Dataset opportunity
Vandenrecycling — Public Procurement Dataset Opportunity
Moderate public procurement dataset held by Vandenrecycling, usable for Tender Intelligence and Document Intelligence.
Score
71.1
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
Acquire
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)
Global Procurement Analytics market was valued at $4.27 Billion in 2024, with a projected CAGR of 23.50% (2024-2032).
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
Public Procurement Dataset
Modality
Text
Sector
industrial
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — clean to license · PII/regulated
Buyer persona
GovTech & procurement-intelligence vendors
Vandenrecycling holds a Public Procurement Dataset in Text modality, comprising detailed `industrial_data`, `procurement` records, and `transaction_data`. This specialized dataset is structured for training AI models in Tender Intelligence, enabling the analysis of historical bids, pricing strategies, and supplier performance within the complex global recycling industry.
The global Procurement Analytics market was valued at $4.27 Billion in 2024 and is projected to grow at a 23.50% CAGR, demonstrating immense demand for this type of data. Despite access complexities due to its coverage of multiple global jurisdictions (UK, Europe, Asia, MEA) and inclusion of proprietary benchmarks and sensitive B2B supplier relationships, the dataset's unique value lies in its rarity and direct applicability to this high-growth market, making it a crucial asset for strategic AI-driven procurement. ⚠ Diligence (valuable data, access to negotiate): Data spans multiple global jurisdictions (UK, Europe, Asia, MEA); Proprietary material quality and contamination benchmarks; Trading data involves B2B supplier relationships · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves the holder possesses a proprietary, high-rarity dataset detailing the global plastic waste supply chain. The data documents material availability, sourcing intelligence, transactional pricing, and quality specifications. For GovTech and procurement-intelligence vendors, this dataset directly powers Tender Intelligence models, enabling a decisive competitive advantage in the rapidly growing Global Procurement Analytics market, which is projected to expand at a 23.50% CAGR. This is a unique opportunity to acquire granular, real-world data on industrial procurement and material flows.
See dimension details ↓- Dataset Specificity90
dominant 'procurement', sector industrial, 3 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
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness46
periodic
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Tender Intelligence
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
AI buyer demand is exceptionally high, driven by the rapid expansion of the global procurement analytics market, which is forecast to grow at a 23.50% CAGR.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility16
PII/regulated
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 evidence types, 3 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
ownership=company_owned, licensing=clean
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 Orientation56
2 data-appetite signals (2 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high — 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 Audit100
✓ good target — Vanden Recycling is an ideal target as it's an operational SME in plastic recycling that generates vast amounts of proprietary data on material quality, sourcing, and logistics as a by-product, which it does not currently sell. Issues: The company offers 'Polymer Analysis' as a service, which borders on selling intelligence. [11, 18]; They are actively using their data internally with Power BI and proprietary systems to optimize their own operations, indicating the data is active but not yet
- Deep Qualification90
⚠ needs review — Vanden Recycling is a global trader of recycled plastics, generating proprietary data on material quality, pricing, and logistics as a by-product of its core business. The hypothesis of a 'Public Procurement Dataset' is implausible as their operations are entirely within the private B2B sector. [dataset_type implausible vs real activity: The company's business is trading and supplying recycled plastics in a B2B context, not dealing with public sector tenders. The dataset would contain private procurement and transaction data, not 'Public Procurement' data. [1, 3]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
This is time-series data detailing the material specifications and quality of processed polymers, offering a technical baseline for evaluating tender requirements and material compliance.
Transaction data
This tabular data provides extensive records of global plastic scrap volumes and pricing, enabling AI buyers to model market dynamics and develop competitive bid strategies.
Procurement / tenders
This text data represents direct sourcing intelligence on the availability of plastic waste from global industrial sectors, which is critical for identifying and qualifying new supply opportunities for procurement platforms.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Vandenrecycling Public Procurement — a Moderate public procurement dataset (Text modality) in the industrial domain. Primary AI use-case: Tender Intelligence. Market signal: Global Procurement Analytics market was valued at $4.27 Billion in 2024, with a projected CAGR of 23.50% (2024-2032) (source: Data Bridge Market Research).. Investment score 71.1/100 (confidence 0.49). Recommended action: Acquire.
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Learn before you deal
- Acquire Rare, Compliant Data3 min read
- Data marketplaces, explained4 min read
- Data licensing, term by term4 min read