We utilize data envelopment analysis to evaluate and compare the pricing efficiency of keywords in the Google-sponsored search markets, specifically in relation to manual bidding strategies and automated bidding strategies. Two totally different sets of efficiency scores are obtained from Google Ads by using extensive data from a company in the online apparel retailing industry. Contrary to the big buzz in the industry, the automated bidding strategy does not improve the average efficiency of keywords. Manual bidding rewards efficiency for keywords more productive of transactions, revenue, and clicks. Automated bidding rewards efficiency for keywords more on cost per click, bounce rate, and E-commerce conversion rate. Automated bidding increases efficiency scores with apparel keywords consisting of words of “color” and “quality attributes.” Manual bidding has high-efficiency scores with keywords including words “promotion related,” “gender,” and “style attributes.” Manual bidding works better for modified match types.

我们利用数据包络分析来评估和比较 Google 赞助的搜索市场中关键字的定价效率，特别是与手动出价策略和自动出价策略相关的定价效率。通过使用在线服装零售行业公司的大量数据，Google Ads 获得了两组完全不同的效率得分。与业界的热议相反，自动出价策略并没有提高关键词的平均效率。手动出价奖励关键字的效率，提高交易、收入和点击的效率。自动出价在每次点击成本、跳出率和电子商务转化率方面更加奖励关键字的效率。自动出价可通过由“颜色”和“质量属性”等词组成的服装关键词提高效率得分。人工出价对于“促销相关”、“性别”、“风格属性”等关键词的效率得分较高。手动出价更适合修改后的比赛类型。