Insights from Brand Associations: Alcohol Brands and Automotive Brands in the Mind of the Consumer
Bibliographic record
Abstract
Purpose -The purpose of this paper is to show how the analysis of brand associations can help to elaborate the cognitive position of a brand.The paper compares brand associations of Hungarian consumers in two product categories, automobiles and alcoholic drinks, in two datasets. Design/Methodology/Approach-To obtain a detailed picture of a brand's position in the mind of consumers, free brand associations to 10 alcohol and 13 automotive brands were collected, the associations were categorized, and their frequency and distribution analyzed.K-means clustering was used to identify similarities.Associations within and across product categories are compared, and shifts in associative structures are described.Findings and implications -The paper shows that associative structures diff er across product categories.The two datasets (collected in 2011-2012 and 2015-2016) highlight that brand associations and thus a brand's image change over time and that change is not only due to marketing communication -rather, media news and personal experiences also lead to change.Results confi rm that positive and negative associations are likely to be connected to each brand; however, Fetscherin and Sažetak Svrha -Svrha je rada pokazati kako analiza asocijacija na marku može pomoći pri kognitivnom pozicioniranju marke.U radu se uspoređuju asocijacije na marku mađarskih potrošača u dvjema kategorijama proizvoda, automobila i alkoholnih pića,i to u dva skupa podataka.Metodološki pristup -Za dobivanje detaljne slike pozicija maraka u svijesti potrošača prikupljene su slobodne, nevezane asocijacije za 10 maraka alkoholnih pića i 13 maraka automobila.One su kategorizirane te su analizirane frekvencija i distribucija.Za utvrđivanje sličnosti korištena je K-mean klasterska analiza.Asocijacije su uspoređene unutar i između kategorija proizvoda te su opisani pomaci unutar struktura asocijacija.Rezultati i implikacije -Rad pokazuje da se strukture asocijacija razlikuju po kategorijama proizvoda.Dva skupa podataka (prikupljena u razdobljima od 2011.do 2012.i od 2015.do 2016.)pokazuju da se asocijacije na marku, a time i imidž marke, mijenjaju tijekom vremena, a to se ne događa samo zbog marketinške komunikacije -vijesti iz medija i osobno iskustvo također dovode do promjena.Rezultati pokazuju da su pozitivne i negativne asocijacije vjerojatno povezane sa svakom markom.No Fetscherinova i Henrichova (2014) matrica samo je djelomično dokazana asocijacijama.Može se zaključiti
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".