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        Ventana Research Analyst Perspectives

        As I discussed in the state of data and analytics in the cloud recently, usability is a top evaluation criterion for organizations in selecting cloud-based analytics software. Data access of cloud and on-premises systems are essential antecedents of usability. They can help business people perform analytic tasks themselves without having to rely on IT. Some tools allow data integration by business users on an ad hoc basis, but to provide an enterprise integration process and a governed...

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        Topics: Big Data, Sales Performance, Software as a Service, Mobile Technology, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Information Management, Operational Intelligence, Data

        Calabrio is a vendor of workforce optimization software whose core product is Calabrio ONE. It includes the common workforce optimization applications: call recording, quality management, workforce management and analytics. The company is rated Hot in our 2015 Workforce Optimization Value Index, and its product suite is the highest rated in the Usability category. Since our assessment, each of the modules has undergone upgrades, Calabrio has introduced more cloud-based services, and its...

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        Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Cloud Computing, Call Center

        Through a continuing program of acquisitions and internal development, NICE Systems has transitioned from being a vendor of workforce optimization systems to one focused on aspects of the customer experience, notably voice of the customer (VOC), customer engagement analytics and customer journey mapping. It is also moving to cloud-based services from products installed on customers’ premises and is taking a business-solution approach (providing previously integrated and configured products that...

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        Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Business Collaboration, Cloud Computing, Call Center

        From its history of managing postal mail, Pitney Bowes has expanded into products for data management, analytics and location intelligence, as my colleague Mark Smith noted. Continuing this expansion through internal development and acquisitions of vendors such as Portrait Software and RTC, it has added to its portfolio products that include customer information management and customer engagement.

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        Topics: Big Data, Customer Performance, Business Analytics, Business Collaboration, Cloud Computing, Call Center

        At the end of last year, I wrote about Interactive Intelligence’s release of a new service, PureCloud. It was the company’s first step into the multitenant cloud computing market, using Amazon Web Services and aimed at small-to-midsize contact centers. To help companies understand the different cloud-computing models, I provided answers to Interactive Intelligence questions on the advancements of these approaches for business.

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        Topics: Customer Experience, Customer Performance, Cloud Computing, Call Center

        Optimization is the application of algorithms to sets of data to guide executives and managers in making the best decisions. It’s a trending topic because using optimization technologies and techniques to better manage a variety of day-to-day business issues is becoming easier. I expect optimization, once the preserve of data scientists and operations research specialists will become mainstream in general purpose business analytics over the next five years.

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        Topics: Big Data, Performance Management, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Performance, Financial Performance, Information Management, Price Optimization

        Our research into next-generation predictive analytics shows that along with not having enough skilled resources, which I discussed in my previous analysis, the inability to readily access and integrate data is a primary reason for dissatisfaction with predictive analytics (in 62% of participating organizations). Furthermore, this area consumes the most time in the predictive analytics process: The research finds that preparing data for analysis (40%) and accessing data (22%) are the parts of...

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        Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization

        Recently my colleague Tony Cosentino wrote an analyst perspective asserting that big data analytics will displace net promoter score (NPS) for more effectively measuring the entire customer experience. This prompted a response from Maxie Schmidt-Subramanian, asserting that big data and NPS aren’t the only ways to measure customer experience success. The main point of Tony’s piece, as I interpret it, is that NPS is just a number, but big data analytics can reveal much more about customer...

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        Topics: Big Data, Customer Performance, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Call Center

        The Performance Index analysis we performed as part of our next-generation predictive analytics benchmark research shows that only one in four organizations, those functioning at the highest Innovative level of performance, can use predictive analytics to compete effectively against others that use this technology less well. We analyze performance in detail in four dimensions (People, Process, Information and Technology), and for predictive analytics we find that organizations perform best in...

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        Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Operational Performance Management (OPM), Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Location Intelligence, Oracle, Information Optimization

        To impact business success, Ventana Research recommends viewing predictive analytics as a business investment rather than an IT investment. Our recent benchmark research into next-generation predictive analytics reveals that since our previous research on the topic in 2012, funding has shifted from general business budgets (previously 44%) to line of business IT budgets (previously 19%). Now more than half of organizations fund such projects from business budgets: 29 percent from general...

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        Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Customer Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Business Performance Management (BPM), Rapidminer
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        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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