Dataset opportunity
Listenfield — 搜索和查询日志数据集机会
Listenfield 持有的海量搜索和查询日志数据集，可用于 RAG 和搜索相关性。
Score
47.5
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
92%
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)
全球农业分析市场在 2025 年的估值为 36 亿美元，预计在 2026 年至 2033 年的复合年增长率为 13.8%（来源：Grand View Research）。[1]
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
搜索和查询日志数据集
Modality
文本
Sector
其他
Volume
大型
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
LLM 应用团队和企业搜索供应商
Listenfield 持有一个专门的搜索和查询日志数据集，具有文本模态，源自其农业 SaaS 平台。该数据集包含用户关于种植实践的真实查询，并附带宝贵的相应证据，例如 iot_data、精确的 geo_data 和用户生成的内容。查询文本与多模态地面实况的这种独特组合使其特别适合训练和微调 RAG 模型，使其能够为复杂的农业问题提供准确、上下文感知的答案。
农业分析市场凸显了该数据集的商业价值，该市场在 2025 年的估值为36 亿美元，预计从 2026 年到 2033 年的复合年增长率将达到13.8%。[1] 尽管由于 PII、数据共享所有权和潜在的承接限制存在访问复杂性，但该数据集的稀有性及其在快速增长的农业人工智能领域的直接适用性带来了重大机遇。其价值在于为开发复杂的、数据驱动的农业解决方案的 AI 买家提供竞争优势。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据包含 PII 和农场的精确地理位置（GDPR/隐私敏感）；所有权与农民/客户共享特定种植日志；主要业务是 SaaS 仪表板，可能会限制原始数据承接·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 Listenfield 拥有专有的用户生成贡献流，包括来自其农业平台的聊天、论坛讨论和直接搜索活动。该数据集捕获了农民和农业技术专业人士的明确意图和专业词汇，使其成为LLM 应用团队构建领域特定 RAG 系统的宝贵资产。在全球农业分析市场预计每年增长 13.8% 的情况下，这种独特的搜索查询和用户互动来源提供了显著的竞争优势。
See dimension details ↓- Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value100
适用于 RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
AI 买家需求旺盛，这得益于农业分析市场 13.8% 的快速复合年增长率以及对专业多模态数据以训练有效的精准农业 RAG 模型至关重要的需求。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility14
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 Feasibility48
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Dataset Specificity98
占主导地位的“search_logs”，行业其他，5 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（开放降低稀有性）
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume100
27 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Evidence Strength100
7 种证据类型，27 个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
所有权=混合，许可=GDPR 敏感
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 个数据胃口信号（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，5 个近期外部信号 — 超出已货币化数据的专有数据
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 Audit58
⚠ 审查 — 这是一个糟糕的目标，因为其核心业务是向农业领域销售 AI 驱动的软件（FarmAI）、分析（仪表板）和数据即服务（AgroAPI），而农业领域是一个排除类别。问题：公司核心产品是 AI 软件和数据 API，这明确排除了 ICP；业务模式是其 SaaS 平台和 API 的 B2B 订阅服务，而不是销售以数据为副产品的实体产品或服务；他们使用的数据要么来自第三方（天气、卫星），要么属于其客户（农场数据），而不是作为；公司的全部价值主张是销售情报和分析，这与“休眠数据”的要求直接冲突。[2, 3, 4]
- Deep Qualification80
✓ 通过 — Listenfield 是农业分析的 SaaS 提供商，而不是数据销售商；其主要业务是 FarmAI 平台，该平台作为副产品生成专有数据。底层数据集是合理的，但由于与农民共享数据所有权、严格的使用条款以及敏感 PII 的存在，访问权限很复杂。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>A number of cereal growers in England and Wales are reporting that 2026 grain yields are down by up to 30% on normally expected levels. This is a direct consequence of harvest dates being a month ahead of their normal schedule. A shorter growing season, particularly for wheat, will directly impact final crop yields. Meanwhile […]</p> <p>The post <a href="https://www.agriland.ie/farming-news/2026-grain-yields-fall-by-30-in-parts-of-uk/">2026 grain yields fall by 30% in parts of UK</a> appeared first on <a href="https://www.agriland.ie">Agriland.ie</a>.</p>”
- “<p>Reports of tar spot being confirmed in Ontario corn fields are increasing, and with the calendar turning to August, growers should be scouting regularly and making timely fungicide decisions as weather conditions evolve. Ontario Ministry of Agriculture, Food and Agribusiness plant pathologist Albert Tenuta says tar spot was first detected a few weeks ago near... <a href="https://www.realagriculture.com/2026/07/tracking-tar-spot-with-albert-tenuta/">Read More</a></p>”
- “Le podcast du 31 juillet 2026”
Geospatial data
Listenfield 明确收集用户地理空间数据，包括坐标和种植活动信息，这对于构建具有位置感知能力的农业人工智能服务至关重要。
IoT / sensor data
这些证据表明收集了来自物理传感器设备和卫星的时间序列数据，这对于创建农业监测的地面实况数据集很有价值。
Downloads / exports
平台条款授予用户下载内容的许可，这表明存在结构化的表格报告或数据导出供用户分析。
Search / query logs
保护其搜索功能免遭自动抓取的平台条款间接证实了存在一个专有的搜索引擎，该搜索引擎会生成有价值的用户查询日志。
User-generated content
该平台托管用户生成的内容，如聊天和论坛，从而创建了丰富的非结构化领域特定文本来源，非常适合训练对话式 AI 和 RAG 系统。
Industrial data
证据表明收集了专门的工业数据，例如土壤分析结果，用于从土壤到收获的预测建模。
Image collection
该服务通过其平台收集用户上传的图像，提供独特的视觉数据集，用于训练计算机视觉模型来识别作物健康和耕作条件。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Listenfield Search & Query Logs — a Large search & query logs dataset (Text modality) in the other domain. Primary AI use-case: RAG. Market signal: Global Agriculture Analytics market was valued at $3.6 billion in 2025 and is projected to grow at a CAGR of 13.8% (2026-2033) (source: Grand View Research). [1]. Investment score 47.5/100 (confidence 0.92). Recommended action: Data Sharing Agreement.
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