Dataset opportunity
Air Up — 交易数据集机会
Air Up 持有的中等交易数据集，可用于推荐模型和欺诈检测。
Score
63.6
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
49%
Action
数据共享协议
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market size (indicative estimate)
全球推荐引擎市场在 2025 年的估值为 71 亿美元，预计复合年增长率为 36.3%（2026-2033 年）。
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 🧑💻Hiring a data role
招募数据分析师和分析工程师以优化 D2C 增长
source ↗
Profile
Dataset profile
Type
交易数据集
Modality
表格
Sector
零售
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — GDPR 敏感（PII 审查）
Buyer persona
电子商务与个性化 AI 团队
Air Up 持有一个有价值的表格 交易数据集，来自其直接面向消费者 (D2C) 业务，包含详细的 `transaction_data`、`business_records` 和 `event_streams`。这些关于客户购买模式、香型偏好和重复购买行为的详细数据非常适合开发和训练高性能的推荐模型。
该数据的商业价值体现在相关的全球推荐引擎市场的增长上，该市场在 2025 年的估值为71 亿美元，预计将以36.3% 的复合年增长率增长。虽然大量的消费者个人身份信息 (PII) 和商业敏感的 D2C 数据需要严格的匿名化和谨慎的谈判，但该数据集的稀有性以及对专有香型研发的洞察力，为这个高增长市场的 AI 买家提供了显著的竞争优势。⚠ 尽职调查（有价值的数据，可协商访问）：大量消费者 PII 需要严格匿名化；直接面向消费者 (D2C) 交易数据具有商业敏感性；专有香型研发数据可能受到商业秘密保护 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Air Up 拥有一个专有的、高分辨率的数据集，详细说明了在新型香型补水市场中完整的客户旅程。这些独特的数据对于寻求构建下一代推荐模型的电子商务和个性化 AI 团队来说是一个强大的资产，这些模型可以准确预测消费者口味并推动订阅增长。在全球推荐引擎市场预计以 36.3% 的复合年增长率（2026-2033 年）增长的情况下，这个稀有的数据集通过解锁对风味偏好、购买周期和长期用户参与度的细微洞察，提供了显著的竞争优势。
See dimension details ↓- Right to License62
所有权=公司所有，许可=GDPR 敏感
Whether the company can legally license the data out — based on ownership and licensing complexity. - Training Value74
适用于推荐模型
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
AI 买家对这类直接面向消费者交易数据的需求异常高，这得益于在以 36.3% 的复合年增长率增长的市场中为个性化提供支持的关键需求。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/受监管
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 种证据类型，3 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Dataset Specificity78
主导的“transaction_data”，行业零售，2 种特定类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 次证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Corporate Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 个数据需求信号（1 种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus70
盈余=中等 — 超出已货币化的专有数据
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit83
✓ 良好目标 — Air Up 是一个强有力的目标，因为它是一家快速增长的 D2C 公司，销售实体产品，产生了宝贵的交易和消费者偏好数据副产品，而这些数据似乎并未作为核心业务进行货币化。问题：该公司增长迅速，拥有 300 多名员工，接近大型企业而非中小型企业；他们的隐私政策提到在某些法律定义下与第三方共享/出售个人信息用于广告目的，这可能会使纯粹的“休眠”数据复杂化；该公司已经使用其客户数据进行内部个性化推荐和提高留存率，因此数据并非完全“休眠”。
- Deep Qualification90
✓ 通过 — Air Up 是一家香型补水系统的 D2C 制造商，使其成为宝贵的交易和客户偏好数据的持有者。数据归公司所有，但包含 PII，并且虽然未发现明确的转售限制，但隐私政策是标准的，并未授予数据货币化的明确权利。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Transaction data
该数据集包含详尽的交易记录，详细说明了消费者购买行为、香型订阅周期和区域受欢迎程度，这对于训练优化客户生命周期价值和库存管理的模型至关重要。
business_records
这包括关于香型味觉感知和风味表现的专有业务记录，为预测新产品发布市场成功的模型提供了独特的真实依据。
Event streams
证据还指向时间序列数据，捕捉消费者与补水系统的互动方式，提供了构建适应用户习惯的复杂个性化引擎所必需的详细行为信号。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Air Up Transaction — a Moderate transaction dataset (Tabular modality) in the retail domain. Primary AI use-case: Recommendation Models. Market signal: Global Recommendation Engine Market was valued at USD 7.1 billion in 2025, with a projected CAGR of 36.3% (2026-2033) (source: Grand View Research).. Investment score 63.6/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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