Archive for January, 2010

January 30th 2010

Predictive Analyics World Feb 16-17: What People Are Saying About It

Predictive Analytics World is Feb 16-17 in San Francisco. Here’s what people are saying about it.

“PAW was one-of-a-kind. Typically any type of thought leadership conference might be 90% generalized or theoretical sessions, whereas PAW was almost all strategic/tactical sessions. It is the only conference I have attended thus far that has challenged me to take my strategic and analytical thinking to the next level.”
Jared Vestal
Director of Marketing Analytics

“This is the Analytical Conference for real analysts and I’m planning to recommend it to my colleagues.”
Stephen Yu
VP Database Strategies
infoUSA National Account Division

“We left San Francisco with a long list of actionable items-can’t wait to see what’s on tap for next year!”
Michael C. Foroobar
Sr. Associate – Strategy, Reporting, and Analytics

Read more testimony

Read detailed blog entries about PAW

The sascom magazine blog interviewed me (Eric Siegel, PAW Conference Chair)
about trends in predictive analytics and the upcoming PAW, and I answered these questions:

  • What trends do you see in predictive analytics?
  • What are the top ways you see people dealing with the growing complexity of problems they need to solve?
  • How will the February Predictive Analytics World conference differ from previous conferences? Why should we attend?

Also, Michael Berry of Data Miners posted a blog interview with me (Eric Siegel, PAW Conference Chair), which gets a bit more personal and technical.

More information about Predictive Analytics World

A complete overview of the PAW conference agenda

Click here to register for PAW

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January 24th 2010

Bay Area SAS and R Users Groups at Predictive Analytics World, Feb 16-17

Predictive Analytics World, February 16-17 in San Francisco, will host two Bay Area Users Group meetings. Open admission: come to the exhibit, conference reception and a users group meeting for free.

Date: February 16

6:30pm:  Predictive Analytics World reception
7:30pm – 10:00pm:  SAS and R Users Group Meetings

The users group meetings are in parallel, at the same time.


1. Bay Area SAS Users Group Meeting – click for more information

Tonya Etchison Balan, Manager, Analytics Product Management, SAS Institute
Bharat Chitnavis, VP, Business Analytics Partners

2. useR Meeting (Bay Area R Users Group) – click for more information

Analytics pioneer John Chambers

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January 21st 2010

Predictive Analytics World’s Hot Trends: Agenda for Feb 16-17

Predictive Analytics World – coming Feb 16-17 to San Francisco – is bursting at the seams with compelling, detailed, revealing case studies from brand-named companies.

For a quick, meaty snapshot of PAW’s agenda, as well as a review of the hottest work going on in predictive analytics, check out my recent webinar:

Archived BetterManagement webcast: “Predictive Analytics: Hot Trends for 2010”

Available to view any time, on-demand: Click here to access the webcast now

Businesses around the globe have deployed analytics for the business impact it delivers.  Across many industries and departments, predictive analytics has been applied to address a vast range of business challenges.  What’s next?

Trend #1: Innovative applications
Trend #2: New data sources
Trend #3: New methodologies (e.g., uplift – see below)

Most of this webinar is spent on the first: innovative applications. Data-driven models predict new things such as the reliability of hardware and corporate processes alike, and drive all kinds of organizational decisions, for the likes of air traffic management, military operations, mobile consumer applications, and startup investment strategy.

Click here for more information and to view the webinar


One of Trend #3’s hottest tickets, uplift modeling (a.k.a., net lift modeling), will covered by this keynote address at February’s PAW:

“Response Modeling is the Wrong Modeling: Maximize Impact With Net Lift Modeling”

Keynote Speaker: Kim Larsen of Charles Schwab

The true effectiveness of a marketing campaign isn’t response rate! It’s the incremental impact – that is, additional revenue directly attributable to the campaign that would not otherwise have been generated. Yet traditional targeting criteria are often designed to find clients that are interested in the product, but would have bought it whether or not they received a promotion. In such cases, the incremental impact is insignificant and the marketing dollars could have been spent elsewhere.

Net Lift Models are designed to maximize incremental impact by targeting the undecided clients that can be motivated by marketing. These “swing customers” are akin to the swing states of a presidential election; data miners could learn a lot from presidential campaigns.

Click here for the complete keynote description

Click here for a complete overview of the conference agenda

Click for all other information about PAW

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January 17th 2010

PAW Keynote: Weigend on the New Data Economy

Predictive Analytics World, Feb 16-17 in San Francisco, is the only cross-vendor conference on the commercial deployment of predictive analytics, and delivers an unprecedented line-up of brand name case studies and speakers.

For example, check out this exciting, insightful keynote coming from Andreas Weigend:

Keynote – February 16, 2010, 1:30pm
Predictive Power Part II: Advanced Analytics in the New Data Economy

Speaker: Andreas S. Weigend, Ph.D., Former Chief Scientist,

Welcome to the New Data Economy, bringing new rules, reason and requirements to the commercial data miner. What’s new? The relentless focus on value for the consumer, corresponding new revenue models, and ubiquitous data collection capabilities are here to stay, delivering a whole new world of opportunity and challenge for the practitioner of advanced analytics.

Mobile. The mobile device delivers new power in its omnipresent capacity to collect behavioral data – including device use, sound (voice quality), and movement (geo-location) – and, in turn, to influence behavior. iPhone apps such as RedLaser are “killer,” putting the consumer first by letting the user scan barcodes and compare prices and alternatives on the go. Mobile application Boy Ahoy proves looks also can “kill,” combining online dating with geolocation so you can “predictively score” with the guy standing right next to you.

Explicit data collection. No enterprise is more consumer-centric than the social network, which first and foremost incents users to explicitly volunteer personal information, and goes from there to facilitate interactive behavior – such as virtual gifting. Explicit data empowers analysis beyond the implicitly-conveyed consumer data businesses traditionally track. Boundaries between the private and the public have disappeared or been re-negotiated: At the key of Facebook’s functionality is the distribution of “news” in mutually agreed “friendships.”

Virtual gifting. Revenue is generated from “thin air” – and new data is collected – with a new economy of intention amongst consumers such as Facebook users, who pay to communicate attention or demonstrate affection by buying virtual flowers and other such goodies composed of nothing more than pixels on the screen of the beloved and all of their and the gifter’s friends, thereby providing a quickly-escalating revenue model that competes with paid ads.

Virtual currency. Similarly, online gamers log on for free, but fork over real cash to buy weapons and armor. Such virtual currency provides an incentive for users to exhibit behavior that is good for the ecosystem.

Social data. Telecom – both mobile and otherwise – and social networks deliver a rich new data set that reveals what can be predicted from the behavior of one’s friends (see also the “Social Data” track of conference sessions, just 20 minutes after this keynote address).

Cross-vendor data. Social networks and travel option aggregators track consumer trends across vendor – Priceline is privy to more consumers’ behavior than any individual hotel chain or airline. These are the new consumer-centric data collectors.

In this keynote, learn from the former Chief Scientist of how to:

  • Position the deployment of predictive models within the New Data Economy so that new opportunities are leveraged, new value propositions are pursued, and the escalating requirements of commercial deployment are met.
  • Focus on the new data opportunities, not only the analytical methods, given the New Data delivered by consumer-centric business and technology, such as mobile, explicit, social and cross-vendor data.

Click here for more information about Predictive Analytics World

Click here for the complete conference agenda at-a-glance

Click here to register

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January 12th 2010

Predictive Analytics World, Feb 16-17 – Early Bird Ends Friday

Predictive Analytics World – Feb 16-17 in San Francisco – is rapidly approaching, and the Early Bird Price expires this Friday.

Case study highlights of PAW’s February program include:

Social Data:
* 1-800 Flowers:  Leveraging Social Media Data to Manage Fraud Risk
* Leading North American Telecom: The Social Effect: Predicting Telecom Customer Churn with Call Data

Uplift Modeling:
* Charles Schwab: Response Modeling is the Wrong Modeling: Maximize Impact With Net Lift Modeling

Innovative Applications:

* Eureka! Seven Innovative Applications of Predictive Analytics, Eric Siegel, Ph.D., Conference Chair
* Younoodle: The Mathematics of Innovation: Predicting Startup Success
* Visa: Building 10,000 Predictive Models: Scaling Health & Status Models to Large, Complex Systems
* Continental Airlines and PASSUR Aerospace: Predicting the Health of Air Traffic Systems
* U.S. Army, and a large commercial satellite company: Reliability Analytics: Predicting Equipment Failure

Cross-Sell & Recommendations:

* PayPal (eBay): Next Best Product Model: How to optimize on probability as well as profitability
* AT&T: Market Simulation in the Telecommunications Sector
* Sun Microsystems: Time-Purchasing Analytics and Next-Logical Predictions: Lessons from the High-Tech B2B World

…And much more.
For a program overview at-a-glance, see

And, on that program overview, be sure to note the R and SAS user group meetings the evening of Feb 16 – free, open admission.

On a related note, see my newly published article, “Six Ways to Lower Costs with Predictive Analytics,” at

Be sure to register by January 15 for the Early Bird rate (save $200):

For more information, see:

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