The contact center has long represented the starting point for customer experience initiatives. Now, however, most organizations are finding that they need to invest beyond this singular point of engagement. When organizations look at customer experience holistically, they see the need to incorporate the perspectives of people in other departments and channels of customer engagement. These diverse new points of view come with an interest in deploying CX technology that also meets their needs. As a result, organizations are looking at not just vendors traditionally in the contact center space but those that operate across the entire customer journey, and shifting some of the existing contact center budgets to tools that fill multiple roles.
The Opportunity for CX is Beyond Your Contact Center
Posted by
Keith Dawson on Jan 26, 2021 3:00:00 AM
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Topics: Sales, Customer Experience, Marketing, Contact Center
Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.
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Topics: business intelligence, Analytics, Data Governance, Data Preparation, Information Management, Data, data lakes
Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data. Our research shows that nearly three-quarters of organizations deploy both data lakes and data warehouses but are using a variety of approaches which can be cumbersome. A single platform that can provide both capabilities will help address organizations’ requirements.
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Topics: PROS Pricing, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, data lakes, AI and Machine Learning
Tableau and Salesforce bring New Look to Business Analytics
Posted by
David Menninger on Jan 20, 2021 3:00:00 AM
Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever. However, the process of using data and analytics is not always easy. The necessary tools are often separate, but our research shows organizations prefer an integrated environment. In our Data Preparation Benchmark Research, we found that 41% of participants use Analytics and Business Intelligence tools for data preparation.
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Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Information Management, Internet of Things, Data, Digital Technology, natural language processing, Conversational Computing, AI and Machine Learning
Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data. Big data architectures have attempted to solve the problem with large pools of cost-effective storage, but in doing so have often created on-premises management and administration challenges. These challenges of acquiring, installing and maintaining large clusters of computing resources gave rise to cloud-based implementations as an alternative. Public cloud is becoming the new center for data as organizations migrate from static on-premises IT architectures to global, dynamic and multi-cloud architectures.
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Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Data, data lakes, AI and Machine Learning
Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads running independently, data spread across multiple data centers, data governance, etc. In our ongoing benchmark research project, we are researching the ways in which organizations work with big data and the challenges they face.
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Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, Information Management (IM), data lakes, AI and Machine Learning
True leadership is the ability to motivate sales organizations to perform at their best. But the demand to do so requires the support of an orchestrated process and tools designed to help sales teams work in a directed manner that can help attain quotas through compensation plans. To manage quotas and resources and optimize sales compensation, everyone in the sales organization, from managers to selling professionals, needs unified and planful sales leadership and operations.
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Topics: Sales, Sales Performance Management, intelligent sales, sales enablement
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