Dataset opportunity
Goodlogisticsgroup — Mobility Event Dataset Opportunity
Goodlogisticsgroup 持有的中等规模移动事件数据集，可用于预测和异常检测。
Score
63.3
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
Partnership (group-level)
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)
全球供应链分析市场规模在 2025 年的估值为 110 亿美元，预计到 2034 年将达到 412 亿美元，复合年增长率为 15.85%。
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.
Profile
Dataset profile
Type
移动事件数据集
Modality
时间序列
Sector
mobility
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待澄清
Buyer persona
Quant funds & demand-forecasting AI teams
Goodlogisticsgroup 持有一个结构为时间序列的移动事件数据集，该数据集由 business_records、real-time event_streams 和 geo_data 编译而成。这提供了多式联运货物移动的精细、顺序视图，使其非常适合 AI 驱动的预测模型，用于预测运输时间、解决延误和优化需求规划。
全球供应链分析市场在 2025 年的估值为 110 亿美元，预计到 2034 年将达到 412 亿美元，复合年增长率 (CAGR) 为 15.85%。[2] 尽管存在访问复杂性——包括 Denholm 集团下的多级审批、数据共享所有权和监管合规性——但目前被锁定在遗留系统中的数据的稀有性和丰富性，为愿意完成尽职调查过程的买家提供了显著的竞争优势。⚠ 尽职调查（有价值的数据，可协商的访问权限）：大型私营集团（Denholm）的子公司，需要多级审批；数据所有权在托运人、承运人和物流提供商之间共享；海关和贸易数据受严格的监管合规性和保密性约束；大量数据被锁定在遗留货运管理系统中 · 公司：Denholm Group 的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Goodlogisticsgroup 拥有一项专有的、多模式的物流情报资产，结合了实时货物跟踪以及关于海关和路线绩效的深入历史背景。该独特数据集非常适合量化基金和构建预测模型以预测供应链中断和商品流的公司 AI 团队。在全球供应链分析市场预计到 2034 年将达到412 亿美元的背景下，这些数据提供了显著的预测优势。
See dimension details ↓- Dataset Specificity78
占主导地位的 'event_streams'，行业 mobility，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 个证据命中
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. - Training Value74
适合 Forecasting
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI 买家需求异常高，这得益于快速增长的供应链分析市场（CAGR 15.85%），其中精细的时间序列数据对于构建有价值的预测模型至关重要。[2]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
高难度，Denholm Group 的子公司
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 个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
所有权=混合，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
Denholm Group 的子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 数据胃口信号（0 类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=高 — 专有数据超出已货币化的部分
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 Audit92
✓ 好目标 — 这是一家真实、历史悠久的物流和货运代理公司，拥有实体业务，使其成为专有、休眠运营数据的良好潜在来源。问题：该公司于 2021 年被 Denholm Group 收购，并于 2024 年与 Denholm Global Logistics 合并，组建了 'Denholm Good Logistics'。[5, 8]；它现在是一个更大集团的一部分，这可能会使决策复杂化，尽管它似乎作为一个独立的实体运作。[5, 9]；公司网站上未找到该提示中提到的“移动事件数据集”；他们的业务是提供物流服务，而不是销售数据。[8,
- Deep Qualification80
✓ 通过 — 该目标是一家 3PL/4PL 物流服务提供商，使其成为一个潜在的移动事件数据集的数据持有者，该数据集是其核心业务的副产品。然而，物流中的数据所有权本质上是混合的，并且在公开文件中未指定转售的许可权，需要直接协商。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Event streams
这种证据类型是一个连续的时间序列流，提供对全球货运的实时可见性，对于预测运输时间和中断的模型至关重要。
business_records
这些证据证实了结构化业务记录的存在，包括海关申报和商品代码，这对于预测国际贸易流量和经济活动至关重要。
Geospatial data
这些证据指向一个丰富的历史数据集，详细说明了路线效率和物流绩效，使得能够训练 AI 模型来优化多式联运运输策略。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
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Deliverable
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Goodlogisticsgroup Mobility Event — a Moderate mobility event dataset (Time Series modality) in the mobility domain. Primary AI use-case: Forecasting. Market signal: Global supply chain analytics market size was valued at USD 11.0 Billion in 2025 and is projected to reach USD 41.2 Billion by 2034, exhibiting a CAGR of 15.85% (source: IMARC Group). [2]. Investment score 63.3/100 (confidence 0.49). Recommended action: Partnership (group-level).
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