SMEs fight for survival: An exploration of the development of a strategic marketing plan for EpiTech Public Health Consulting
Bibliographic record
Abstract
Small businesses play a vital role in the Canadian economy and represent 97.9% of all Canadian companies. Small business has a closure rate of 90.2% annually. Creating and executing a well-formulated marketing strategy is essential to business sustainability. Effective marketing strategy builds small business survival rates and supports long term execution advantages. The purpose of this holistic single case study was to explore the marketing strategies that EpiTech Public Health uses to sustain its businesses for longer years. EpiTech Public Health Consulting is a private, public-health consulting firm. EpiTech’s primary area of expertise is related to workplace infection spread. The data collection source included a review of 20 documents, more than 12 marketing instruments and participant observation notes. SWOT analysis and Ansoff Matrix marketing strategy model served as the conceptual framework. The result of SWOT analysis indicates that the position of EpiTech is in quadrat I, which supports the growth of marketing strategy through offensive marketing. An introduction to content marketing can implement the strategy. The Ansoff Growth Matrix result indicates that the position of EpiTech service/product is seen as the new business activity for Nanaimo, so, the primary strategy for EpiTech, is a market development strategy to increase the market share and to create the brand image to the customers. The Vaismoradi et al. data analysis process was used to validate findings. The data analysis included diverse mind map, explorations with observation notes, and document analysis using thematic analysis model. Two marketing strategy themes emerged: customer retention and attitudes and conventional and unconventional marketing that focuses on lowering the cost of products and services to meet the market needs of individuals or institutes. The findings revealed several features of how to use marketing strategies effectively to improve stability in the local economy. Further, its recommendation includes a sample marketing plan for the year 2021.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".