Botanee: Leveraging Multi-touchpoint Marketing to Build a Strong Chinese Brand in the Digital Age
Bibliographic record
Abstract
近年来，随着消费者的需求越来越个性化、多样化，越来越多的新消费品牌开始涌现在市场上。但近几年的行业表现证明，只是通过资本加持、外包生产、过度营销等手段，品牌很难获得长期的可持续发展。本案例选择专注敏感肌肤的功效性护肤品牌薇诺娜及其公司贝泰妮作为对象，描述了薇诺娜从创立以来是如何通过产品创新，渠道布局和数字时代多触点的管理来切入敏感性肌肤这个细分市场的，又是如何一步步拓展市场并成为国内的护肤品领军品牌的。 从2018年开始，薇诺娜连续多年入围天猫美容护肤类目榜单前十，也是唯一连续上榜的中国品牌。 展望未来，贝泰妮还面临着很多问题。薇诺娜目前占据公司营收的99%以上，如何才能做好品牌拓展、覆盖更多的客群？薇诺娜旗下的明星单品特护霜一直是品牌收入的重要贡献来源，未来公司如何打造第二款“大单品”？ 随着公司规模扩大、触点不断增多，人员结构越来越复杂，如何做好内部的品牌管理？
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.005 |
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; both teacher heads agree on what is shown here.
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".