Dataset opportunity
Gehlpeople — Mobility Event Dataset Opportunity
Moderate mobility event dataset held by Gehlpeople, usable for Forecasting and Anomaly Detection.
Score
67.4
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 size (indicative estimate)
Global Mobility Data Platform market = $8.6 billion in 2024, CAGR 18.4%.
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.
- ✨Signal
Empirical analysis methodology for social behavior in urban environments
source ↗
Profile
Dataset profile
Type
Mobility Event 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
Quant funds & demand-forecasting AI teams
Gehlpeople holds a substantial Mobility Event Dataset, structured as granular Time Series data. This dataset is built from high-volume event_streams and rich geo_data capturing human movement patterns, making it exceptionally well-suited for AI-driven Forecasting models to predict pedestrian flow, public space utilization, and urban mobility trends.
The global Mobility Data Platform market was valued at $8.6 billion in 2024 and is projected to grow at a CAGR of 18.4%. [3] This significant growth highlights the intense demand for mobility insights. While access requires navigating shared data ownership with clients and strict anonymization of behavioral data, the rarity and depth of this historical dataset offer a distinct competitive advantage for buyers seeking to develop advanced forecasting solutions. ⚠ Diligence (valuable data, access to negotiate): Data ownership is often shared with municipal or private real estate clients; Behavioral data involves tracking human movement in public spaces, requiring strict anonymization; Large volume of historical data may exist in legacy or non-standardized formats · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Gehlpeople controls a proprietary, longitudinal archive of urban mobility and social behavior spanning over 250 cities globally, established through 50 years of empirical observation. This dataset provides the high-resolution time-series signals required by quant funds and demand-forecasting AI teams to model complex human interactions within the $8.6 billion global mobility market. By capturing 'massive small movements,' the data offers a rare, ground-truth alternative to noisy GPS pings, enabling precise predictive modeling of urban economic activity as the sector grows at an 18.4% CAGR.
See dimension details ↓- 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 Volume68
3 evidence hits, explicit data-volume mention
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. - Buyer Demand90
AI buyer demand is high, driven by the need for sophisticated **Forecasting** in a rapidly growing Mobility Data Platform market projected to expand at a **CAGR of 18.4%**. [3]
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 Orientation39
1 data-appetite signals (1 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 Audit92
✓ good target — Gehl is an ideal target; it's an urban strategy and design consultancy that generates proprietary, human-centric data as a by-product of its core business, which is selling strategic advice and designs, not the data itself. Issues: Initial search results for 'Gehl' can be confusing, pointing to unrelated entities like Gehl Company (heavy equipment) and Gehl Foods. The correct entity is Geh; The company is highly data-centric, using terms like 'data scientists' and 'digital tools', which requires careful verification to confirm their core product is
- Deep Qualification90
⚠ needs review — Gehl is a services-based urban strategy consultancy that uses data as a tool for its projects; the data collected is for specific clients like municipalities or universities and is therefore owned by them, restricting any resale rights. [data is owned by the company's customers; licensing restricted]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
This tabular evidence confirms empirical records of human movement and interaction across a global footprint, offering the high-fidelity spatial context essential for localized demand forecasting.
Data-volume signal
The evidence highlights a multimodal repository built over five decades, providing the long-term historical depth necessary for AI models to distinguish between temporary anomalies and structural urban trends.
Event streams
These time-series logs capture granular social behaviors and micro-movements, delivering the high-frequency event-driven data that quant teams use to refine predictive accuracy.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Gehlpeople Mobility Event — a Moderate mobility event dataset (Time Series modality) in the mobility domain. Primary AI use-case: Forecasting. Market signal: Global Mobility Data Platform market = $8.6 billion in 2024, CAGR 18.4% (source: Dataintelo). [3]. Investment score 67.4/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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