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        Analyst Perspectives

        The emergence of the Chief Revenue Officer (CRO) has mirrored the adoption of the subscription model and the development of multiple selling and buying channels over and above the traditional direct sales model, referred to as Revenue Management. Supporting the traditional sales team and management was the sales operations team with responsibilities around incentive compensation, territory and quota planning, sales metrics and reporting and sales forecasting as well as sales engagement and...

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        Topics: Sales, Customer Experience, Analytics, Sales Performance Management, Digital Commerce, Subscription Management, partner management, Revenue Management, Sales Engagement

        Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a...

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        Topics: Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

        Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As...

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        Topics: Analytics, Cloud Computing, Data Governance, Data Integration, Data, Digital Technology, data lakes, data operations, data platforms, AI and Machine Learning

        How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but...

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        Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, Streaming Analytics, AI and Machine Learning

        When NICE acquired inContact in 2016, it began a transformation that saw it broaden its product offering and positioned itself to play a larger role in the contact center and customer experience industries. It was a prescient move, creating a firm that could supply end-to-end contact center functionality in the cloud. And it anticipated today’s market dynamic, in which NICE and its competitors are racing to define (and capitalize on) the post-contact center future.

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        Topics: Customer Experience, Voice of the Customer, Business Continuity, Analytics, Contact Center, Data, Digital transformation, agent management, Digital Business, Experience Management, Customer Experience Management, Field Service, customer service and support, AI and Machine Learning

        Our research shows that nearly all financial service organizations (97%) consider it important to accelerate the flow of information and improve responsiveness. Even just a few years ago, capturing and evaluating this information quickly was much more challenging, but with the advent of streaming data technologies that capture and process large volumes of data in real time, financial service organizations can quickly turn events into valuable business outcomes in the form of new products and...

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        Topics: Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics

        In part one of this Analyst Perspective on the use of artificial intelligence within contact center applications, we focused on the evolution — and resulting benefits — of tools embedded with AI, including ease-of-use for non-data-scientists.

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        Topics: Customer Experience, Voice of the Customer, Analytics, agent management, Customer Experience Management, Field Service, customer service and support, AI and Machine Learning

        Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. It can enable data engineers, data scientists, analysts and other workers to process big data and unify analytics through a single interface. The platform supports streaming data, SQL queries, graph processing and machine learning. It also offers a collaborative user interface —...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Information Management, Data, data lakes, AI and Machine Learning

        The work environment today demands that your organization advances the efficiency to execute business processes for continuous operations to have a positive impact on business performance. The capability to be responsive to any range of minor to disruptive business events is required to support business continuity and level of organizational readiness to meet the needs of digital business. Ventana Research asserts that in 2025, one-quarter of organizations will remain digitally ineffective in...

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        Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Cloud Computing, Contact Center, Data, Digital Technology, Operations & Supply Chain, Enterprise Resource Planning, Digital transformation, natural language processing, continuous supply chain, agent management, Digital Business, Experience Management, Field Service, Process Mining, Streaming Analytics, AI and Machine Learning

        When artificial intelligence emerged from the labs and vendors started offering it as a component of their software, many contact-center buyers shied away from it. From their point of view, AI and machine learning tools were new, expensive, relatively untested and had an uncertain use case. This stance was understandable, as contact center professionals are traditionally expected to be risk-averse when deploying technology into their operations. Contact centers are, by design, supposed to be...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, agent management, Customer Experience Management, Field Service, customer service and support, AI and Machine Learning
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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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