The Perception of Cosmetic Brand Names among Saudi Consumers: Implications for Intercultural Advertising
Bibliographic record
Abstract
As the global cosmetics market expands rapidly, the importance of cultural sensitivity in advertising becomes evident. However, certain brand names used internationally may unintentionally offend specific audiences due to linguistic and cultural differences. This study examines the perceptions and attitudes of 770 Saudi individuals toward brand names deemed inappropriate or provocative within the Saudi sociocultural context. The research aims to shed light on the implications for intercultural advertising targeting Saudi consumers. The findings reveal strong negative reactions to brand names with sexual references, with respondents using terms such as "disgusting," "shocking," and "shameless" in their descriptions. The study also highlights the impact of these names on religious and moral values cherished in Saudi society. The implications for international cosmetic companies targeting Gulf consumers include careful consideration of name translations and connotations in Arabic-speaking markets, involvement of local expertise in advertising campaigns, and enhanced cultural sensitivity training for marketing professionals operating abroad. This research contributes to the understanding of intercultural advertising and provides insights for improving cultural competence in English language education, particularly in the context of teaching English for advertising. By raising awareness of these issues, appropriate choices of brand identifiers can be discussed to benefit both businesses and target audiences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".