The marketing strategy of a company Lululemon for implementation brand to czech market
Bibliographic record
Abstract
THE MARKETING STRATEGY OF A COMPANY LULULEMON FOR IMPLEMENTATION BRAND TO CZECH MARKET Objectives: The thesis is focused on preparing the marketing strategy for Canadian company Lululemon which would like to expand to Czech market. This document will be used as an important support for the company while entering on a Czech market. Methods: Based on results of situational analysis is formed optimal marketing strategy for the company to expand on Czech market. In thesis I used methods of analysis of macro environment and micro environment, Porter five forces analysis and SWOT analysis, which identify internal and external environment of company. I also used method of personal questionnaire. Results: According to PEST analysis the situation in Czech Republic is stable and signal the safety and future profitability for Lululemon company. If company wants to compete with the known sports brands they have to invest more money to mass propagation and open new stores. Key words: marketing, marketing strategy, marketing mix, PEST analysis, SWOT analysis
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".