数据决策开品:羽绒服水洗液单周销量破300万,品类TOP1

· 行为数据决策
数糖科技

基于消费者行为数据开发的吉屋羽绒服专用水洗液产品,单周销量破300万,开创羽绒服水洗液新品类,成功在强敌环伺的家居洗衣赛道打造出新爆品

Based on consumer behavior data, Jiwu has developed a specialized water cleaner for down jackets. This product has achieved a record-breaking weekly sales of over 3 million, pioneering a new category in the market of down jacket cleaning solutions. It has successfully created a new explosive product in the competitive home laundry industry, despite fierce competition.

 

数据驱动的新品开发如何实现?

How is data-driven product development achieved?

 

在产品正式上市前,数糖与吉屋团队进行了 新品开发MVP(最小可行性测试) 数研合作。羽绒服专用水洗液作为一款从0开发的新品,我们用几个关键步骤给了该产品大规模投产的确定性。

Before the official launch of the product, ActStat team collaborated with Giju team on the development of a new product MVP (Minimum Viable Product) test. The collaboration focused on developing a down jacket-specific laundry detergent from scratch. We utilized several key steps to ensure the certainty of large-scale production for this product.

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在消费者行为数据中挖掘产品机会

Discovering product opportunities through consumer behavior data

数糖团队通过跨类目的消费者行为数据研究,从历史数据研究及行业数据中,探索到羽绒服清洁品类机会,并进行了需求量级的初步确认。由于该产品并不是吉屋已经研发成熟的储备品,我们与吉屋产品研发团队共同进行了产品真实性验证,并与吉屋供应链部门确定包装形式、成本结构、供应链生产能力。

ActStat team explored product opportunities in consumer behavior data by cross-analyzing data across categories. Through historical and industry data analysis, we discovered an opportunity in the down jacket cleaning product category and conducted a preliminary confirmation of demand volume. As this product was not already in the pipeline of products developed by JIWU, we collaborated with their product development team to conduct a validation of the product’s authenticity and worked with their supply chain department to determine packaging form, cost structure, and production capacity of the supply chain.

 

将前期行为数据的洞察,转化为可落地的方案

Translating the insights from preliminary behavioral data into actionable solutions

在充分验证产品的真实性和生产可行性后,我们准备了测试用的最小可行性产品物料准备,包含卖点体系打造、包装设计、小样制作、商品拍摄、橱窗和详情页等。与此同时,安排工厂生产了1000件合规商品,并安排商品检测,完成产品测试要素的准备工作。

After fully verifying the authenticity and production feasibility of the product, we prepared minimum viable product materials for testing, including building selling point systems, designing packaging, producing samples, shooting product photos, and creating storefront and detail pages. Meanwhile, we arranged for the production of 1000 compliant products at the factory and arranged for product testing and preparation of product testing elements.


敏捷测试,快速验证多个挑战点

Agile testing, quickly validating multiple challenge points

产品MVP测试共耗时3周,第1周进行实验设计,并同时进行测试准备,包含对目标行为人群假设、测试用短视频、产品链接和购买通路方面的细化;第2周数据生成及采集,我们在抖音渠道按实验设计进行测试投放,用真实的商品、真实的消费者、真实的购买链路、真实的成交和互动行为得到1000件商品销售完成后的消费者行为数据。第3周,经过数据清洗和分析,我们确定了“羽绒服专用水洗液”这一新产品在目标消费者行为的角度成立,数据表现较好且存在较大量级。

The MVP testing of the product took a total of 3 weeks. In the first week, we conducted experiment design and simultaneously prepared for testing, including refining assumptions about the target user behavior, creating test videos, preparing product links, and aligning with the purchase process. In the second week, data generation and collection took place. We conducted the test on the Douyin channel as per the experiment design, using real products, real consumers, real purchase channels, and real transaction and interaction behavior. We obtained consumer behavioral data after the sale of 1000 products. In the third week, after data cleaning and analysis, we confirmed the validity of the new product "Down Jacket Special Washing Liquid" from the perspective of target consumer behavior. The data showed promising performance and a significant volume.

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通过初测后,再进行深度复核验证

After the initial testing, we conducted a comprehensive review and validation.

为了进一步提高新品的确定性,与吉屋团队共同讨论后决定,用最小经济批量,进行再次验证。在这个阶段,还进一步做了流量词及概念测试,最终验证MVP结论有效。

To further increase the certainty of the new product, we decided, in collaboration with the Jiwu team, to conduct another round of validation using the minimum economic batch. At this stage, we also conducted traffic keyword and concept testing, ultimately validating the effectiveness of the MVP conclusion.

 

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