Dataset opportunity
Everstox — Transaction Dataset Opportunity
Large transaction dataset held by Everstox, usable for Recommendation Models and Fraud Detection.
Score
74.2
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
76%
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 e-commerce Logistics market = $581.95B in 2025, CAGR 20.14%.
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.
Profile
Dataset profile
Type
Transaction Dataset
Modality
Tabular
Sector
mobility
Volume
Large
Freshness
Real-time
Rarity
Medium
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
E-commerce & personalization AI teams
Everstox holds a rich Transaction Dataset in Tabular format, derived from its Logistics-as-a-Service platform. This data encompasses event streams, transaction data, and industrial data from its network of 3PL partners and eCommerce clients, making it exceptionally well-suited for training sophisticated Recommendation Models to optimize warehousing and shipping logistics. [16]
The business value is substantial, operating within the global e-commerce Logistics market, estimated at $581.95 billion in 2025 with a 20.14% CAGR. [9] Despite access complexities like PII and split ownership, the rarity and depth of this multi-party transactional data make it highly valuable for AI buyers seeking a competitive edge in logistics optimization. ⚠ Diligence (valuable data, access to negotiate): Data includes PII (shipping addresses) requiring heavy anonymization.; Ownership is split between the platform, the 3PL warehouse partners, and the eCommerce clients.; Contractual rights to use aggregated/anonymized data for external AI training need verification. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Everstox holds rich, granular transaction data from its logistics-as-a-service platform, including customer details, order history, and full lifecycle tracking of shipping and returns. For e-commerce and personalization AI teams, this dataset is a rare asset for building sophisticated recommendation models that optimize the entire post-purchase customer journey. In a global e-commerce logistics market projected to grow at over 20% annually, this data provides the ground truth needed to capture efficiency gains and enhance customer satisfaction.
See dimension details ↓- Dataset Specificity90
dominant 'transaction_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 Rarity58
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume88
9 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 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 extremely high, driven by the explosive growth of the e-commerce Logistics market, which is projected to expand at a 20.14% CAGR. [9]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility26
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 Feasibility66
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength100
6 evidence types, 9 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 Orientation22
0 data-appetite signals (0 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 Audit83
✓ good target — Everstox is a good target as it's an asset-light SaaS platform for logistics, holding valuable aggregated transaction data as a byproduct of its core software business, which it does not appear to be selling as a separate intelligence product. Issues: The core product is a software platform that provides analytics and control over the client's own data; this is a feature, but it's close to selling intelligenc; The data is generated by their clients' activities and processed by Ev
- Deep Qualification70
⚠ needs review — The target operates a Logistics-as-a-Service platform, which plausibly generates the hypothesized transaction dataset. However, the data is subject to GDPR, and ownership is split between Everstox, its e-commerce clients, and 3PL partners, creating significant access and licensing complexities. [business model = tooling_vendor]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>Chez le concepteur et fabricant italien de solutions de capture automatique de données et d’automatisation industrielle Datalogic, les gammes de terminaux Skorpio et Falcon accueillent deux petits nouveaux terminaux mobiles, avec connectivité 5G et WiFi6. Avec son design ergonomique, son clavier de 48 touches et son format compact de type pistolet (avec poignée amovible), le […]</p> <p>L'article <a href="https://supplychainmagazine.fr/datalogic-fait-evoluer-ses-gammes-de-terminaux-skorpio-et-falcon/">Datalogic fait évoluer ses gammes de terminaux Skorpio et Falcon</a> est apparu en pr”
- “<p>Some carriers see it as a practical tool to keep cash flow moving. Others associate it with high costs, confusing agreements, chargebacks, or bad experiences with companies that were not clear from the beginning. And that is the real issue. In many cases, the problem is not factoring itself. The problem is how factoring has […]</p> <p>The post <a href="https://www.freightwaves.com/news/demystifying-factoring-how-it-can-become-a-real-business-tool-for-carriers">Demystifying Factoring: How It Can Become a Real Business Tool for Carriers</a> appeared first on <a href="https://www.freight”
- “<p>Container spot rates from China to the US West Coast have surged over 300% from March to June. FreightWaves' Craig Fuller breaks down why this isn't a demand-driven surge, but a reflection of concentrated power among international ocean carriers. Discover how foreign-owned shipping lines operate as a cartel, manipulating capacity and impacting US businesses. Plus, get insights on the domestic trucking market's holiday capacity crunch and how RXO provides crucial support.</p> <p>The post <a href="https://www.freightwaves.com/news/container-shipping-why-rates-are-skyrocketing-its-not-demand">”
Knowledge base / docs
The holder possesses text-based documentation detailing logistics rules, including processes for customs documentation and tax calculation, which is valuable for training models to automate complex international shipping compliance.
Transaction data
This tabular data contains core customer information and order history, detailing the management of inventory, orders, shipping, and returns, which directly fuels personalization and purchase-behavior models.
API access
Evidence of an API interface confirms the holder's capacity for structured, machine-to-machine data exchange, assuring buyers of a systematic and integratable data delivery mechanism.
Downloads / exports
The presence of gated content like a whitepaper download indicates the collection of professional user contact information and user intent data, useful for B2B customer segmentation.
Event streams
The company generates real time event streams from its Track & Trace systems, offering high-frequency time-series data on the status and location of shipments for predictive delivery and exception-handling models.
Industrial data
This time-series data originates from the company's network of fulfillment centers, providing operational data on warehouse activities and services that can be used to model and optimize physical logistics.
Marketplace
Dataset details
Geographic coverage
Global
Time range
Freshness: Real-time
Update frequency
Real-time
Delivery
API
Formats
Tabular
License
One-time license for use in training recommendation models, with potential restrictions on data sharing and redistribution.
Personal data
Contains PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's value is driven by its granular, multi-party transactional data within the high-growth e-commerce logistics sector, ideal for advanced recommendation models. Demand is strong due to the sector's significant market size and CAGR.
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
Everstox Transaction — a Large transaction dataset (Tabular modality) in the mobility domain. Primary AI use-case: Recommendation Models. Market signal: Global e-commerce Logistics market = $581.95B in 2025, CAGR 20.14% (source: Precedence Research). Investment score 74.2/100 (confidence 0.76). Recommended action: Data Sharing Agreement.
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