Market Basket Analysis is a data modeling technique which leverages large amounts of customer transaction data to find associations between items or events by determining the likelihood for them to occur together. Market Basket Analysis results in a better understanding of your customers and their buying behavior, allowing you to predict the likelihood of a future customer response based on associations, and ultimately tailor your marketing and sales strategies and operations for improved performance. Market Basket Analysis is applicable in many industries and across use cases, many of which this whitepaper will illustrate and define.
Emerging Uses of Predictive Analytics for Insurers
Leading insurers are beginning to employ predictive analytics to gain a competitive edge in the current market environment. Although predictive analytics has been traditionally applied in catastrophe and fraud related assessment, predictive analytics is now finding applications and use for insurers in the areas of sales and risk analytics. This white paper describes several of the emerging uses of predictive analytics in the insurance industry. Insurers who are adopting advanced analytics in their business processes are improving business performance by maximizing customer lifetime value, optimizing revenue retention/growth, and preserving revenue by mitigating losses. Read more about solutions for renewals management, channel sales management and claims fraud abuse and deterrence solutions.
Predictive Strategy Scenarios for Marketing, Sales and Risk
How and where can you apply predictive strategies in your business? The use of data mining and predictive analytics by organizations continues to grow as businesses attempt to tap into their customer and enterprise data to improve business decisions including those related to strategy – when, where and how to play to win. Usage of predictive models as an integral part of optimized, automated decisions is becoming more prevalent in all areas of business. StrategyBUILDER with its Strategy Trees, provides business analysts the ability to design and deploy predictive strategies for better business decisioning. This white paper describes several illustrative scenarios and some common uses of predictive analytics to improve business decisions including those related to strategy. Scenarios include marketing campaign development, sales productivity, credit line application, and fraud mitigation.
How to Optimize Your Data Mining Environment
Data mining is the process of applying business intelligence software tools to business data in order to create predictive models. Organizations are able to better understand and continuously optimize key business drivers to improve performance through this process of relationship identification and pattern detection.To meet these requirements, Angoss provides organizations with a set of data mining and predictive analytics software tools that are easy to use, robust in functionality and seamlessly integrate with your existing processes, technology platforms and enterprise business analytics and decision management systems.
Key Performance Indicators, Six Sigma and Data Mining
KPIs, Six Sigma and Data Mining management systems, methodologies and tools are all closely related. An understanding of these relationships helps organizations accelerate productivity gains in their operations to improve profitability. This white paper summarizes these relationships and illustrates how these business value benefits are achieved. It provides a framework for discussion of how KPIs are made relevant and actionable within organizations; how Six Sigma process optimization initiatives linked to KPIs enable improved "data driven decision-making"; and how data mining processes support the variability in experience between performance achievements and target performance goals.
How to Credit Score with Predictive Analytics
Best practices in the financial services industry for consumer lending, notably in the areas of credit card and personal unsecured financial products, have moved toward the use of proprietary credit scores and strategies created using data mining and predictive analytics. This paper discusses market and regulatory drivers that are increasing the usage of data mining and predictive analytics as an integral component of credit lifecycle management.
Creating Scorecards with KnowledgeSTUDIO
Scorecards are used primarily by retail banking and credit card issuers to support consumer lending and related credit application decisions. The use of scorecards is also becoming more common in other lending areas (small and mid-market business lending) and other business domains (telecommunications and other industries where products or services are provided on credit).Increasingly, lenders are creating their own proprietary scorecards using their own data, analytics competencies and technologies to create strategic competitive advantage and to optimize portfolio performance. This paper examines how scorecards are treated in KnowledgeSTUDIO® as a type of predictive model that associates values with a set of characteristics that can be summed to produce a score.
Grow Revenues and Reduce Risk With Analytics Software
Gaining knowledge through data selection, data exploration, model creation and predictive action is the key to increasing revenues, reducing costs and minimizing risk. Today’s organizations and analysts require a suite of data mining and predictive analytics tools that are robust in functionality, easy to use and implement, affordable, and integrated with current processes and technology. Angoss answers these requirements with a suite of software tools to discover the patterns and characteristics within this data, predict what might happen and then act on the results.
Creating and Deploying Predictive Strategies in Marketing, Sales and Risk
Angoss helps businesses achieve significant revenue growth and measurable Return on Investment (ROI) with systematic productivity improvements to their marketing, sales and risk operations. Angoss does this by helping our customers create predictive models that uncover new insights and understanding about their customers. This knowledge is then embedded into the business rules that govern marketing, sales and risk management activities. The ability to create actionable, targeted predictive strategies improves marketing effectiveness, sales performance and risk mitigation.
Building Better Segmentation and Targeting Strategies
Data mining and predictive analytics are now perceived as advanced technologies. Predictive analytics is an area of business intelligence that is just beginning to be tapped for its business value. International Data Corporation has stated, “Predictive analytics solutions generate an average return of 145%.” With potential returns like this on the horizon, many organizations are embracing predictive analytics in order to accelerate business performance for competitive advantage.
Overcoming Customer Relationship Management Data Deluge
Good leads go stale very quickly. Without prompt action, their likelihood to convert declines with resulting impact to sales productivity and return on marketing investment. As challenging as the data deluge may seem, these environments are some of the richest for predictive sales analytics solutions.
Optimizing B2B Demand Generation by Adding Predictive Analytics
Predictive leads are data mining-driven insights into customer and prospect behaviors—as well as those of your sales team—that most impact sales success. They can be used to drive continuous improvement in sales performance, commissions and revenues. By using data mining on their own sales data, sales organizations can discover the key predictors of best leads and sales closes, predict which leads will convert to opportunities and closed sales and act on this information to align their marketing, demand generation and sales force activities with actionable business insights.
Predictive Analytics for Telecom Service Providers
Angoss technology helps telecom providers to better assess, manage and monitor sales performance for mid-market business clients throughout their customer lifecycle. With a comprehensive platform to develop and monitor prospecting and customer models, scores and strategies, telcos are able to improve performance. This white paper explains how Angoss software and solutions can be used to accelerate business process automation and monitor results for statisticians and business analysts alike.
Mutual Funds Predictive Sales Leads and Redemption Control System
Mutual fund distributors face an increasing number of competitive pressures to their share of wallet. These pressures arise not only from competitors with similar products and channels but also from bank-owned funds that can target customers through existing relationships. This paper explores how predictive analytics leverage an organization’s business knowledge by applying sophisticated data analysis techniques to enterprise data. As a result, mutual fund companies are able to build optimal strategies for customer acquisition and retention, upsell and cross-sell, fraud detection and performance improvement.
Business Analytics Powered by Market Basket Analysis
Market Basket Analysis is a data modeling technique which leverages large amounts of customer transaction data to find associations between items or events by determining the likelihood for them to occur together. Market Basket Analysis results in a better understanding of your customers and their buying behavior, allowing you to predict the likelihood of a future customer response based on associations, and ultimately tailor your marketing and sales strategies and operations for improved performance. Market Basket Analysis is applicable in many industries and across use cases, many of which this whitepaper will illustrate and define.
Emerging Uses of Predictive Analytics for Insurers
Leading insurers are beginning to employ predictive analytics to gain a competitive edge in the current market environment. Although predictive analytics has been traditionally applied in catastrophe and fraud related assessment, predictive analytics is now finding applications and use for insurers in the areas of sales and risk analytics. This white paper describes several of the emerging uses of predictive analytics in the insurance industry. Insurers who are adopting advanced analytics in their business processes are improving business performance by maximizing customer lifetime value, optimizing revenue retention/growth, and preserving revenue by mitigating losses. Read more about solutions for renewals management, channel sales management and claims fraud abuse and deterrence solutions.
Predictive Strategy Scenarios for Marketing, Sales and Risk
How and where can you apply predictive strategies in your business? The use of data mining and predictive analytics by organizations continues to grow as businesses attempt to tap into their customer and enterprise data to improve business decisions including those related to strategy – when, where and how to play to win. Usage of predictive models as an integral part of optimized, automated decisions is becoming more prevalent in all areas of business. StrategyBUILDER with its Strategy Trees, provides business analysts the ability to design and deploy predictive strategies for better business decisioning. This white paper describes several illustrative scenarios and some common uses of predictive analytics to improve business decisions including those related to strategy. Scenarios include marketing campaign development, sales productivity, credit line application, and fraud mitigation.
How to Optimize Your Data Mining Environment
Data mining is the process of applying business intelligence software tools to business data in order to create predictive models. Organizations are able to better understand and continuously optimize key business drivers to improve performance through this process of relationship identification and pattern detection.To meet these requirements, Angoss provides organizations with a set of data mining and predictive analytics software tools that are easy to use, robust in functionality and seamlessly integrate with your existing processes, technology platforms and enterprise business analytics and decision management systems.
Key Performance Indicators, Six Sigma and Data Mining
KPIs, Six Sigma and Data Mining management systems, methodologies and tools are all closely related. An understanding of these relationships helps organizations accelerate productivity gains in their operations to improve profitability. This white paper summarizes these relationships and illustrates how these business value benefits are achieved. It provides a framework for discussion of how KPIs are made relevant and actionable within organizations; how Six Sigma process optimization initiatives linked to KPIs enable improved “data driven decision-making”; and how data mining processes support the variability in experience between performance achievements and target performance goals.
Creating Scorecards with KnowledgeSTUDIO
Scorecards are used primarily by retail banking and credit card issuers to support consumer lending and related credit application decisions. The use of scorecards is also becoming more common in other lending areas (small and mid-market business lending) and other business domains (telecommunications and other industries where products or services are provided on credit).Increasingly, lenders are creating their own proprietary scorecards using their own data, analytics competencies and technologies to create strategic competitive advantage and to optimize portfolio performance. This paper examines how scorecards are treated in KnowledgeSTUDIO® as a type of predictive model that associates values with a set of characteristics that can be summed to produce a score.
Grow Revenues and Reduce Risk With Analytics Software
Gaining knowledge through data selection, data exploration, model creation and predictive action is the key to increasing revenues, reducing costs and minimizing risk. Today’s organizations and analysts require a suite of data mining and predictive analytics tools that are robust in functionality, easy to use and implement, affordable, and integrated with current processes and technology. Angoss answers these requirements with a suite of software tools to discover the patterns and characteristics within this data, predict what might happen and then act on the results.
Creating and Deploying Predictive Strategies in Marketing, Sales and Risk
Angoss helps businesses achieve significant revenue growth and measurable Return on Investment (ROI) with systematic productivity improvements to their marketing, sales and risk operations. Angoss does this by helping our customers create predictive models that uncover new insights and understanding about their customers. This knowledge is then embedded into the business rules that govern marketing, sales and risk management activities. The ability to create actionable, targeted predictive strategies improves marketing effectiveness, sales performance and risk mitigation.
Building Better Segmentation and Targeting Strategies
Data mining and predictive analytics are now perceived as advanced technologies. Predictive analytics is an area of business intelligence that is just beginning to be tapped for its business value. International Data Corporation has stated, “Predictive analytics solutions generate an average return of 145%.” With potential returns like this on the horizon, many organizations are embracing predictive analytics in order to accelerate business performance for competitive advantage.
Overcoming Customer Relationship Management Data Deluge
Good leads go stale very quickly. Without prompt action, their likelihood to convert declines with resulting impact to sales productivity and return on marketing investment. As challenging as the data deluge may seem, these environments are some of the richest for predictive sales analytics solutions.
On-Demand Analytics Solutions
Under pressure to advance corporate objectives to increase revenues and market share, business leaders demand insights into how customers and prospects are most likely to transact with them in the near and long term. With a combination of innovative data analytics software, robust deployment capabilities and industry expertise, Angoss is uniquely qualified as an ideal analytics partner. Angoss provides an exclusive focus on fully automated deployments of predictive analytics solutions for sales, marketing and risk. Learn how customers are realizing high Return on Investment (ROI) and exceptional value from Angoss’ proven software-as-a-service (SaaS) delivery model.