Monday November 15, 2010
All conference sessions take place in Edward 5-7
Registration, Coffee and Danish
Room: Albert Suites
Keynote
Five Ways Predictive Analytics Cuts Enterprise Risk
All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.
Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a "loss customer" such as a bad debtor or an insurance policy-holder with high claims.
In this keynote session, Dr. Eric Siegel will reveal:
- Five ways predictive analytics evolves your enterprise to reduce risk
- Hidden sources of risk across operational functions
- What every business should learn from insurance companies
- How advancements have reversed the very meaning of fraud
- Why "man + machine" teams are greater than the sum of their parts for enterprise decision support
Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World
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Platinum Sponsor Presentation
The Analytical Revolution
The algorithms at the heart of predictive analytics have been around for years - in some cases for decades. But now, as we see predictive analytics move to the mainstream and become a competitive necessity for organisations in all industries, the most crucial challenges are to ensure that results can be delivered to where they can make a direct impact on outcomes and business performance, and that the application of analytics can be scaled to the most demanding enterprise requirements.
This session will look at the obstacles to successfully applying analysis at the enterprise level, and how today's approaches and technologies can enable the true "industrialisation" of predictive analytics.
Speaker: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd
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Gold Sponsor Presentation
How Predictive Analytics is Driving Business Value
Organisations are increasingly relying on analytics to make key business decisions. Today, technology advances and the increasing need to realise competitive advantage in the market place are driving predictive analytics from the domain of marketers and tactical one-off exercises to the point where analytics are being embedded within core business processes.
During this session, Richard will share some of the focus areas where Deloitte is driving business transformation through predictive analytics, including Workforce, Brand Equity and Reputational Risk, Customer Insight and Network Analytics.
Speaker: Richard Fayers, Senior Manager, Deloitte Analytical Insight
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Break / Exhibits
Room: Albert Suites
10:45am-11:35am
Healthcare
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics
While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK.
Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc.
Speaker: Trish Mathe, Life Line Screening
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11:35am-12:25pm
Open Source Analytics; Healthcare
Case Study: A large health care organization
The Rise of Open Source Analytics: Lowering Costs While Improving Patient Care
Rapidminer and R were the number 1 and 2 in this years annual KDNuggets data mining tool usage poll, followed by Knime on place 4 and Weka on place 6. So what's going on here? Are these open source tools really that good or is their popularity strongly correlated with lower acquisition costs alone? This session answers these questions based on a real world case for a large health care organization and explains the risks & benefits of using open source technology. The final part of the session explains how these tools stack up against their traditional, proprietary counterparts.
Speaker: Jos van Dongen, Associate & Principal, DeltIQ Group
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Lunch / Exhibits
Room: Albert Suites
1:25pm-2:15pm
Keynote
Thought Leader:
Case Study: Yahoo! and other large on-line e-businesses
Search Marketing and Predictive Analytics:
SEM, SEO and On-line Marketing Case Studies
Search Engine Marketing is a $15B industry in the U.S. growing to double that number over the next 3 years. Worldwide the SEM market was over $50B in 2010. Not only is this a fast growing area of marketing, but it is one that has significant implications for brand and direct marketing and is undergoing rapid change with emerging channels such as mobile and social. What is unique about this area of marketing is a singularly heavy dependence on analytics:
- Large numbers of variables and options
- Real-time auctions/bids and a need to adjust strategies in real-time
- Difficult optimization problems on allocating spend across a huge number of keywords
- Fast-changing competitive terrain and heavy competition on the obvious channels
- Complicated interactions between various channels and a large choice of search keyword expansion possibilities
- Profitability and ROI analysis that are complex and often challenging
The size of the industry, its growing importance in marketing, its upcoming role in Mobile Advertising, and its uniquely heavy reliance on analytics makes it particularly interesting as an area for predictive analytics applications. In this session, not only will hear about some of the latest strategies and techniques to optimize search, you will hear case studies that illustrate the important role of analytics from industry practitioners.
Speaker: Usama Fayyad, , Ph.D., CEO, Open Insights
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Platinum Sponsor Presentation
Creating a Model Factory Using in-Database Analytics
With the ever-increasing number of analytical models required to make fact-based decisions, as well as increasing audit compliance regulations, it is more important than ever that these models can be created, monitored, retuned and deployed as quickly and automatically as possible. This paper, using a case study from a major financial organisation, will show how organisations can build a model factory efficiently using the latest SAS technology that utilizes the power of in-database processing.
Speaker: John Spooner, Analytics Specialist, SAS (UK)
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Session Break
Room: Albert Suites
Retail
Case Study: SABMiller
Predictive Analytics & Global Marketing Strategy
Over the last few years SABMiller plc, the second largest brewing company in the world operating in 70 countries, has been systematically segmenting its markets in different countries globally in order optimize their portfolio strategy & align it to their long term country specific growth strategy. This presentation talks about the overall methodology followed and the challenges that had to be overcome both from a technical as well as from a change management stand point in order to successfully implement a standard analytics approach to diverse markets and diverse business positions in a highly global setting.
The session explains how country specific growth strategies were converted to objective variables and consumption occasion segments were created that differentiated the market effectively by their growth potential. In addition to this the presentation will also provide a discussion on issues like:
- The dilemmas of static vs. dynamic solutions and standardization vs. adaptable solutions
- Challenges in acceptability, local capability development, overcoming implementation inertia, cost effectiveness, etc
- The role that business partners at SAB and analytics service partners at AbsolutData together play in providing impactful and actionable solutions
Speaker: Anne Stephens, SABMiller plc
Speaker: Titir Pal, AbsolutData
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Retail
Case Study: Overtoom Belgium
Increasing Marketing Relevance Through Personalized Targeting
Since many years, Overtoom Belgium - a leading B2B retailer and division of the French Manutan group - focuses on an extensive use of CRM. In this presentation, we demonstrate how Overtoom has integrated Predictive Analytics to optimize customer relationships. In this process, they employ analytics to develop answers to the key question: "which product should we offer to which customer via which channel". We show how Overtoom gained a 10% revenue increase by replacing the existing segmentation scheme with accurate predictive response models. Additionally, we illustrate how Overtoom succeeds to deliver more relevant communications by offering personalized promotional content to every single customer, and how these personalized offers positively impact Overtoom's conversion rates.
Speaker: Dr. Geert Verstraeten, Python Predictions
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Break / Exhibits
Room: Albert Suites
4:50pm-5:40pm
Uplift Modelling:
Case Study: Lloyds TSB General Insurance & US Bank
Uplift Modelling: You Should Not Only Measure But Model Incremental Response
Most marketing analysts understand that measuring the impact of a marketing campaign requires a valid control group so that uplift (incremental response) can be reported. However, it is much less widely understood that the targeting models used almost everywhere do not attempt to optimize that incremental measure. That requires an uplift model.
This session will explain why a switch to uplift modelling is needed, illustrate what can and does go wrong when they are not used and the hugely positive impact they can have when used effectively. It will also discuss a range of approaches to building and assessing uplift models, from simple basic adjustments to existing modelling processes through to full-blown uplift modelling.
The talk will use Lloyds TSB General Insurance & US Bank as a case study and also illustrate real-world results from other companies and sectors.
Speaker: Nicholas Radcliffe, Founder and Director, Stochastic Solutions
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Consumer services
Case Study: Canadian Automobile Association and other B2C examples
The Diminishing Marginal Returns of Variable Creation in Predictive Analytics Solutions
Variable Creation is the key to success in any predictive analytics exercise. Many different approaches are adopted during this process, yet there are diminishing marginal returns as the number of variables increase. Our organization conducted a case study on four existing clients to explore this so-called diminishing impact of variable creation on predictive analytics solutions. Existing predictive analytics solutions were built using our traditional variable creation process. Yet, presuming that we could exponentially increase the number of variables, we wanted to determine if this added significant benefit to the existing solution.
Speaker: Richard Boire, BoireFillerGroup
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Reception / Exhibits
Room: Albert Suites
Tuesday November 16, 2010
All conference sessions take place in Edward 5-7
Registration, Coffee and Danish
Room: Albert Suites
9:00am-9:55am
Keynote
Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others
The High ROI of Data Mining for Innovative Organizations
Data mining and advanced analytics can enhance your bottom line in three basic ways, by 1) streamlining a process, 2) eliminating the bad, or 3) highlighting the good. In rare situations, a fourth way - creating something new - is possible. But modern organizations are so effective at their core tasks that data mining usually results in an iterative, rather than transformative, improvement. Still, the impact can be dramatic.
Dr. Elder will share the story (problem, solution, and effect) of nine projects conducted over the last decade for some of America's most innovative agencies and corporations:
- Streamline:
- Cross-selling for HSBC
- Image recognition for Anheuser-Busch
- Biometric identification for Lumidigm (for Disney)
- Optimal decisioning for Peregrine Systems (now part of Hewlett-Packard)
- Quick decisions for the Social Security Administration
- Eliminate Bad:
- Tax fraud detection for the IRS
- Warranty Fraud detection for Hewlett-Packard
- Highlight Good:
- Sector trading for WestWind Foundation
- Drug efficacy discovery for Pharmacia & UpJohn (now Pfizer)
Moderator: Eric Siegel, Program Chair, Predictive Analytics World
Speaker: John Elder, Ph.D., Elder Research, Inc.
Also see Dr. Elder's full-day workshop
[ Top of this page ] [ Agenda overview ]
Break / Exhibits
Room: Albert Suites
10:30am-11:20am
Telecommunications
Case Study: Leading Telecommunications Operator
Predictive Analytics and Efficient Fact-based Marketing
The presentation describes what are the major topics and issues when you introduce predictive analytics and how to build a Fact-Based marketing environment. The introduced tools and methodologies proved to be highly efficient in terms of improving the overall direct marketing activity and customer contact operations for the involved companies. Generally, the introduced approaches have great potential for organizations with large customer bases like Mobile Operators, Internet Giants, Media Companies, or Retail Chains.
Main Introduced Solutions:-Automated Serial Production of Predictive Models for Campaign Targeting-Automated Campaign Measurements and Tracking Solutions-Precise Product Added Value Evaluation.
Speaker: Tamer Keshi, Ph.D., Long-term contractor, T-Mobile
Speaker: Beata Kovacs, International Head of CRM Solutions, Deutsche Telekom
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Session Changeover
11:25am-12:15pm
Thought Leader
Nine Laws of Data Mining
Data mining is the predictive core of predictive analytics, a business process that finds useful patterns in data through the use of business knowledge. The industry standard CRISP-DM methodology describes the process, but does not explain why the process takes the form that it does. I present nine "laws of data mining", useful maxims for data miners, with explanations that reveal the reasons behind the surface properties of the data mining process. The nine laws have implications for predictive analytics applications: how and why it works so well, which ambitions could succeed, and which must fail.
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Lunch / Exhibits
Room: Albert Suites
1:30pm-2:25pm
Expert Panel: Kaboom! Predictive Analytics Hits the Mainstream
Predictive analytics has taken off, across industry sectors and across applications in marketing, fraud detection, credit scoring and beyond. Where exactly are we in the process of crossing the chasm toward pervasive deployment, and how can we ensure progress keeps up the pace and stays on target?
This expert panel will address:
- How much of predictive analytics' potential has been fully realized?
- Where are the outstanding opportunities with greatest potential?
- What are the greatest challenges faced by the industry in achieving wide scale adoption?
- How are these challenges best overcome?
Panelist: John Elder, Ph.D., Elder Research, Inc.
Panelist: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd
Panelist: Udo Sglavo, Global Analytic Solutions Manager, SAS
Panel moderator: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World
Session Changeover
2:30pm-3:20pm
Crowdsourcing Data Mining
Case Study: University of Melbourne, Chessmetrics
Prediction Competitions: Far More Than Just a Bit of Fun
Data modelling competitions allow companies and researchers to post a problem and have it scrutinised by the world's best data scientists. There are an infinite number of techniques that can be applied to any modelling task but it is impossible to know at the outset which will be most effective. By exposing the problem to a wide audience, competitions are a cost effective way to reach the frontier of what is possible from a given dataset. The power of competitions is neatly illustrated by the results of a recent bioinformatics competition hosted by Kaggle. It required participants to pick markers in HIV's genetic sequence that coincide with changes in the severity of infection. Within a week and a half, the best entry had already outdone the best methods in the scientific literature. This presentation will cover how competitions typically work, some case studies and the types of business modelling challenges that the Kaggle platform can address.
Speaker: Anthony Goldbloom, Kaggle Pty Ltd
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Breaks /Exhibits
Room: Albert Suites
3:50pm-4:40pm
Human Resources; e-Commerce
Case Study: Naukri.com, Jeevansathi.com
Increasing Marketing ROI and Efficiency of Candidate-Search with Predictive Analytics
InfoEdge, India's largest and most profitable online firm with a bouquet of internet properties has been Google's biggest customer in India. Our team used predictive modeling to double our profits across multiple fronts. For Naukri.com, India's number 1 job portal, predictive models target jobseekers most relevant to the recruiter. Analytical insights provided a deeper understanding of recruiter behaviour and informed a redesign of this product's recruiter search functionality. This session will describe how we did it, and also reveal how Jeevansathi.com, India's 2nd-largest matrimony portal, targets the acquisition of consumers in the market for marriage.
[ Top of this page ] [ Agenda overview ]
Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World
[ Top of this page ] [ Agenda overview ]
Wednesday November 17, 2010
Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes
Click here for the detailed workshop description
- Workshop starts at 9:00am
- First AM Break from 10:00 - 10:15
- Second AM Break from 11:15 - 11:30
- Lunch from 12:30 - 1:15pm
- First PM Break: 2:00 - 2:15
- Second PM Break: 3:15 - 3:30
- Workshop ends at 4:30pm
Speaker: John Elder, Ph.D., CEO and Founder, Elder Research, Inc.
[ Agenda overview ]
