Cities and countries pour billions into sustainable mobility, but the data is scattered. Public dashboards like EAFO, OpenChargeMap, or operator reports give partial views, while consulting studies are static snapshots. The result: it’s hard to compare two markets side-by-side or track progress over time.
This segment brings together web intelligence and curated APIs under one taxonomy. You get standardized indicators for carsharing and EV charging, operator rankings, and a MaaS maturity index with clear explanations. For consultants, foresight teams, or policymakers, it means moving from patchwork data to a comparable, explainable view of mobility ecosystems, at local, national, and global scale.
Normalize territories (city, region, country) into a consistent taxonomy.
Count active operators and rank the top three (≥300 vehicles for carsharing).
Track public EV charging networks, excluding private or closed systems.
Compute a MaaS maturity index (0–100) combining operator scale, ticketing, and digital integration.
Provide plain-language comments and a confidence score for every variable.
This segment is activated with a blend of trusted sources and your own inputs
AI reasoning
Web intelligence
Comparable datasets on EV and carsharing ecosystems across geographies.
Top-3 operator lists with fleets and charging points, standardized.
MaaS maturity index with clear explanatory comments.
Ready-to-use outputs in CSV, Sheets, JSON, or API for BI or CRM.
Your questions on this segment, answered
Your questions on this segment, answered
How quickly can we get a first extract for a new geography?
First extracts are typically delivered within minutes to hours, depending on scope and data volume.
What confidence should I place in the maturity scores?
Every field includes a confidence % based on source availability, freshness, and methods, so you can weigh reliability transparently.
Can we integrate the outputs into BI, CRM, or policy tools?
Yes. Exports are available in CSV, Sheets, JSON, or API for seamless integration with dashboards, models, or CRMs.
How does this dataset differ from EAFO, OpenChargeMap, or city dashboards?
Those sources show partial data; Starzdata combines them with Smart Queries into a standardized, explainable dataset with confidence scoring.
How do you ensure comparability across cities and countries?
All geographies are normalized under one taxonomy, and scoring rules are consistent worldwide, making maturity indices directly comparable.
How are operator counts and top-3 rankings defined?
Carsharing operators must have at least 300 active vehicles; charging rankings include only public networks with open access.
What exactly does the MaaS maturity index measure?
It scores digital integration, ticketing and booking coverage, operator scale, and EV charging density, normalized to 0–100.
How often is the mobility dataset refreshed?
Updates run monthly by default, with on-demand refreshes for major operator or policy changes.
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