The Study on The Relationship Between Promotional Strategies to Freshmen Students’ Perceptions and Needs in A Higher Educational Institution in Iligan City
Bibliographic record
Abstract
This study delves into the impact of promotional strategies on the perceptions and needs of freshmen students in higher education institutions. Its primary objective is to scrutinize the connection between promotional strategies, customer perception, and customer needs, with the goal of formulating precise and efficient marketing tactics. Conducted at a higher education institution in Iligan City, Philippines, the research encompasses participants from various colleges, ensuring a well-rounded sample. Employing a descriptive-correlational research design, data was gathered through an online survey questionnaire and subjected to analysis through descriptive statistics and Pearson correlataion analysis. The outcomes reveal a substantial positive correlation between promotional strategies and both customer perception and customer needs. Promotional strategies that are personalized, convenient, and sustainable are shown to enhance customer experience, customer value, and brand loyalty. This study offers valuable insights for both marketers and scholars, advocating for educational institutions to implement marketing programs with a focus on promotional strategies. Future research should explore the efficacy of promotional strategies across different contexts and diverse demographic groups to ensure all-encompassing and impactful marketing strategies. By comprehending the influence of promotional strategies on customer perception and needs, businesses and educational institutions can craft tailored marketing campaigns to attract and retain customers in today's fiercely competitive market landscape.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".