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.
White Papers
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.
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.
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.
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.
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.
Success Stories
Mutual Fund Company Taps FundGUARD to Improve Sales Efficacy and Grow Assets
With more than 30 years of investment experience and more than $85 billion in assets under management (AUM), this leading mutual funds management company is no stranger to the unique and multi-faceted challenges of growing and retaining assets through a large and diversified financial advisors network. The company selected FundGUARD for its simplicity, versatility and quality. As a result, it has realized significant growth in AUM and improved sales productivity.
Capital Card Services Deploys Richer Portfolio Analytics and Strategy Development
Capital Card Services provides industry-leading servicing and portfolio management to meet the needs of credit card issuers across the United States to over 500,000 cardholder accounts. The company wanted to apply data analysis software and predictive analytics to its business model in order to meet its strategic objectives of improved efficiencies and productivity.
Sainsbury's Finance Selects Angoss for Superior Speed and Versatility
A savvy analytical software consumer, Sainsbury's Finance department understands the value of its customer data. The company has been active in leveraging this rich information source for customer acquisition, retention and cross-sell/upsell. With millions of customers in its database, the company required an analytics solution that was fast, flexible, user-friendly and capable of handling large volumes of data. After rigorously evaluating many software options, Sainsbury’s Finance selected KnowledgeSTUDIO for its superior quality in all categories.
Videos
Quick Tour of KnowledgeSTUDIO
NEW - Find out why over 500 leading organizations worldwide rely on Angoss predictive analytics to improve business performance.
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In-Database Analytics for Big Data
Learn how Angoss' In-Database Analytics module allows users to perform the complete end-to-end analytics cycle directly from within the data warehouse.
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Industry Leading Data Visualization
This presentation features enhancements to the Angoss Analytics Suite data visualization capabilities, which further improve productivity and usability making predictive analytics accessible and easy to use for technical and business users.
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Upcoming Events
Top Trends in Business Analytics
There is a shift toward business analysts as users and consumers of predictive analytics products and services — many organizations believe anyone with knowledge of the business should be able to make use of predictive techniques. Join the Webinar to learn drivers and benefits of predictive analytics for the business and use cases for sales and marketing analytics.
When: This webinar has already taken place. Please click the link in the right menu to view a webcast of the presentation.