What You Need to Know
- Breakouts in the Fraud Analytics predictive analytics are Review Analytics, Price Analytics, Performance Analytics. Seriously consider these technologies to gain a strategic advantage.
- The technologies who are at the peak of their interest are Number Analytics, Review Analytics, Performance Analytics.
- By far most employment needs are found in the Fraud, Google Analytics, Risk Analytics technologies.
- These 3 fields have the most active practitioners who have the specific skill set or experience: Google Analytics, Fraud, Risk Analytics.
- Google Analytics, Fraud, Host Analytics lead in searches for information online.
- These three technologies are receiving the highest investments to gain clients: Telecom Analytics, Web Analytics Software, Social Analytics.
- These three technologies have the most active advertisers: Web Analytics Software, Text Analytics, Social Analytics.
- In patents, these three technologies have the most coverage Fraud, Text Analytics, Performance Analytics.
- The most publications are available for Fraud, Google Analytics, Text Analytics.
- Instruction and courseware availability is highest in these technologies: Fraud, Google Analytics, Content Marketing Software.
The Fraud Analytics 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 Fraud Analytics’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:
000378 – Review Analytics
000310 – Price Analytics
000297 – Performance Analytics
000254 – Social Analytics
000254 – Host Analytics
000200 – minFraud
000165 – Content Marketing Software
000156 – Text Analytics
000147 – Fraud
000123 – Risk Analytics
000095 – Salesforce Analytics Cloud
000089 – Web Analytics Software
000062 – Google Analytics
000057 – Roambi Analytics
000052 – WANTED Analytics
000049 – Analytics SEO
000044 – Sift Science
000037 – SAP Predictive Analytics
000033 – Survey Analytics
000030 – Workforce Analytics
000026 – Pentaho Business Analytics
000000 – Telecom Analytics
000000 – Scholar Analytics
000000 – SAP Cloud for Analytics
000000 – Ruler Analytics
000000 – Number Analytics