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Drivers and prediction of organic search engine ctr: the impact of differently phrased titles
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| 1.89 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
33% of web traffic in the $5.7 trillion e-commerce industry originates from organic search
engines. Thus, website providers benefit from understanding the drivers of click-through rates
(CTR) on organic searches. However, existing literature focuses on position as the primary
CTR influence, disregarding other result page characteristics. To solve this problem, we
conduct an elaborate data analysis and determine suitable CTR prediction modeling
techniques. We discover novel patterns impacting CTR and find tree-based models to
outperform state-of-the-art deep-learning models.
Furthermore, we conduct an NLP-based analysis of result titles and show that particular
formulation patterns can significantly influence a result’s CTR.
Descrição
Palavras-chave
Organic click-through rate Ctr prediction E-commerce Serp features Shap Nlp