  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.

Computation and Language