Dataset opportunity
Mactrans — Industrial Operations Dataset Opportunity
Moderate industrial operations dataset held by Mactrans, usable for Industrial Monitoring and Forecasting.
Score
48
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 Supply Chain Analytics market = $6.27B in 2023, CAGR 17.20%.
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
Industrial Operations Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify · PII/regulated
Buyer persona
Industrial AI integrators
Mactrans holds a rich Time Series dataset derived from its non-asset-based logistics operations, encompassing geo_data, industrial_data, and transaction_data. This multi-faceted data provides a comprehensive foundation for developing and training Industrial Monitoring AI models to track shipment statuses, predict delays, and optimize transportation routes in real-time.
The business value is substantial, targeting the global Supply Chain Analytics market, which was valued at $6.27 Billion in 2023 and is projected to grow with a CAGR of 17.20%. [6] While access requires navigating complexities like carrier-originated data and client usage restrictions, the dataset's unique rarity comes from the proprietary MACsync platform, which aggregates cross-client lane intelligence. This offers a distinct competitive advantage, making the data highly valuable for AI buyers despite the access complexities. ⚠ Diligence (valuable data, access to negotiate): Non-asset based model means some data is carrier-originated; Client shipment data may have contractual usage restrictions; Proprietary MACsync platform aggregates cross-client lane intelligence · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Mactrans possesses a proprietary, high-rarity dataset detailing carrier performance and historical shipping operations across North America. This time-series data is ideal for Industrial AI integrators building industrial monitoring and supply chain optimization models. In a Global Supply Chain Analytics market projected to grow at over 17% annually, this dataset offers a unique source of real-world logistics intelligence to power next-generation AI solutions.
See dimension details ↓- Dataset Specificity90
dominant 'industrial_data', sector mobility, 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 Industrial Monitoring
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 extremely high, driven by the 17.20% CAGR of the supply chain analytics market as companies aggressively seek a competitive edge through real-time operational intelligence. [6]
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
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 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 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, 2 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 Audit75
⚠ review — Mactrans is a non-asset based 3PL/4PL freight broker whose core business is providing transportation management, analytics, and a TMS platform to clients, making it a bad fit as it already sells intelligence. Issues: The company's core business is providing logistics intelligence and a Transportation Management System (TMS), which falls under the exclusion criteria of sellin; Mactrans is a non-asset based 3PL, meaning it does not own its own trucks but rather arranges transportation with a network of thousands of carriers. [3, 9] The; Their 'MACsync' 4PL service explicitly involves analyzing a client's entire supply chain, managing RFPs, and providing a TMS to optimize cost and service, which
- Deep Qualification70
✓ pass — Mactrans is a non-asset-based 3PL provider, making it a `data_holder` of valuable logistics data (geo, industrial, transactional time-series) as a byproduct of its services. However, data ownership is `mixed` (originating from clients and carriers) and licensing rights for resale are `unclear` due to a lack of specific data resale clauses in their legal documents, posing a significant hurdle for acquisition.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>UPS said earnings improved in the second quarter as it fully ended handling low-margin Amazon shipments and continued streamlining its domestic network as it concentrates on high-quality revenue. </p> <p>The post <a href="https://www.freightwaves.com/news/ups-shift-away-from-amazon-shows-bigger-payoff">UPS shift away from Amazon shows bigger payoff</a> appeared first on <a href="https://www.freightwaves.com">FreightWaves</a>.</p>”
- “<figure><div><img src="https://imgproxy.divecdn.com/nb8zojeztfJqtRHEFzevDvqf7eVDeaH88EIJzJwBBFE/g:nowe:0:335/c:3987:2252/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9ESEwtdG91ci0wMDlfQ1FsZVUybi5qcGc=.webp" /></div></figure><p>The reduction of two percentage points runs counter to the fuel fee increases other parcel carriers have installed in recent quarters.</p>”
Transaction data
The company generates tabular transaction data summarizing historical shipping activity, including rates and service lanes, which is essential for training cost-optimization and RFP management models.
Industrial data
This time-series evidence points to a proprietary dataset tracking the ongoing performance of over 2,000 carriers, providing a critical signal for building predictive industrial monitoring and carrier evaluation systems.
Geospatial data
Mactrans captures tabular geospatial data on its North American freight network, detailing cross-border routes and specialized services like Just-In-Time delivery, which is vital for modeling complex supply chain logistics.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Mactrans Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the mobility domain. Primary AI use-case: Industrial Monitoring. Market signal: Global Supply Chain Analytics market = $6.27B in 2023, CAGR 17.20% (source: Zion Market Research). Investment score 48.0/100 (confidence 0.49). Recommended action: Acquire.
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Learn before you deal
- How a Data Transaction Works3 min read
- What you are entitled to sell3 min read
- 5 Mistakes That Drive Buyers Away3 min read