason for a recommendation is a need on the receiver’s side.

An advertisement is something you get from someone who may or may not know something about you. They have an item they want you to be interested in, and hope you might gain some use by it. They give it freely, but they do expect something in return as they are paying for this transaction. Thus they are biased, however small, to give you that ad. Advertisers will never give you what they objectively think is best for you. They’ll give you what they have. Ads are thus economic capital.

The primary reason for an advertisement is a need on the sender’s side.

Facebook cannot give recommendations as long as they accept money from advertisers which constrains the items available for placement. They are being paid to show only certain stuff…not necessarily the stuff that’s best for you, but the stuff made by the people who are giving them money.

To their credit, Facebook doesn’t seem to be using the term “recommendation”…yet.

 

url:http://bokardo.com/archives/the-difference-between-a-recommendation-and-an-ad/

### DSP广告信息流广告区别 #### 技术实现 DSP(需求方平台)是一种技术解决方案,允许广告商通过程序化购买的方式自动竞拍在线展示广告位。这种模式依赖复杂的算法技术栈来实时评估竞价广告库存[^1]。 相比之下,信息流广告通常嵌入在应用或网站的内容流中,如社交媒体动态消息或新闻文章之间。这类广告的技术核心在于如何无缝融入用户体验的同时保持高可见度,并且往往利用机器学习模型优化位置、时间以及个性化推荐以提升互动率[^2]。 #### 用户体验 对于用户而言,信息流广告因其自然地融合于内容之中而显得更加隐蔽平滑,减少了突兀感,使得浏览者更可能无意间注意到这些推广内容而不感到被打扰。 然而,DSP驱动下的横幅或其他形式的显示广告可能会出现在页面的不同区域,有时会因为其显眼的位置引起用户的反感;尽管如此,DSP能够基于详细的受众数据精准定位目标群体,从而提供更具相关性的广告给最终消费者. #### 广告投放机制 在DSP平台上,广告主可以根据特定的目标市场参数设定预算并参公开拍卖过程中的每一次印象竞争。一旦赢得某个广告位,则该条目即刻展现给选定的访问者群体前。这种方式极大地提高了效率并且降低了成本,因为它只针对那些最有可能转化的人群进行投资。 另一方面,信息流广告服务提供商一般采用固定价格或者按点击收费(CPC)模式销售广告空间。它们依靠内部算法决定何时何地向谁推送哪些类型的促销材料——这取决于个人资料特征比如兴趣爱好、地理位置等因素。因此,虽然不是完全自动化的过程,但仍然能有效触达潜在顾客并促进品牌认知度的增长。 ```python # 示例代码用于说明两种方式的数据处理逻辑差异 (伪代码) def dsp_ad_targeting(user_data): """模拟DSP广告定向""" target_users = [] for user in all_users: if meets_criteria(user, user_data): # 自定义匹配规则 bid_price = calculate_bid(user) win_auction(bid_price) show_ad_to_user(user) def feed_ad_placement(feed_items, user_profile): """模拟信息流广告放置""" ad_item = select_relevant_ad(user_profile) for item in feed_items: insert_into_feed(item, ad_item) # 将广告项随机插入到内容列表中 ```
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