Alfamart brand communication on expansion retail business in the Philippines
Bibliographic record
Abstract
ABSTRACT In a guideline, the global brand company is broadly positioned around the world. In case the brand could be a premium estimated brand, it could be a premium cost around the world. The application of a global brand ought to too be indivisible from the part of the branding and key communication that makes difference in companies entering the domain of other countries. But what makes a brand profitable and how profitable is it? What could be a global brand and why are there still neighborhood brands? The spread of the COVID-19 pandemic in Southeast Asia, made global business lines run slowly and had to force business people to rack their brains to survive during a pandemic. The establishment of a lockdown policy has also hampered the distribution of retail goods as one of the impacts of the COVID-19 pandemic. However, it is different from Alfamart, which was able to survive during the pandemic with a decrease in net profit at the end of the third quarter of 2020 with a fairly small figure of -1.85% (Hafiyyan, 2020a). One of the strategies revealed is the expansion of Alfamart received a positive response in the Philippines competing 7-Eleven, Mini-Stop, Allday, Family Mart, and Lawson. So throughout 2020 Alfamart managed to open more than 1.000 new stores in Metro Manila and nearby province. The global brand communication strategy used by Alfamart to deliver strong brand awareness to Filipino customer mind and made Alfamart's brand positioning as a super minimart that serves the community. According to the above exposures, Alfamart is considered a successful brand in Indonesia that expand its global retail business in Southeast Asia since the COVID-19 pandemic that spread throughout the world. It is exciting research, Alfamart has not become the primary choice of consumers to shop at minimart or convenience stores in the Indonesian market itself. It is also inseparable from the brand communication strategy used by Alfamart to build strong brand awareness in Filipino consumers' minds. This research method is the case study, continuing to data analysis using the pattern matching of the informant insights and findings. The authors focus on describing the strategy of Alfamart Philippines to communicate its brand awareness in the community. Then, analyze the pattern matching of Filipino customers’ perceived brand of Alfamart through interviews with informants. The research findings are that Alfamart has expanded rapidly to open more than 1.200 stores since 2014 to help the community at Barangay (a remote area of the Philippines) for jobs and serve groceries product especially frozen food so that Alfamart become an "extended pantry" to their home. Alfamart’s accessibility and brand positioning as super minimart for Filipino customers built strong brand awareness as a global brand from Indonesia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.002 |
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".