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Drivers and prediction of organic search engine ctr - the effects of serp features and their business implications
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| 2.08 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
33% of web traffic in the $5.7 trillion e-commerce industry originates from organic search
engine results. Thus, website providers benefit from a holistic understanding of the drivers of
click-through rates (CTR) on organic searches to increase traffic. However, providers face a
knowledge gap, as existing literature focuses on position as the primary CTR influence,
disregarding other result page characteristics. To solve this problem, we use an extensive
dataset comprising organic Google result page information. We conduct an elaborate data
analysis highlighting the impact of four categories of result page characteristics before
determining suitable CTR prediction modeling techniques. We discover novel patterns
impacting CTR for each category and find tree-based models to outperform state-of-the-art
deep-learning models.
Furthermore, we reveal particular SERP feature effects on CTR and highlight their possible
business implications.
Descrição
Palavras-chave
Organic click-through rate Ctr prediction E-commerce Serp features