Dataset opportunity
Sparqle — Mobility Event Dataset Opportunity
Moderate mobility event dataset held by Sparqle, usable for Forecasting and Anomaly Detection.
Score
68.6
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
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 Location Intelligence market = $25.3 billion in 2025, CAGR 15.8% (source: Future Market Insights). [4]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-30
General Motors is driving toward supply chain resiliency
supplychaindive.com ↗ - 📰press2026-07-30
Feds opening exports office as part of strategy to diversify trade
canadianmanufacturing.com ↗ - 📰press2026-07-30
Why DEF sensors are essential to American trucking
fleetowner.com ↗ - 📰press2026-07-30
EMASS collaborates with Bosch to deliver tracking solutions
iotinsider.com ↗ - 📰press2026-07-30
Purolator donates 14 retired trucks to Canadian food banks
insidelogistics.ca ↗
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
Sparqle holds a proprietary Mobility Event Dataset structured as a Time Series. This data, accessible via `api` and `event_streams`, includes rich `geo_data` from its delivery platform, capturing detailed operational events like fleet movements and delivery statuses. The temporal and geographical nature of this dataset makes it exceptionally well-suited for AI-driven Forecasting applications, such as predicting delivery times, optimizing routes, and planning for demand surges.
The business value of such data is reflected in the global Location Intelligence market, which is estimated at $25.3 billion in 2025 and projected to grow at a 15.8% CAGR. [4] This high-growth market underscores the significant demand for granular geospatial insights for operational efficiency. While access requires navigating PII anonymization, potential retailer contract restrictions, and specific telemetry extraction, the rarity and depth of this real-world operational data offer a substantial competitive advantage for AI buyers seeking to build predictive models. ⚠ Diligence (valuable data, access to negotiate): Contains PII (recipient addresses and names) requiring anonymization; Operational data might be partially restricted by retailer contracts; Real-time fleet telemetry requires specific extraction from their delivery platform · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence proves Sparqle possesses a proprietary, real-time dataset of e-commerce delivery events across Europe, captured directly from its logistics operations. This high-rarity time-series data is ideal for AI forecasting models, offering quant funds a unique signal on retail activity and providing demand-planning teams with ground-truth logistics intelligence. As the location intelligence market grows towards a projected $25.3 billion by 2025, this dataset provides a crucial, granular view into last-mile delivery velocity and sustainability trends, making it a valuable asset for predicting economic patterns.
See dimension details ↓- Acquisition Feasibility4
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. - Buyer Demand90
AI buyer demand is driven by the high-growth Location Intelligence market, which is projected to expand at a 15.8% CAGR, creating a strong need for predictive geospatial datasets. [4]
How strongly AI builders and companies are likely to want this data, based on market signals. - Dataset Specificity78
dominant 'event_streams', sector mobility, 2 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
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 Value74
fit for Forecasting
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Legal Accessibility32
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - 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 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 — Sparqle is an operational SME providing sustainable last-mile delivery services using its own fleet and software; while it heavily promotes its technology and offers data reporting to clients, its core business is the delivery service itself, making its operational data a potentially valuable, albeit not entirely dormant, asset. Issues: Company heavily markets its 'proprietary software', 'AI-powered routing', and 'extensive data reporting' as key differentiators. [17, 23, 24]; It offers an API and webhooks for order integration and tracking, indicating a high level of technical maturity. [5]; The line between selling a tech-enabled service and selling the technology/intelligence itself is thin. [1, 23]; Pitchbook classifies their primary industry as 'Business/Productivity Software', which conflicts with the ICP. [1]
- Deep Qualification90
✓ pass — Sparqle is a sustainable delivery operator, not a data seller; its core business of last-mile logistics generates a valuable, dormant 'Mobility Event Dataset' as a byproduct. This data is highly coherent with the 'Logistics Telemetry' niche. A recent funding round in February 2026 aims to expand its tech platform and European presence, but data access is complex due to PII and likely data ownership by retailer clients like Decathlon and Ricoh.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
This tabular data provides detailed geospatial information on delivery routes and outcomes across Europe, offering valuable signals for regional economic analysis and sustainability impact reporting.
Event streams
This core time-series evidence points to a continuous stream of e-commerce delivery events, providing the granular data needed for building high-frequency demand-forecasting models.
API access
The existence of an API for retailers demonstrates a mature, structured, and programmatically accessible data source, ensuring a high-quality data flow for seamless AI model integration.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Sparqle Mobility Event — a Moderate mobility event dataset (Time Series modality) in the mobility domain. Primary AI use-case: Forecasting. Market signal: Global Location Intelligence market = $25.3 billion in 2025, CAGR 15.8% (source: Future Market Insights). [4]. Investment score 68.6/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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Learn before you deal
- What is a Dataset Worth?3 min read
- How a Data Transaction Works3 min read
- What you are entitled to sell3 min read