Dataset opportunity
Pme Express — Mobility Event Dataset Opportunity
Moderate mobility event dataset held by Pme Express, usable for Forecasting and Anomaly Detection.
Score
68.3
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
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 Transportation Analytics market = $12.61B in 2024, CAGR 23.8% (source: Grand View Research). [15]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-11
Distribution automobile : l’heure délicate des successions familiales
journalauto.com ↗ - 📰press2026-06-11
Stellantis dope une Charger avec une batterie solide
journalauto.com ↗ - 📰press2026-06-10
Harley-Davidson to reshore Revolution Max engine production
manufacturingdive.com ↗ - 📰press2026-06-10
Razor reshapes supply chain to weather Trump-era China tariffs
manufacturingdive.com ↗
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
Mobility Event Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — GDPR-sensitive (PII review)
Buyer persona
Quant funds & demand-forecasting AI teams
Pme Express holds a valuable Mobility Event Dataset structured as a Time Series. This dataset uniquely combines `event_streams`, `geo_data`, and `transaction_data`, providing a comprehensive view of mobility operations. Its granular, time-stamped nature makes it exceptionally well-suited for the AI buyer use case of Forecasting, allowing for the development of models to predict delivery times, optimize routes, and anticipate demand fluctuations.
The market this data serves, Transportation Analytics, is substantial and rapidly growing, valued at $12.61 billion in 2024 with a projected CAGR of 23.8%. [15] While the data contains PII requiring strict anonymization and may need consolidation from legacy TMS, its operational rarity and depth are highly sought after. For an AI buyer, the strategic value of gaining predictive accuracy in logistics justifies the investment in navigating these access complexities. ⚠ Diligence (valuable data, access to negotiate): Contains PII (sender/recipient names and addresses) requiring strict anonymization; Data is likely stored in legacy transport management systems (TMS); Operational logs may require consolidation from different regional delivery hubs · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Pme Express owns a proprietary, high-frequency dataset capturing the pulse of European express freight through time-series event streams, geographic trade flows, and historical shipping volumes. This high-rarity data is a direct input for sophisticated forecasting models used by quant funds and AI teams to predict economic activity and supply chain shifts. In a rapidly growing transportation analytics market (projected at $12.61B in 2024), this dataset offers a distinct informational advantage for generating alpha and optimizing logistics.
See dimension details ↓- Dataset Specificity90
dominant 'event_streams', 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 Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Forecasting
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
The Mobility as a Service (MaaS) market, a primary consumer of mobility data for AI-powered demand forecasting, is expected to grow at a CAGR of 33.65% from 2025 to 2032. [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 License62
ownership=owned, 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 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 Surplus70
surplus=medium, 4 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 Audit100
✓ good target — PME Express is an excellent target as it's an operational SME in express transport and logistics with its own fleet, generating proprietary mobility data as a by-product of its core business, and shows no indication of selling this data.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Event streams
This evidence type consists of time-series data tracking delivery events and timestamps for shipments, providing a high-frequency signal for forecasting models that monitor economic activity.
Geospatial data
This tabular data details proprietary origin-destination pairs for freight, revealing crucial commercial trade-flow patterns across Europe for supply chain analysis.
Transaction data
This tabular data provides historical shipping volumes and package details segmented by industry sector, enabling granular, sector-specific demand forecasting.
Coverage
Scanned sources
Deliverable
Premium dataset report
Pme Express Mobility Event — a Moderate mobility event dataset (Time Series modality) in the mobility domain. Primary AI use-case: Forecasting. Market signal: Global Transportation Analytics market = $12.61B in 2024, CAGR 23.8% (source: Grand View Research). [15]. Investment score 68.3/100 (confidence 0.49). Recommended action: Data Sharing Agreement.