Dataset opportunity
Listenfield — Search & Query Logs Dataset Opportunity
Large search & query logs dataset held by Listenfield, usable for RAG and Search Relevance.
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
Data Sharing Agreement
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
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]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-08-01
2026 grain yields fall by 30% in parts of UK
agriland.ie ↗ - 📰press2026-07-31
Tracking tar spot with Albert Tenuta
realagriculture.com ↗ - 📰press2026-07-31
Le podcast du 31 juillet 2026
lafranceagricole.fr ↗ - 📰press2026-07-31
From garden to farmers market: Lessons from a first-time vendor
farmprogress.com ↗ - 📰press2026-07-31
Aide à l’achat d’engrais azotés : le guichet ouvre ce vendredi 31 juillet
lafranceagricole.fr ↗
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
Search & Query Logs Dataset
Modality
Text
Sector
other
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
LLM application teams & enterprise search vendors
Listenfield holds a specialized Search & Query Logs Dataset with a Text modality, derived from its agricultural SaaS platform. This dataset contains real-world user queries on cultivation practices, enriched with valuable corresponding evidence such as iot_data, precise geo_data, and user-generated content. This unique combination of query text and multi-modal ground truth makes it exceptionally well-suited for training and fine-tuning a RAG model, enabling it to provide accurate, context-aware answers to complex agricultural questions.
The business value is underscored by the Agriculture Analytics market, which was valued at $3.6 billion in 2025 and is projected to grow at a CAGR of 13.8% from 2026 to 2033. [1] Despite access complexities due to PII, shared data ownership, and potential off-take restrictions, the rarity and direct applicability of this dataset to the high-growth AI-in-agriculture sector present a significant opportunity. Its value lies in providing a competitive edge for AI buyers developing sophisticated, data-driven farming solutions. ⚠ Diligence (valuable data, access to negotiate): Data includes PII and precise geolocation of farms (GDPR/Privacy sensitive); Ownership is shared with farmers/clients for specific cultivation logs; Primary business is a SaaS dashboard which may restrict raw data off-take · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Listenfield possesses a proprietary stream of user-generated contributions, including chats, forum discussions, and direct search activity from its agricultural platform. This dataset captures the explicit intent and specialized vocabulary of farmers and ag-tech professionals, making it a high-value asset for LLM application teams building domain-specific RAG systems. In a global agriculture analytics market projected to grow at 13.8% annually, this unique source of search queries and user interactions offers a significant competitive edge.
See dimension details ↓- Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value100
fit for RAG
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand85
AI buyer demand is high, driven by the rapid 13.8% CAGR of the Agriculture Analytics market and the critical need for specialized, multi-modal data to train effective RAG models for precision farming. [1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility14
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility48
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Dataset Specificity98
dominant 'search_logs', sector other, 5 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume100
27 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Evidence Strength100
7 evidence types, 27 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
ownership=mixed, licensing=gdpr_sensitive
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation73
3 data-appetite signals (3 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 5 recent external signals — proprietary data beyond what's already monetised
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
⚠ review — This is a bad target because its core business is selling AI-driven software (FarmAI), analytics (dashboards), and data-as-a-service (AgroAPI) to the agriculture sector, which is an excluded category. Issues: Company's core products are AI software and data APIs, which are explicitly excluded by the ICP.; The business model is B2B subscription service for their SaaS platform and API, not selling a physical product or service with data as a by-product. [5, 9]; The data they use is either sourced from third parties (weather, satellite) or belongs to their clients (farm data), it is not proprietary data generated as an ; The company's entire value proposition is based on selling intelligence and analytics, which is a direct conflict with the 'dormant data' requirement. [2, 3, 4]
- Deep Qualification80
✓ pass — Listenfield is a SaaS provider for agricultural analytics, not a data seller; its primary business is the FarmAI platform which generates proprietary data as a byproduct. The underlying dataset is plausible but access is complex due to shared data ownership with farmers, strict usage terms, and the presence of sensitive PII.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
Listenfield explicitly collects user geospatial data, including coordinates and cultivation activity information, which is essential for building location-aware agricultural AI services.
IoT / sensor data
This evidence indicates the collection of time-series data from physical sensor devices and satellites, valuable for creating ground-truth datasets for agricultural monitoring.
Downloads / exports
The platform's terms grant users a license to download content, suggesting the availability of structured, tabular reports or data exports for user analysis.
Search / query logs
Platform terms protecting against automated scraping of its search function indirectly confirm the existence of a proprietary search engine, which generates valuable user query logs.
User-generated content
The platform hosts user-generated contributions like chats and forums, creating a rich source of unstructured domain-specific text ideal for training conversational AI and RAG systems.
Industrial data
Evidence points to the collection of specialized industrial data, such as soil analysis results, used for predictive modeling from soil to harvest.
Image collection
The service collects user-uploaded images through its platform, providing a unique visual dataset for training computer vision models on crop health and farming conditions.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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.
From the marketplace
Explore live data opportunities
Chementors — Regulatory Records Dataset Opportunity
View opportunity →industrialSemefab — Regulatory Records Dataset Opportunity
View opportunity →industrialSteadyenergy — Regulatory Records Dataset Opportunity
View opportunity →