SaaS PREDICTIVE ANALYTICS REPORT

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ANALYSIS

What You Need to Know

  • Breakouts in the SaaS predictive analytics are Infrastructure as a service, Platform as a service, Data governance. Seriously consider these technologies to gain a strategic advantage.
  • The technologies who are at the peak of their interest are Business analytics, *aaS, User experience.
  • By far most employment needs are found in the JavaScript, User experience, Web development technologies.
  • These 3 fields have the most active practitioners who have the specific skill set or experience: JavaScript, Web development, User experience.
  • Crowdfunding, Ruby on Rails, JavaScript lead in searches for information online.
  • These three technologies are receiving the highest investments to gain clients: Infrastructure as a service, Platform as a service, Source code escrow.
  • These three technologies have the most active advertisers: Web development, Content management system, Collaborative software.
  • In patents, these three technologies have the most coverage User experience, JavaScript, Web application.
  • The most publications are available for Customer relationship management, User experience, Web application.
  • Instruction and courseware availability is highest in these technologies: JavaScript, Crowdfunding, User experience.

The SaaS 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 SaaS’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:

135520 – Infrastructure as a service
000621 – Platform as a service
000348 – Data governance
000348 – Agile software development
000321 – *aaS
000278 – Mobile backend as a service
000199 – Data loss
000185 – Information sharing
000176 – Business analytics
000173 – User experience
000173 – Multitenancy
000135 – Web application framework
000112 – Desktop as a service
000096 – Software delivery
000087 – Laravel
000083 – Web application
000067 – Software architecture
000059 – Procurify
000051 – Freemium
000046 – Vaporware
000038 – JavaScript
000035 – Ruby on Rails
000035 – Regression testing
000035 – Customer relationship management
000031 – Gamification
000030 – Web analytics
000022 – Web development
000022 – Crowdfunding
000013 – QuinStreet
000000 – Source code escrow
000000 – Software copyright
000000 – MediaWiki
000000 – Donationware
000000 – Content management system
000000 – Collaborative software


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