Generational responses to guerrilla marketing: examining brand associations across Generations Z and Y
Bibliographic record
Abstract
Purpose This study aims to examine generational differences in the impact of guerrilla marketing on brand perceptions in Azerbaijan, focusing on Generations Z and Y. It investigates how unconventional marketing tactics, such as guerrilla marketing, influence brand trust and performance, particularly in emerging markets. Clarifying how these age groups respond to guerrilla marketing, this research aims to provide insights for marketers on optimizing engagement strategies that align with cultural and generational preferences. Design/methodology/approach A quasi-experimental research design was used, involving 196 participants divided into control and experimental groups. Participants were exposed to guerrilla marketing campaigns, and their brand trust and performance perceptions were measured. The study applied statistical analysis to compare generational responses, assessing the effectiveness of unconventional marketing strategies. This approach permitted a controlled examination of how different age groups perceive and react to guerrilla marketing tactics in an emerging market context. Findings The study revealed that Generation Z responds positively to guerrilla marketing’s creativity and disruptive nature, while Generation Y prefers traditional marketing approaches. These findings highlight the varying effectiveness of unconventional marketing strategies across age groups, emphasizing the need for tailored marketing approaches to maximize brand trust and performance in emerging markets. Originality/value This research contributes to the literature on generational marketing by providing empirical evidence on the effectiveness of guerrilla marketing in an emerging market and offers practical insights for marketers seeking to engage diverse generational cohorts through innovative, culturally aligned strategies. By highlighting the differing perceptions of Generations Z and Y, this study underscores the importance of adapting marketing tactics to specific audience preferences, enhancing brand positioning in developing economies, such as Azerbaijan.
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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) | 0.003 | 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".