Dataset opportunity
Cargoplot — 公共采购数据集机会
Cargoplot 持有的海量公共采购数据集，可用于投标情报和文档情报。
Score
74.3
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
72%
Action
收购
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)
全球采购分析市场 = 2026 年为 71.1 亿美元，复合年增长率为 23.85%。
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.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
Profile
Dataset profile
Type
公共采购数据集
Modality
文本
Sector
mobility
Volume
大型
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待明确 · PII/受监管
Buyer persona
GovTech 和采购情报供应商
Cargoplot 持有文本模态的公共采购数据集，并独家丰富了专有业务记录、交易数据和第三方承运商费率。这种组合可以对物流投标进行细粒度分析，使人工智能驱动的投标情报用例能够通过评估历史定价、专有承运商可靠性评分以及真实交易数据中的客户特定物流模式，超越公开信息。
此数据直接服务于全球采购分析市场，该市场在 2026 年的价值为 71.1 亿美元，预计将以 23.85% 的复合年增长率增长。[1] 虽然由于敏感的第三方承运商费率和商业定价，访问权限需要协商，但这种复杂性凸显了该数据集的稀有性和高战略价值，在快速扩张的市场中提供了独特的竞争优势。⚠ 注意（有价值的数据，可协商访问）：数据包括第三方承运商费率，可能存在转售限制；专有可靠性评分源自汇总的承运商绩效；交易数据涉及敏感的商业定价和客户特定物流。· 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 Cargoplot 拥有专有的物流采购和交易数据，详细说明了真实的运输费率、承运商报价和贸易量。这对于构建投标情报解决方案的 GovTech 和采购情报供应商来说是一项高价值资产，提供了对实际市场定价和承运商绩效的难得一窥。在全球采购分析市场预计到 2026 年将达到 71.1 亿美元的背景下，该数据集通过使模型能够高精度地对采购成本和贸易量进行基准测试和预测，提供了关键的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的“采购”，行业 mobility，3 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 Rarity82
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume76
7 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 Value84
适用于投标情报
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
人工智能买家需求旺盛，这得益于采购分析市场快速增长的 23.85% 复合年增长率，而这种细粒度的物流和交易数据是其主要投入。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility6
开放/API 访问
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
低难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
6 种证据类型，7 次命中
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 Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation73
3 个数据需求信号（3 种类型）
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 Audit100
✓ 良好目标 — Cargoplot 是一个面向中欧航运的数字货运市场，作为其核心匹配服务的副产品，积累了专有的交易、定价和物流线路数据。问题：提示中的“公共采购”标签很可能是错误的分类，因为该公司促进的是私人 B2B 贸易；然而，这使得数据更有价值
- Deep Qualification90
⚠ 需要审查 — Cargoplot 是一个货运代理平台，使其成为一个数据持有者，拥有与“货运和物流市场动态”细分市场高度相关的数据集（费率、承运商绩效、交易量），但“公共采购”标签不正确，因为其业务是商业航运。[数据集类型与实际活动不符：目标公司运营一个面向私营企业的商业货运代理平台，而不是与公共部门投标相关的服务；未发现“公共采购数据集”的证据。[7, 10, 16]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Knowledge base / docs
该平台拥有关于物流和监管主题的文章和指南的知识库，对于培训模型掌握行业特定术语和合规性要求非常有价值。
Developer portal
开发人员门户的证据表明了技术成熟度以及结构化数据访问的可能性，这对关注数据集成便捷性的买家来说是一个积极信号。
Transaction data
该公司持有大量财务活动的表格记录，包括处理的 1.5 亿欧元商品，为预测分析提供了关于贸易量和经济活动的直接、高价值数据。
IoT / sensor data
该平台从实时集装箱跟踪中生成时间序列数据，为预测供应链事件和优化物流路线的模型提供了丰富的数据源。
business_records
该数据集包括详细说明市场费率和承运商可靠性的业务记录，这对于培训人工智能评估供应商绩效和基准测试采购选项至关重要。
Procurement / tenders
该系统捕获来自竞争性承运商报价和详细成本报价的文本数据，为分析价格明细和投标策略的投标情报模型提供直接输入。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Cargoplot Public Procurement — a Large public procurement dataset (Text modality) in the mobility domain. Primary AI use-case: Tender Intelligence. Market signal: Global Procurement Analytics market = $7.11B in 2026, CAGR 23.85% (source: Mordor Intelligence). Investment score 74.3/100 (confidence 0.72). Recommended action: Acquire.
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