Knowledge Management is an umbrella term for making more efficient use of the human knowledge that exists within an organization. The major focus of knowledge management is to identify and gather content from documents, reports and other sources and to be able to search that content for meaningful relationships.
Read this Forrester report to learn how digital intelligence can help you combine insights from existing, new and emerging channels to drive timely, customer-obsessed decision-making. Get an up-close look at the disruptive nature of digital intelligence technology and find out how to continuously improve customer engagement.
Ordinary analytics tools can’t keep up with today’s digital, multichannel and demanding customers. This guide highlights three major challenges associated with traditional analytics and how innovative strategies combined with IBM’s Customer Experience Analytics solution can solve them.
"Increasingly, brands are looking to differentiate based on an exceptional customer experience. The key to improving the customer experience is being able to effectively measure what’s working and what you need to improve. IBM host a webinar presenting tips on how to measure the customer experience for your brand and how to use that data to build better journeys.
Please join IBM and guest speaker Andrew Hogan from Forrester Research as we share tips on how to best measure the digital experiences customers have with your brand and how to use that information to build better journeys.
The webinar will provide attendees with:
• Best practices to measure the quality of digital customer experiences
• Guidance on the kinds of tools to use to capture the right CX metrics
• Tips for integrating metrics, including the role of customer journeys
• Techniques to drive action and improve digital experiences"
- About the mandates that will significantly increase transaction complexity and transaction volumes for payers and providers
- How to reduce costs and improve processing efficiencies while also decreasing the risk associated with data movement
- Ways to improve customer service and ensure compliance with evolving regulations while reducing IT operating expenses
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.
This video demonstrates how IBM’s Behavior Based Customer Insight for Banking leverages predictive analytics to help you personalize customer engagement and deliver customized actions. The solution leverages advanced predictive models to analyze customer transactions and spending behavior to more deeply understand customer needs and propensities, anticipate life events, and help provide a unique customer experience.
Learn new ways of analyzing digitally connected customers-from dynamic segmentation to the use of advanced analytics. With predictive tools, banks can analyze transactions and spending behavior to better understand customer needs, anticipate life events, and provide a unique experience.
How do you keep 130,000 guests safely entertained, fed, watered and informed in a sustainable way? Roskilde Festival knew that the critical insights lay hidden in huge volumes of real-time data.
The Copenhagen Business School used IBM technologies to build a cloud big data lab that correlates information from multiple sources, delivering valuable insight for planning and running the festival.
Download to learn more.
Join IBM and partner Zementis in this webcast to hear how Predictive Model Markup Language (PMML), an industry standard, is helping solve business obstacles and enabling users to:
- Drive timely and relevant insights via in-line predictive analytics
- Score thousands of data records per second, scaling with business needs to enable instantaneous decisions
- Improve performance and cost efficiency by reducing or eliminating movement data off-platform to conduct analysis
As most companies now realize, analytics is increasingly more of an integral part of their day-to-day business operations. In a recent survey by a global research firm, 80% of CIOs stated that transition from backward-looking, passive analysis must shift to forward-looking predictive analytics. The challenge is that many analytic solutions are aligned to a specific platform, tied to inflexible programming models and requiring vast data movement. In this webcast, Forrester and experts from IBM will highlight how technology like Apache Spark on z/OS allows businesses to extract deep customer insight without the cost, latency and security risks of data movement throughout the enterprise.
Big Data, cloud, and mobility are changing the way we do business and bringing more opportunities to small and midsized businesses (SMBs) than ever before. To create competitive differentiation and take advantage of these opportunities, you need to close the gap between what your business demands and what your IT systems can deliver.
For small and midsize businesses, the realities of a dynamic marketplace and ever-changing customer expectations pose continual challenges and opportunities. Big Data, the cloud and mobility are changing the way information moves and connections are made across the organization, offering productive potential while promising competitive advantage. But adoption of these advanced technologies will require a transformation in the capacities, functions and methods of IT.
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
This paper from Osterman Research, explores the origins of the "information problem" many organizations are now facing and presents a detailed discussion of how to calculate your current information costs as well as how to calculate the ROI of an information governance program.
Read this Forrester whitepaper to learn more about the critical, yet often overlooked, role that data classification and data discovery can play in reducing your organization’s risk and enhancing security.
ENDPOINT DATA. It’s often one of the most forgotten aspects of an enterprise data protection strategy. Yet, content on laptops, desktops and mobile devices is among a company’s most valuable data even while it’s potentially at the greatest risk. According to IDC there will be some 1.3 billion mobile workers by 2015. However, only half of enterprises today are using some type of endpoint backup. That means that the volume of endpoint data that is in jeopardy is nothing short of significant.
Download to read the buyer's checklist on endpoint data protection!