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Market entry comparison

Global Market Entry Navigator

Compare overseas market candidates on scale, growth, purchasing power, digital reach, trade exposure, and inflation context — using latest available World Bank indicators mirrored in BizNavi Hub.

What this country market comparison tool does

Global Market Entry Navigator helps you run an international expansion shortlist: pick candidate countries and compare market size, growth, purchasing power, internet adoption, import scale, and inflation side by side. It is a market entry analysis aid — not an AI that picks a winner.

Why compare markets this way

Overseas expansion decisions usually mix public macro indicators with your own margin assumptions. This tool keeps those layers visible: latest available World Bank series from the Hub mirror, plus an optional expected-margin overlay you enter yourself.

Method & data

Observations are read from BizNavi Hub’s World Bank WDI mirror (same path as Data Explorer). We do not call the World Bank API from your browser for each country×indicator.

  • Countries only — World Bank region aggregates are excluded.
  • Each cell shows value, year, and missing/stale state when applicable.
  • Optional score uses transparent, editable weights and min-max normalization inside your selection.
  • Scenario links (?gme=) store countries, weights, sort, and margin overlays — never raw API payloads or PII.

Limits

Not tax, legal, or investment advice. Indicator years differ. Trade % of GDP is unavailable in Phase A; imports are used as the trade-exposure proxy. Official tariff/tax rates are not auto-filled.

FAQ

Does this recommend the best country?

No. It compares indicators you select. Ranking is relative and optional.

Is the data real-time?

No. It shows latest available / latest reported values from the Hub World Bank mirror.

Why is Trade % of GDP missing?

That series is not ingested in the Hub mirror yet. Phase A uses imports of goods and services (NE.IMP.GNFS.CD).

Can I share my comparison?

Yes. Copy scenario link encodes selection and settings in ?gme= without storing PII on the server.

How does the score treat missing data?

Missing metrics are skipped and remaining weights are renormalized — they are not scored as zero.