Automated bidding vs manual bidding strategies in search engine marketing: a keyword efficiency perspective

Pingjun Jiang ()
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Pingjun Jiang: La Salle University

Journal of Marketing Analytics, 2025, vol. 13, issue 1, No 7, 82-95

Abstract: Abstract 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.

Keywords: Keyword research; Keyword efficiency; Manual bidding; Automated bidding; AI in marketing; Search engine marketing; Data envelopment analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1057/s41270-023-00260-4

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