JSAI2025

Presentation information

General Session

General Session » GS-10 AI application

[1M5-GS-10] AI application:

Tue. May 27, 2025 5:40 PM - 7:20 PM Room M (Room 1008)

座長:前川 知行(静岡大学)

5:40 PM - 6:00 PM

[1M5-GS-10-01] The Impact of TV Commercial Favorability on Consumer Behavior Funnel

○Takuma Kawada1, Keisuke Okuno1, Shun Onozawa1, Yusuke Tanaka1, Hiroaki Inaba1, Kan Ogoshi1, Yuta Sawada1, Ryuichi Ishikawa2, Harang Romain3, Yusuke Miyao3, Shogo Yonekura3, Namgi Han3, Satoshi Nakagawa3 (1. DENTU INC., 2. Dentsu Digital INC., 3. Univ. of Tokyo)

Keywords:Funnel, Favorability, Text mining

We collected data from Video Research Ltd.'s "Creative Carte", a large-scale CM survey dataset (3,387 CMs, ~1.8 million responses), and conducted path analysis to quantitatively analyze the impact of TV commercial (CM) favorability on consumer purchase behavior using a purchase funnel. The analysis examined the influence of CM favorability and persuasiveness on each stage of the purchase funnel (awareness, interest, and purchase intention). Results showed that CM favorability had a remarkably high overall effect (0.701) on purchase intention. Text mining was performed on viewers' free-form responses, utilizing a large language model and principal component analysis, suggested the importance of factors contributing to "intuitive appeal," such as visual elements, in effective CMs. Conversely, the analysis indicated that factors such as insufficient or unclear expressions could potentially detract from CM effectiveness. This research provides empirical evidence of CM favorability's significant impact on consumer purchase behavior, particularly through factors such as intuitive appeal and expression quality. These findings offer practical insights for advertisers aiming to enhance CM performance.

Authentication for paper PDF access
A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.

Password