Contactless Payments Market Data: 2025-2030

Our Contactless Payments market analysis provides exhaustive data coverage of the market in its entirety, including the adoption of mobile wallets featuring contactless payment technology, the growth of contactless transactions and its associated values. The data suite includes access to the full set of forecast data of 139 tables and over 60,000 datapoints, as well as an accompanying report analysing the reasons for growth. The metrics comprised in the research suite include:

• The number of users of contactless payments
• The total transaction value of contactless payments    
• The total volume of contactless payments made annually.

All report content is delivered in the English language.

These metrics are split by the following key segments:

• Contactless Cards
• Mobile Payments, further split by:
  • Apple Pay
  • Google Pay
  • Samsung Pay
  • Other Original Equipment Manufacturer (OEM) Pay
• Wearable Payments
• Contactless Ticketing Payments

The forecast data also includes market sizing for contactless tokenisation and contactless-enabled ATMs.

The data itself is accompanied by a Data & Forecasting report; analysing the main drivers of growth across key forecast metrics, as well as explaining the fundamental methodology and assumptions involved. Taken together, the research is a vital tool for sizing the contactless payments market.

Juniper Research’s Interactive Forecast Excel contains the following functionality:

• Statistics Analysis: Users benefit from the ability to search for specific metrics, displayed for all regions and countries across the data period. Graphs are easily modified and can be exported to the clipboard.
• Country Data Tool: This tool lets users look at metrics for all regions and countries in the forecast period. Users can refine the metrics displayed via a search bar.
• Country Comparison Tool: Users can select and compare specific countries. The ability to export graphs is included in this tool.
• What-if Analysis: Here, users can compare forecast metrics against their own assumptions, via 5 interactive scenarios.

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