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Published By: Mintigo     Published Date: Sep 05, 2018
One of the most common use cases for AI in B2B is to make predictions about which accounts are most likely to buy and which leads are most likely to convert. However, use cases for AI are being extended beyond predictive account and lead scoring to include decision-making and process automation as well. Download this SiriusDecisions technology perspective on Predictive Analytics and Artificial Intelligence Technology to learn more. This paper will cover: • The benefits, evolution and capabilities of AI technology solutions for B2B organizations • The core and extended capability groups of AI • The business priorities supported by AI Fill out the form to get your free copy!
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Mintigo
Published By: Mintigo     Published Date: Sep 05, 2018
Artificial intelligence (AI) enables marketers using a predictive marketing platform to address many strategic questions. Whether you’re new to AI for Marketing or more seasoned with the use of AI, this ebook is a great resource for you. In this ebook, you’ll learn how to: • Optimize your marketing spending • Increase conversion rate across the funnel • Optimize customer engagement • Cross-sell and upsell throughout your customer base • Segment leads and grow customer value • Grow your market and find new prospects Fill out the form to get your free copy!
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Mintigo
Published By: IBM     Published Date: Sep 08, 2015
Please join us for an in-depth discussion of the latest data and analytics capabilities that banks are using today to uncover new customer insight - at the individual level - to improve offers and cross sell, optimize campaigns and deliver profitable revenue. The discussion will explore how leading banks are employing predictive analysis on customer data not often analyzed - like individual transactions, interactions, behavior and social media. See how banks can move beyond traditional segmentation and enable marketing to the "Segment of One."
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banking, finance, customer engagement, analytics, insights, segmentation, data management, personal finance, investing, small business
    
IBM
Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
The 21st century marks the rise of artificial intelligence (AI) and machine learning capabilities for mass consumption. A staggering surge of machine learning has been applied for myriad of uses — from self-driving cars to curing cancer. AI and machine learning have only recently entered the world of cybersecurity, but it’s occurring just in time. According to Gartner Research, the total market for all security will surpass $100B in 2019. Companies are looking to spend on innovation to secure against cyberthreats. As a result, more tech startups today tout AI to secure funding; and more established vendors now claim to embed machine learning in their products. Yet, the hype around AI and machine learning — what they are and how they work — has created confusion in the marketplace. How do you make sense of the claims? Can you test for yourself to know the truth? Cylance leads the cybersecurity world of AI. The company spearheaded an innovation revolution by replacing legacy antivirus software with predictive, preventative solutions and services that protect the endpoint — and the organization. Cylance stops zero-day threats and the most sophisticated known and unknown attacks. Read more in this analytical white paper.
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cylance, endpoint, protection, cyber, security
    
BlackBerry Cylance
Published By: BlackBerry Cylance     Published Date: Aug 22, 2018
Cylance engaged SE Labs to independently assess CylancePROTECT’s ability to predict and prevent previously unknown threats. SE Labs pitted the May 2015 version of CylancePROTECT® — without a cloud connection or updates — against some of the most destructive and disruptive threats that appeared between 2016 and 2018, after the model was trained and deployed.
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predictive, advantage, cylance, protect, cloud, connect
    
BlackBerry Cylance
Published By: SAS     Published Date: Mar 06, 2018
Tax fraud is already prevalent, and fraudsters are more sophisticated and automated than ever. To get ahead of the game in detecting fraud and protecting revenue, tax agencies need to leverage more advanced and predictive analytics. Legacy processes, systems, and attitudes need not stand in the way. To explore the challenges, opportunities, and value of tax fraud analytics, IIA spoke with Deborah Pianko, a Government Fraud Solutions Architect within the SAS Security Intelligence practice.
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SAS
Published By: SPSS Inc.     Published Date: Mar 31, 2009
This paper briefly defines text analytics, describes various approaches to text analytics, and then focuses on the natural language processing techniques used by text analytics solutions.
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spss, text analytics, data management, statistical analysis, natural language processing techniques, computational linguistics, web sites, blogs, wikis, e-mails, instant messaging, predictive analytics, bottom up approach, documents, customer relationship management, crm, voice of the customer, competitive landscape, security threats, understanding text
    
SPSS Inc.
Published By: SAS     Published Date: Apr 13, 2011
This paper will outline the value and methods involved in data mining across both quantitative and qualitative data. In addition, it will describe the data transformations necessary before doing such work, and the tools that are particularly valuable for mining mixed data types.
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business intelligence, michael lock, predictive analytics, business insight, business visibility, small to medium sized business, data mining, data quality
    
SAS
Published By: SAS     Published Date: Mar 01, 2012
Learn what criteria distinguished certain companies as top performers within the SMB sector, the factors to consider when assessing your organization's BI competency and the required actions to achieve best-in-class performance.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management, business intelligence, michael lock, predictive analytics, business insight, business visibility
    
SAS
Published By: SAS     Published Date: Mar 01, 2012
This paper defines predictive analytics, then details ways this type of analytics can be applied to marketing, risk, operations and more. It also includes information relevant to a wide variety of industries - from manufacturing to hospitals.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management, business activity monitoring, business integration, business management, business metrics, business process automation
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
The solution to operationalizing analytic s involves the effective combination of a Decision Management approach with a robust, modern analytic technology platform. This paper discusses both how to use a focus on decisions to ensure the right problem gets solved and what such an analytic technology platform looks like.
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sas, predictive analytics, technology platform, solution, operationalizing, production systems, best practices, business analytics, analytical applications, data quality
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This paper will discuss the barriers to data-driven decision making for midsized businesses, and how experts and non-experts alike can use SAS Visual Analytics to unlock the value of data – including big data – to increase revenue, cut operational costs and better manage their business.
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sas, bottom line, midsized businesses, leveraging data, data management, internal and external, decision making, big data, operational costs, decision support, operational execution, strategic analysis, predictive analytics, data landscape, real-time data, interactivity, data democracy, visual analytics, best practices, business intelligence
    
SAS
Published By: TeamQuest     Published Date: Dec 19, 2014
Businesses are constantly putting pressure on price, performance and reliability of IT services and infrastructure. Recent adoption of technologies such as virtualization, dynamic computing and various forms of cloud computing coupled with changing management paradigms has raised the stakes even more. This ruthless drive for efficiency calls for the use of more sophisticated optimization methods. It is safe to say that if you don’t, chances are you will be “done” by others who do.
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infrastructure, virtualization, optimization, guide, descriptive, diagnostic, predictive, prescriptive, analysis, efficiency, risk, white, paper, it management, knowledge management, data management, data center
    
TeamQuest
Published By: Intel Security     Published Date: Apr 06, 2016
Spend less on prevention; invest in detection, response and predictive capabilities.
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security architect, information, continuous response, incident, monitoring, remediation, adaptive architecture, protection, advanced threats, prevention, detection
    
Intel Security
Published By: IBM     Published Date: Nov 14, 2014
A recent study completed by Ventana Research found that 68% of companies are using predictive analytics to gain a competitive edge. Find out more now, and learn how predictive analytics can help you.
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ibm, ventana, deployment, predictive analytics, forecasting, accessing data, business management, data management, business analytics, productivity
    
IBM
Published By: IBM     Published Date: Nov 14, 2014
IBM SPSS Modeler is a powerful, versatile data and text analytics workbench. Learn how you can build accurate predictive models quickly and intuitively, without programming. So you can use data to understand the current state of your organization and get a view into the future.
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ibm, webinar, business intelligence, entity analytics, modeler, automated modeling, predictive intelligence, building models, spss modeler gold, data management, change management
    
IBM
Published By: IBM     Published Date: Nov 14, 2014
Data mining uncovers patterns in data through a variety of predictive techniques. By engaging in data mining, organizations like yours gain greater insight into external conditions, internal processes, your markets – and your customers.
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ibm, data mining, data management, business results, predictive intelligence, business insights, best practices, business intelligence, return on investment
    
IBM
Published By: IBM     Published Date: Feb 04, 2015
Driving the right interaction at the right time. This paper examines the need to uncover and understand the dynamic roles and changing needs of individuals, the importance of synchronizing interactions with these changing needs, and how predictive analytics can drive customer intimacy by facilitating 1:1 interactions.
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predictive analytics, customer interaction, crm, business analytics, marketing attributes
    
IBM
Published By: IBM     Published Date: Feb 05, 2015
Using IBM SPSS Modeler to develop predictive models for crime prevention, the City of Lancaster saw a crime rate reduction of over 35 percent.
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roi, predictive models, crime rate reduction, spss modeler, predictive analytics
    
IBM
Published By: IBM     Published Date: May 20, 2015
Today’s customers are well-informed and empowered by information. They use other people and online experts as information sources. They interact with companies by multiple methods and expect a relevant dialogue with each brand. This paper introduces the IBM Predictive Customer Intelligence solution, which is designed to help your company create personalized, relevant experiences for individual customers with a focus on driving new revenue. Along with explaining the architecture of the solution, this paper covers how the solution works.
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ibm, software, business analytics, database, database development, quality assurance, analytical applications, business intelligence, data quality, productivity, project management
    
IBM
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