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可计算开店科技荣膺亿邦动力·α引力奖 数智化引领线下增长新范式

龚作仁 2026-02-06 17:18
龚作仁 2026/02/06 17:18

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文章重点介绍了可计算开店科技获奖及其创新模式,提供实操干货。

1. 可计算开店科技获“2025α引力奖”,被评为“新价值力服务商”和“年度数字技术服务商”,奖项聚焦不追逐短期风口、凭借内生动力穿越周期的服务商。

2. 在市场供给过剩、行业增长放缓背景下,品牌线下拓展转向效率与确定性竞争,核心模式是“开小、开灵活、可计算”,构建数据化慢闪店。

3. 实操方法包括搭建“测试—评估—复制”的UCR增长闭环,形成可验证、可复盘、可复制的数智化决策能力,帮助品牌精准捕捉流量红利、挖掘线下新增量,实现韧性生长。

品牌商可关注渠道建设和消费趋势的干货内容。

1. 品牌渠道建设:在市场供给过剩、增长放缓环境下,线下拓展从规模扩张转向效率与确定性核心竞争,可计算开店科技协助品牌构建可持续增长模式,通过数据化慢闪店提升渠道效率。

2. 消费趋势:行业转向效率竞争,品牌需精准捕捉流量红利;解决方案包括UCR增长闭环,帮助品牌在不确定环境中挖掘新增量,实现韧性生长。

3. 用户行为观察:基于“开小、开灵活、可计算”模式,品牌可结合经验判断形成数智化决策,优化用户行为响应。

卖家可获取增长机会和最新商业模式的干货内容。

1. 增长市场机会:在市场供给过剩、行业增长放缓背景下,机会在于挖掘线下新增量和精准捕捉流量红利,可计算开店科技提供UCR闭环帮助在不确定环境中实现韧性生长。

2. 最新商业模式:数据化慢闪店模式以“开小、开灵活、可计算”为核心,支持品牌测试-评估-复制,形成可复制的决策能力。

3. 可学习点:品牌线下开店经验可转化为数智化决策,卖家可借鉴此方法应对风险,提升效率;同时,获奖事件提示服务商价值,可作为合作参考。

工厂可从中获得数字化启示和商业机会的干货内容。

1. 产品生产和设计需求:品牌转向效率竞争,需求可复制的决策能力;工厂可参与构建数据化慢闪店模式,优化产品设计以适应“开小、开灵活”趋势。

2. 商业机会:市场变化带来挖掘线下新增量的机会,工厂可合作开发可计算开店解决方案,助力品牌实现韧性生长。

3. 推进数字化启示:行业趋势强调数智化决策,工厂可借鉴UCR增长闭环(测试-评估-复制),推进电商和数字化生产流程,提升效率与确定性。

服务商可聚焦行业趋势和解决方案的干货内容。

1. 行业发展趋势:在市场供给过剩、行业增长放缓背景下,线下零售转向效率与确定性竞争,未来核心竞争力在于可规模化复制的决策能力。

2. 新技术:数智化决策能力是关键,可计算开店科技构建数据化慢闪店模式,结合“开小、开灵活、可计算”核心,实现可验证、可复盘的技术创新。

3. 客户痛点和解决方案:客户痛点包括不确定环境中的增长挑战;解决方案是UCR增长闭环(测试-评估-复制),帮助品牌精准捕捉流量红利、挖掘新增量,提供韧性生长路径。

平台商可了解商业需求和最新做法的干货内容。

1. 商业对平台的需求:品牌在效率竞争阶段需要可复制的决策能力,平台需支持数据化慢闪店模式,以应对市场供给过剩和增长放缓的挑战。

2. 平台的最新做法:类似可计算开店科技的UCR增长闭环,平台可整合测试-评估-复制流程,优化招商和运营管理,帮助品牌挖掘线下新增量。

3. 风向规避:在不确定环境中,平台需规避风险,通过数智化决策提升确定性;获奖案例提示服务商价值,可作为合作参考,强化平台生态。

研究者可分析产业动向和商业模式的干货内容。

1. 产业新动向:在市场供给过剩、行业增长放缓背景下,线下拓展从规模扩张转向效率与确定性核心竞争,未来核心竞争力聚焦可规模化复制的决策能力。

2. 新商业模式:数据化慢闪店模式以“开小、开灵活、可计算”为核心,构建UCR增长闭环(测试-评估-复制),形成可验证、可复盘、可复制的数智化决策。

3. 政策法规启示:奖项标准强调不追逐短期风口、内生动力穿越周期,研究者可探讨如何制定政策支持此类创新,促进韧性生长和可持续生态。

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声明:快读内容全程由AI生成,请注意甄别信息。如您发现问题,请发送邮件至 run@ebrun.com 。

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Quick Summary

The article highlights Computable Store Opening Technology's award win and its innovative model, providing actionable insights.

1. Computable Store Opening Technology received the "2025 α Gravity Award," recognized as a "New Value Force Service Provider" and "Annual Digital Technology Service Provider." The award honors service providers that avoid chasing short-term trends and rely on endogenous momentum to navigate market cycles.

2. Against a backdrop of market oversupply and slowing industry growth, brands are shifting their offline expansion focus to efficiency and predictability. The core model emphasizes "small, flexible, and computable" store formats, building data-driven pop-up stores.

3. Practical methods include establishing a UCR growth loop (Test-Evaluate-Replicate), creating verifiable, reviewable, and replicable data-driven decision-making capabilities. This helps brands accurately capture traffic opportunities, uncover new offline growth, and achieve resilient expansion.

Brands can focus on practical insights for channel development and consumer trends.

1. Channel Development: In an oversupplied market with slowing growth, offline expansion is shifting from scale to efficiency and predictability. Computable Store Opening Technology helps brands build sustainable growth models through data-driven pop-up stores that enhance channel efficiency.

2. Consumer Trends: As the industry pivots to efficiency competition, brands must precisely capture traffic opportunities. The UCR growth loop offers a solution to uncover new growth in uncertain environments, enabling resilient expansion.

3. User Behavior Observation: By adopting the "small, flexible, computable" model, brands can combine experiential judgment with data-driven decisions to optimize responses to user behavior.

Sellers can gain insights on growth opportunities and emerging business models.

1. Growth Opportunities: Amid market oversupply and slowing growth, opportunities lie in uncovering new offline growth and precisely capturing traffic红利. Computable Store Opening Technology's UCR loop helps achieve resilient growth in uncertain conditions.

2. Emerging Business Models: The data-driven pop-up model, centered on "small, flexible, computable" operations, supports test-evaluate-replicate cycles to build replicable decision-making capabilities.

3. Key Takeaways: Brands' offline store experiences can be transformed into data-driven decisions. Sellers can adopt this approach to mitigate risks and improve efficiency. The award win also signals the value of service providers as potential partners.

Factories can derive digitalization insights and business opportunities from the content.

1. Production and Design Needs: Brands' shift toward efficiency competition demands replicable decision-making capabilities. Factories can participate in building data-driven pop-up models and adapt product designs to the "small, flexible" trend.

2. Business Opportunities: Market changes create opportunities to tap into new offline growth. Factories can collaborate on developing computable store-opening solutions to support brands' resilient expansion.

3. Digitalization Insights: Industry trends emphasize data-driven decisions. Factories can learn from the UCR growth loop (Test-Evaluate-Replicate) to advance e-commerce and digital production processes, enhancing efficiency and predictability.

Service providers should focus on industry trends and solution-oriented insights.

1. Industry Trends: With market oversupply and slowing growth, offline retail is competing on efficiency and predictability. Future competitiveness will hinge on scalable, replicable decision-making capabilities.

2. New Technologies: Data-driven decision-making is critical. Computable Store Opening Technology's pop-up model, based on "small, flexible, computable" principles, enables verifiable and reviewable innovation.

3. Client Pain Points and Solutions: Clients struggle with growth in uncertain environments. The UCR growth loop (Test-Evaluate-Replicate) helps brands capture traffic opportunities and uncover new growth, providing a path to resilient expansion.

Platform operators can learn about commercial needs and latest practices.

1. Commercial Demands on Platforms: Brands in the efficiency competition phase require replicable decision-making capabilities. Platforms must support data-driven pop-up models to address oversupply and growth challenges.

2. Platform Best Practices: Similar to Computable Store Opening Technology's UCR loop, platforms can integrate test-evaluate-replicate processes to optimize merchant recruitment and operations, helping brands uncover offline growth.

3. Risk Mitigation: In uncertain environments, platforms must reduce risks through data-driven decisions. The award case highlights the value of service providers as potential partners to strengthen platform ecosystems.

Researchers can analyze industry movements and business models.

1. Industry Trends: Amid market oversupply and slowing growth, offline expansion is shifting from scale to efficiency and predictability. Future competitiveness will center on scalable, replicable decision-making.

2. New Business Models: The data-driven pop-up model, built on "small, flexible, computable" principles, creates a UCR growth loop (Test-Evaluate-Replicate) for verifiable, reviewable, and replicable data-driven decisions.

3. Policy Implications: Award criteria emphasize avoiding short-term trends and sustaining growth through endogenous momentum. Researchers can explore policies that support such innovations to foster resilient growth and sustainable ecosystems.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

近日,在2026广东电子商务大会现场,知名电商媒体亿邦动力揭晓“2025α 引力奖”年度榜单。凭借在线下零售领域的创新实践与技术成果,「可计算开店科技」成功入选“新价值力服务商”,并获评“年度数字技术服务商”。

“α引力奖”聚焦发掘那些不追逐短期风口、凭借内生动力穿越周期的“新竞争力品牌”与其背后的关键赋能者。历经数月严格评审,该奖项已成为衡量服务商价值与成长性的重要标尺。

此次获奖,不仅是对「可计算开店科技」技术实力与服务深度的双重认可,亦是对我们持续助力品牌构建线下可持续增长模式的有力见证。

亿邦智库《2025新竞争力品牌洞察报告》数字化服务商全景图:「可计算开店科技」与多家行业先锋共同定义零售消费领域的未来生态。

在市场供给过剩、行业增长放缓的背景下,品牌线下拓展正从“规模扩张”转向”效率与确定性”的核心竞争阶段。

围绕行业趋势,可计算开店科技以“开小、开灵活、可计算”为核心,构建数据化慢闪店模式,协助品牌搭建 “测试—评估—复制” 的UCR增长闭环,并结合品牌线下开店的经验判断,形成可验证、可复盘、可复制的数智化决策能力,帮助品牌精准捕捉流量红利、挖掘线下新增量,在不确定环境中实现韧性生长。

面向未来,线下开店的核心竞争力,将不再取决于单点资源或经验判断,而在于是否具备可规模化复制的决策能力。可计算开店科技将持续打磨确定性的线下增长新范式,陪伴品牌在复杂环境中稳步前行。

注:文/龚作仁,文章来源:Laborer,本文为作者独立观点,不代表亿邦动力立场。

文章来源:Laborer

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