Aspect-based Analysis of Advertising Appeals for Search Engine Advertising
This work assists ad creators in writing more persuasive ad texts for search engine advertising, but it is incremental as it applies an existing model to a new dataset.
The paper tackled the problem of identifying effective advertising appeals (A$^3$) for different industries in search engine advertising, and found that different industries have unique effective A$^3$ and their identification helps estimate advertising performance.
Writing an ad text that attracts people and persuades them to click or act is essential for the success of search engine advertising. Therefore, ad creators must consider various aspects of advertising appeals (A$^3$) such as the price, product features, and quality. However, products and services exhibit unique effective A$^3$ for different industries. In this work, we focus on exploring the effective A$^3$ for different industries with the aim of assisting the ad creation process. To this end, we created a dataset of advertising appeals and used an existing model that detects various aspects for ad texts. Our experiments demonstrated that different industries have their own effective A$^3$ and that the identification of the A$^3$ contributes to the estimation of advertising performance.