The effect of digital marketing on customer relationship management in the education sector: Peruvian case
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective of the research was to determine the impact of Digital Marketing on customer relationship management (CRM) in an educational institution in central Peru. The study was carried out from the quantitative approach, with a non-experimental correlational transactional research design. A questionnaire was applied to 228 parents between the ages of 30 and 50 who belong to an educational institution in the city of Concepción in Peru. Using the structural equations model, it was found that Content Marketing has a significant influence on the operational management of customer relationships (p <0.05), as well as on the analytical management of customer relationships (p <0.05). Regarding the Marketing of social networks, it was identified that it has a significant influence on the operational management of customer relationships (p <0.05), as well as on the analytical management of customer relationships (p <0, 05), because the media used by educational institutions are attractive to parents. It is concluded that Digital Marketing has a great impact on customer relationship management (CRM) in the educational sector of a city in central Peru.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it