Dataset opportunity
Chargeguru — Mobility Telemetry Dataset Opportunity
Moderate mobility telemetry dataset held by Chargeguru, usable for Predictive Maintenance and Anomaly Detection.
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
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 EV Charger Predictive Maintenance Market = $2.8 billion in 2025, CAGR 12.4% (source: Dataintelo). [1]
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
Mobility Telemetry Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
Industrial AI & maintenance-optimization vendors
Chargeguru holds a Mobility Telemetry Dataset structured as Time Series data, containing event_streams, geo_data, and raw iot_data from its network of electric vehicle chargers. This rich, real-world operational data is specifically suited for developing and training Predictive Maintenance models designed to anticipate hardware failures, reduce downtime, and optimize network-wide reliability.
The business value of this data is directly linked to the EV Charger Predictive Maintenance Market, a sector valued at $2.8 billion in 2025 and projected to grow at a 12.4% CAGR. [1] Despite access complexities—including PII requiring robust anonymization, shared data ownership with B2B clients, and governance challenges following the Zeplug merger—the rarity and direct applicability of this dataset for high-value AI applications make it a compelling asset for negotiation. ⚠ Diligence (valuable data, access to negotiate): Data includes PII (user charging habits and locations) requiring anonymization.; Ownership may be shared with B2B clients (companies/condominiums) where chargers are installed.; Recent merger with Zeplug might complicate data governance across the new group. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence proves Chargeguru holds a proprietary, high-resolution dataset capturing the real-world operational and usage patterns of thousands of EV chargers across Europe. This is a critical asset for industrial AI and maintenance-optimization vendors seeking to build next-generation predictive maintenance solutions. The data directly enables the training of models to anticipate component failure and optimize service logistics, offering a significant competitive edge in the rapidly expanding EV charger market, projected to reach $2.8 billion by 2025. This unique time-series data is the key to unlocking efficiency and reliability in the future of mobility infrastructure.
See dimension details ↓- Dataset Specificity90
dominant 'iot_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 Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Predictive Maintenance
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 significant growth in the predictive maintenance market for EV infrastructure, which is expanding at a 12.4% CAGR. [1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility20
restricted/unknown
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility30
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 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 — 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 — Chargeguru's core business is providing EV charging solutions as a service, which includes chargepoint management software, making it a seller of intelligence and not just a holder of dormant data. Issues: The company's core offering is a service that includes 'chargepoint management software solutions' and 'smart charging features' like load balancing and usage a; They offer software to business clients (e.g., hotels, restaurants) that enables dynamic pricing, real-time cost/revenue
- Deep Qualification90
✓ pass — Chargeguru is a service provider for EV charger installation and management, not a data seller. The data it holds is a plausible byproduct, but ownership is mixed and subject to GDPR, with data governance complexities heightened by the recent Zeplug merger.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
The dataset contains continuous time-series data from thousands of European charging points, capturing operational metrics like power load and session duration, which is essential for training anomaly detection models.
Geospatial data
This proprietary tabular database provides crucial context on charger locations, technical specifications, and installation constraints, enabling more accurate, hardware-specific maintenance predictions and efficient logistics.
Event streams
This aggregated time-series data reveals real-world usage patterns and driver behaviors, providing a demand-side signal that is critical for modeling network stress and optimizing asset management.
Coverage
Scanned sources
Deliverable
Premium dataset report
Chargeguru Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global EV Charger Predictive Maintenance Market = $2.8 billion in 2025, CAGR 12.4% (source: Dataintelo). [1]. Investment score 48.0/100 (confidence 0.49). Recommended action: Data Sharing Agreement.