Dataset opportunity
Precisewarehousing — Transaction Dataset Opportunity
Moderate transaction dataset held by Precisewarehousing, usable for Recommendation Models and Fraud Detection.
Score
54.6
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
42%
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 size (indicative estimate)
Global Supply Chain Analytics market was valued at $11.0 Billion in 2025, projected to exhibit a CAGR of 15.85% from 2026-2034.
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.
- ✨Signal
Courier & LTL Rate Shopping service indicates active management of shipping rate databases
source ↗
Profile
Dataset profile
Type
Transaction Dataset
Modality
Tabular
Sector
mobility
Volume
Moderate
Freshness
Periodic
Rarity
Medium
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify · PII/regulated
Buyer persona
E-commerce & personalization AI teams
Precisewarehousing holds a Transaction Dataset in Tabular format, containing detailed business records and transaction data from its mobility and logistics operations. This includes granular information on third-party carrier rates, client inventory levels, and shipping performance metrics, making it highly suitable for training sophisticated Recommendation Models to optimize carrier selection, routes, and inventory management for e-commerce and logistics clients.
The global Supply Chain Analytics market was valued at $11.0 Billion in 2025 and is projected to grow at a CAGR of 15.85% through 2034. [2] Despite known access complexities, such as the need to anonymize PII in shipping details and contractually clarify data ownership, this valuable dataset is a significant asset. The rarity of such comprehensive, real-world logistics data, combined with high market growth, makes it a compelling opportunity for AI buyers aiming to build a competitive edge in supply chain optimization. [2] ⚠ Diligence (valuable data, access to negotiate): Logistics data involves third-party carrier rates and client inventory details.; Shipping addresses and recipient names constitute PII requiring anonymization.; Ownership of aggregated shipping performance data needs contractual clarification. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence indicates Precisewarehousing possesses a proprietary dataset of shipping transactions, detailing both historical costs across various carriers and real-world logistics performance. This is a high-value asset for e-commerce and personalization AI teams seeking to build sophisticated recommendation models. By training on this data, models can optimize shipping recommendations based on cost, speed, and reliability, providing a crucial competitive advantage in a supply chain analytics market projected to grow at over 15% annually.
See dimension details ↓- Dataset Specificity66
dominant 'transaction_data', sector mobility, 1 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity58
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume46
2 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 Value64
fit for Recommendation Models
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI buyer demand is high, driven by the rapid growth of the Supply Chain Analytics market, which is expected to expand at a 15.85% CAGR as companies seek data to optimize logistics and gain a competitive advantage. [2]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
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
low difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength50
2 evidence types, 2 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
ownership=mixed, licensing=rights_unclear
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 Orientation39
1 data-appetite signals (1 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus70
surplus=medium — 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 — This independently owned Canadian 3PL company, operating since 2011, is a perfect target as its core business is operational logistics, generating valuable, dormant transaction and inventory data as a byproduct.
- Deep Qualification80
✓ pass — Precise Warehousing is a 3PL service provider holding a valuable transactional dataset as a by-product of its core logistics and e-commerce fulfillment operations. A recent acquisition enhances its data generation capabilities, but data ownership is mixed (client and aggregated data) and contains PII, while specific licensing rights remain unverified due to the absence of public legal documents.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Transaction data
The company's rate shopping services generate a proprietary tabular dataset of historical and real-time shipping costs across a network of carriers, essential for any e-commerce platform looking to optimize logistics spend.
business_records
As a Third Party Logistics (3PL) provider, the company captures operational records detailing delivery success rates and lead times, providing the ground-truth performance data needed to build robust predictive models.
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
Precisewarehousing Transaction — a Moderate transaction dataset (Tabular modality) in the mobility domain. Primary AI use-case: Recommendation Models. Market signal: Global Supply Chain Analytics market was valued at $11.0 Billion in 2025, projected to exhibit a CAGR of 15.85% from 2026-2034 (source: IMARC Group). [2]. Investment score 54.6/100 (confidence 0.42). Recommended action: Data Sharing Agreement.
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Learn before you deal
- Data marketplaces, explained4 min read
- Data licensing, term by term4 min read
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