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client analytics

Results 1 - 22 of 22Sort Results By: Published Date | Title | Company Name
Published By: Socialbakers     Published Date: Jan 26, 2015
In this exclusive report, you’ll find out how to use deep social media data to pursue new clients, perfect your data-driven pitches, and master the results with custom, easy-to-read reporting. It’s a data world, and agencies need to bring the best insights on the market to win new clients and keep existing business. This guide will get you started.
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benefits of using social media data, network management, data center design and management, content management
    
Socialbakers
Published By: IBM     Published Date: Jul 21, 2016
This e-book explores the many uses of client insights for banking and wealth management. By using sophisticated analytics and cognitive capabilities, your organization can gain deep understanding of what matters most to your clients. Knowing them well helps to provide targeted, personalized service that they value and increases their loyalty. It’s a smart pathway for reducing churn and generating new revenue models through meaningful cross-selling opportunities in today’s customer-centric world.
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ibm, banking, client insight, financial services, engagement, client insights, enterprise applications
    
IBM
Published By: Carbonite     Published Date: Oct 10, 2018
Overview Key Challenges Organizations still struggle with communication between data owners and those responsible for administering DLP systems, leading to technology-driven — rather than business-driven — implementations. Many clients who deploy enterprise DLP systems struggle to get out of the initial phases of discovering and monitoring data flows, never realizing the potential benefits of deeper data analytics or applying appropriate data protections. DLP as a technology has a reputation of being a high-maintenance control — incomplete deployments are common, tuning is a never-ending process, lack of organization buy-in is low, and calculations of ROI are complex.
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Carbonite
Published By: Spredfast     Published Date: Nov 15, 2018
Can chatbots provide a great customer experience? Watch how top brands automate social customer service practices. You'll learn how to enhance agent workflows and use AI to better connect with the people you care about most.
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social media customer support, social media manager, social media customer service, social customer service, media com customer service, social customer care, social media and customer service, customer service through social media, social media support, social media customer care, client management software, customer support software, social media management tools, social media monitoring, social media training, social media marketing companies, social media analytics, social media marketing, social media software, social media management software
    
Spredfast
Published By: IBM     Published Date: Feb 02, 2016
Energy firms should build and nurture a customer-centric culture delighting clients while maximizing operational and financial results. In doing so, we’ll highlight the crucial role analytics plays in helping energy firms ensure operational efficiency and customer satisfaction.
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ibm, energy, analytics, utility, customer experience, data, customer satisfaction
    
IBM
Published By: IBM     Published Date: Apr 20, 2016
Energy firms should build and nurture a customer-centric culture delighting clients while maximizing operational and financial results. In doing so, we’ll highlight the crucial role analytics plays in helping energy firms ensure operational efficiency and customer satisfaction.
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ibm, customer experience management, cem, energy, utilities, energy sector, aberdeen group
    
IBM
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
For many years, traditional businesses have had a systematic set of processes and practices for deploying, operating and disposing of tangible assets and some forms of intangible asset. Through significant growth in our inquiry discussions with clients, and in observing increased attention from industry regulators, Gartner now sees the recognition that information is an asset becoming increasingly pervasive. At the same time, CDOs and other data and analytics leaders must take into account both internally generated datasets and exogenous sources, such as data from partners, open data and content from data brokers and analytics marketplaces, as they come to terms with the ever-increasing quantity and complexity of information assets. This task is clearly impossible if the organization lacks a clear view of what data is available, how to access it, its fitness for purpose in the contexts in which it is needed, and who is responsible for it.
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Waterline Data & Research Partners
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
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Amazon Web Services
Published By: Infosys     Published Date: May 21, 2018
Experimenting faster is a trait shared by most innovative organizations. They want to experiment with new products and promotions to see if they can unearth bold new ways of serving the customer. But this experimentation cannot be random: it needs to be guided by data and based on current customer insight. It was access to this data that was the problem for our client, a large consumer brand. It took a long time to prepare the data to a point where it could be used by business managers. So long, in fact, that the data was no longer relevant; and the moment as often lost. The company needed to be able to experiment faster but was held back by a cumbersome and ineffective analytics infrastructure.
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experiment, organizations, customer, insights, analytics
    
Infosys
Published By: Infosys     Published Date: May 21, 2018
In HR, working purely on instinct is dangerous. HR Professionals are highly skilled, and their experienced opinion is extremely valuable when it comes to selecting candidates, assessing performance, and all the other important aspects of this function. But can you rely on their instinct alone? This was the big question that our client, a large CPG company was facing. When we realized this was the problem, the solution was obvious. Not necessarily easy, but obvious. There was plenty of data, but it wasn't being used to improve HR decision making. We designed an analytics solution that would improve HR Decision making. We designed an analytics solution that would improve the efficiency of data gathering, to make the HR function more effective. We then proposed an additional layer, which would use artificial intelligence (AI) to improve HR Decision-making further.
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company, employee
    
Infosys
Published By: Infosys     Published Date: Sep 11, 2018
Infosys has been recognized as a ‘Leader’ in NelsonHall’s Vendor Evaluation and Assessment (NEAT) report on big data and analytics services 2018.We have also been highly rated for our focus on automation. Our ability to meet future client requirements as well as deliver immediate benefits such as analytics, data management and support functions to our clients with a specific focus on process automation enabled us to secure this position.
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Infosys
Published By: Infosys     Published Date: Dec 03, 2018
Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next. Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h
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Infosys
Published By: IBM     Published Date: Nov 09, 2012
This research report looks at the client driven redesign of mainframe performance and availability monitoring. Clabby Analytics also got the opportunity to review IBM's new OMEGAMON V5 mainframe which has improved it's features.
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omegamon v 5.1, ibm, mainframe, analytics, it architecture, enterprise applications
    
IBM
Published By: MoreVisibility     Published Date: Dec 19, 2017
As the approach to strategic business decision making becomes more and more data driven, a method for consolidating our various data sets, which are often spread across multiple systems becomes exceedingly important. Two of the biggest players in data driven decision making are website analytics platforms and customer relationship management systems. The former includes accumulating data on top of the funnel behavior such as site traffic origins, lead generation, content consumption tracking, device usage, and overall site behavior. While the latter has a focus more on bottom of the funnel activity such as lead nurturing, customer status, lifetime value, etc. Lastly, without communication between these two essential platforms, a complete understanding of your customers, from lead to longtime client, may never be possible. A web analytics (Google Analytics) and CRM integration provides you with a 360 degree view of your customer base, so that you can understand not just what PPC efforts
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MoreVisibility
Published By: SAS     Published Date: Apr 25, 2017
Whether you call them customers, clients, patrons, guests or patients, customers are your organization’s most important asset. And that means customer loyalty should be among your top priorities. No matter when or where the customer journey begins – from websites and online chat to physical locations and call centers – customers expect you to provide a unique and personal experience. How can you use data and analytics to recognize your best customers across channels and know exactly where they are in their customer journey? Keep reading to find out.
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SAS
Published By: IBM     Published Date: Jan 09, 2015
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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big data, mdm, client analytics, real-time analysis, it management
    
IBM
Published By: IBM     Published Date: May 01, 2017
If you function like most IT organizations, you've spent the past few years relying on mobile device management (MDM), enterprise mobility management (EMM) and client management tools to get the most out of your enterprise endpoints while limiting the onset of threats you may encounter. In peeling back the onion, you'll find little difference between these conventional tools and strategies in comparison to those that Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs) have employed since the dawn of the modern computing era. Their use has simply become more: Time consuming, with IT trudging through mountains of endpoint data; Inefficient, with limited resources and limitless issues to sort through for opportunities and threats; and Costly, with point solution investments required to address gaps in OS support across available tools. Download this whitepaper to learn how to take advantage of the insights afforded by big data and analytics thereby usher i
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ibm, endpoint management, mobile device management, enterprise mobility, os support, it organizations
    
IBM
Published By: IBM     Published Date: Feb 14, 2014
Transforming the way enterprises work to better capitalize on our most valuable resource: people. As one of the world’s leading social businesses, IBM empowers more than 430,000 employees around the globe to know more, do more and deliver more value where and when it matters most. And by extending social capabilities outside the organization, IBM has been able to empower and strengthen connections with clients, IBM Business Partners, suppliers and other stakeholders to tap new opportunities for growth while building brand value.
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ibm, social business, marketing social media, innovation, collaboration, social workforce, client relations, analytics
    
IBM
Published By: IBM     Published Date: Apr 18, 2014
This IDC paper discusses the critical role of hardware infrastructure in business analytics deployments, citing best practices, the IDC's decision framework, and four client case studies - Wellpoint, Vestas, AXTEL, and Miami-Dade County. IDC's recommendation is that "infrastructure cannot — and should not — be an afterthought". Hardware infrastructure and software requirements must be determined in parallel to maximize the success of business analytics projects.
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ibm, business analytics, deployment, hardware, infrastructure, business analytics solutions, workload, server hardware
    
IBM
Published By: IBM     Published Date: Oct 07, 2014
This IDC paper discusses the critical role of hardware infrastructure in business analytics deployments, citing best practices, the IDC's decision framework, and four client case studies - Wellpoint, Vestas, AXTEL, and Miami-Dade County. IDC's recommendation is that "infrastructure cannot — and should not — be an afterthought". Hardware infrastructure and software requirements must be determined in parallel to maximize the success of business analytics projects.
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ibm, idc, hardware infrastructure, business analytics deployments, software, software requirements, business analytics projects, infrastructure management, it management
    
IBM
Published By: Sirius Computer Solutions, Inc.     Published Date: Jul 08, 2014
In today’s data-driven culture, tools for business analysis are quickly evolving. Clients need a solution to accelerate their business analytics and reporting capabilities while lowering OP-Ecosts associated with systems management and cost of ownership. Download to learn more!
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sirius computer solutions, ibm, systems solution, sap business suite, sap hana, data, system management, it management, enterprise applications
    
Sirius Computer Solutions, Inc.
Published By: SAS     Published Date: Aug 03, 2016
Whether you call them customers, clients, patrons, guests or patients, customers are your organization’s most important asset. And that means customer loyalty should be among your top priorities. No matter when or where the customer journey begins – from websites and online chat to physical locations and call centers – customers expect you to provide a unique and personal experience. How can you use data and analytics to recognize your best customers across channels and know exactly where they are in their customer journey? Keep reading to find out.
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best practices, business management, customer loyalty, technology, data, analytics
    
SAS
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