Mobile Payment PREDICTIVE ANALYTICS REPORT

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ANALYSIS

What You Need to Know

  • Breakouts in the Mobile Payment predictive analytics are Street Invoice, Amazon Payments, Square. Seriously consider these technologies to gain a strategic advantage.
  • The technologies who are at the peak of their interest are Payment Depot, Square, Braintree.
  • By far most employment needs are found in the Square, Smartphones, IPhone technologies.
  • These 3 fields have the most active practitioners who have the specific skill set or experience: Square, IPhone, Smartphones.
  • Square, IPhone, Smartphones lead in searches for information online.
  • These three technologies are receiving the highest investments to gain clients: Mobile application management, Mobile cloud computing, Mobile Device Management Software.
  • These three technologies have the most active advertisers: Mobile Device Management Software, Mobile application management, Two-factor authentication.
  • In patents, these three technologies have the most coverage Square, Smartphones, IPhone.
  • The most publications are available for Square, IPhone, Smartphones.
  • Instruction and courseware availability is highest in these technologies: IPhone, Square, Smartphones.

The Mobile Payment report evaluates technologies and applications in terms of their business impact, adoption rate and maturity level to help users decide where and when to invest.

The Predictive Analytics Scores below – ordered on Forecasted Future Needs and Demand from High to Low – shows you Mobile Payment’s Predictive Analysis. The link takes you to a corresponding product in The Art of Service’s store to get started.

The Art of Service’s predictive model results enable businesses to discover and apply the most profitable technologies and applications, attracting the most profitable customers, and therefore helping maximize value from their investments. The Predictive Analytics algorithm evaluates and scores technologies and applications.

The platform monitors over ten thousand technologies and applications for months, looking for interest swings in a topic, concept, technology or application, not just a count of mentions. It then makes forecasts about the velocity of the interest over time, with peaks representing it breaking into the mainstream. Data sources include trend data, employment data, employee skills data, and signals like advertising spent, advertisers, search-counts, Instruction and courseware available activity, patents, and books published.

Predictive Analytics Scores:

001607 – Street Invoice
000459 – Amazon Payments
000414 – Square
000322 – Smartphones
000233 – Mobile application management
000228 – Braintree
000206 – Mobile banking
000150 – MobileIron
000075 – IPhone
000074 – Mobile Device Management Software
000070 – Mobile security
000064 – Two-factor authentication
000050 – Microsoft Visual Studio
000043 – Social commerce
000040 – LTE Advanced
000021 – GLONASS
000013 – Mobile cloud computing
000000 – SecurionPay
000000 – Payment Evolution
000000 – Payment Depot
000000 – PassMarket
000000 – Mobile High-Definition Link
000000 – eSurvey


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