predictive analytics
TRAINING SEMINAR: Predictive Analytics
predictive analytics training seminar PROGRAM: Predictive Analytics for Business, Marketing and Web
  The official training program of  Predictive Analytics World
DATES: Note: There are no scheduled sessions at this time. However, the online version of this course is available on-demand at any time. For alternative in-person workshops, see Predictive Analytics World.
LOCATIONS: San Francisco, New York City
INSTRUCTOR: Eric Siegel, Ph.D., founding chair of Predictive Analytics World
and author of the book Predictive Analytics (copy included)

98% of attendees rated the instructor Excellent or Very Good (details).

What is predictive analytics?

Business metrics do a great job summarizing the past. But if you want to predict how customers will respond in the future, there is one place to turn — predictive analytics. By learning from your abundant historical data, predictive analytics provides something beyond standard business reports and sales forecasts: actionable predictions for each customer. These predictions encompass all channels, both online and off, foreseeing which customers will buy, click, respond, convert or cancel. If you predict it, you own it.

The customer predictions generated by predictive analytics deliver more relevant content to each customer, improving response rates, click rates, buying behavior, retention and overall profit. For online applications such as e-marketing and customer care recommendations, predictive analytics acts in real-time, dynamically selecting the ad, web content or cross-sell product each visitor is most likely to click on or respond to, according to that visitor's profile. This is AB selection, rather than just AB testing.

Predictive Analytics for Business, Marketing and Web is a concentrated training program instructed by the founding chair of Predictive Analytics World that includes interactive breakout sessions and a brief hands-on exercise. In two days we cover:

  • The techniques, tips and pointers you need in order to run a successful predictive analytics and data mining initiative
  • How to strategically position and tactically deploy predictive analytics and data mining at your company
  • How to bridge the prevalent gap between technical understanding and practical use
  • How a predictive model works, how it's created and how much revenue it generates
  • Several detailed case studies that demonstrate predictive analytics in action and make the concepts concrete
  • NEW TOPIC: Five Ways to Lower Costs with Predictive Analytics

No background in statistics or modeling is required. The only specific knowledge assumed for this training program is moderate experience with Microsoft Excel or equivalent.

Who this seminar is for:

Managers. Project leaders, directors, CXOs, vice presidents, investors and decision makers of any kind involved with analytics, direct marketing or online marketing activities.

Marketers. Personnel running or supporting direct marketing, response modeling, or online marketing who wish to improve response rates and increase campaign ROI for retention, upsell and cross-sell.

Technology experts. Analysts, data scientists, BI directors, developers, DBAs, data warehousers, web analysts, and consultants who wish to extend their expertise to predictive analytics.

In order to meet the unique training needs of business decision makers and analytics practitioners, this training program is:

  • Business-focused. Unlike other training programs that also cover scientific, engineering and medical applications of data mining and analytics, this seminar focuses squarely on solving business and marketing problems with these methods.
  • Comprehensive across business needs. Within this realm, however, we step beyond the standard application of response modeling for direct marketing to solve the wider range of business problems listed below.
  • Vendor-neutral and method-neutral. This training program, which is not run by an analytics software vendor, provides a balanced view across analytics tools and methods.

Topics covered:

  1. Solving business problems with predictive analytics

    Predictive analytics solves many business problems, offering solutions such as:

    • Increased customer retention by predicting defection
    • Increased online conversions and ad takes by predicting clicks
    • Increased sales and acquisition rates by predicting cross-sell opportunities
    • Personalized web and email content by predicting online response
    • Greater relevancy by predicting customer needs
    • Increased direct marketing response with response modeling
    • Decreased campaign spending by predicting non-responders
    • Increased fundraising profit by predicting donations
    • Higher-valued acquisitions by predicting customer lifetime value

    In other words, customer prediction drives business actions, which deliver business results. We cover case studies across this range of applications, with detailed examples running through both days of the training program.

  2. Creating predictive models

    Data is your most valuable asset. It represents the entire history of your organization and its interactions with customers. Predictive analytics taps this rich vein of experience, mining it to produce predictive models. Where multi-channel data is available, predictive analytics discovers interactions across customer touch points, such as key online behavior that may predict which customers will respond to direct mail.

    Whatever the application, the core methodology of predictive modeling is the same. We will uncover, in concrete terms, how modeling transforms your data into actionable customer predictions. To this end, we will see exactly what a model is, taking a look inside to see how it works and how it is created. Then we will:

    • Explore several example models in action
    • Turn the knobs that tweak and control modeling
    • Compare and contrast modeling methods intuitively, visualizing their differences so it all makes sense:
      • Decision trees
      • Business rules
      • Naive Bayes
      • Linear regression
      • Logistic regression
      • Neural networks
      • Other more recent advanced modeling techniques

    Live demo of predictive analytics software. Witnessing analytics software in action makes the ideas, concepts and methods covered by this training program concrete. The training agenda includes a detailed demonstration of CART (Salford Systems), a tool specialized for decision trees. Its friendly GUI-based capabilities make the predictive model transparent so we can drill down and really see the inner workings of specific examples. A second broader-use analytics tool is also demonstrated via a short pre-recorded video with the instructor.

    In addition to the products demonstrated, we will discuss the full spectrum of today's predictive analytics software, including free tools, cheap tools, and complete software suites.

  3. Measuring how well predictive models work

    Once you've got a predictive model, how do you know how good it is? We cover methods to evaluate models, which fall into two groups:

    Forecasting: How large a boost in revenue, sales or profit will the model produce?

    Accuracy: How well does it predict, how often is it correct, and how much better is it than standard segmentation such as RFM?

    Deploying a predictive model is playing a numbers game that puts the odds in your favor and improves the effectiveness of campaigns, operations and web behavior. We create profit curves, ROI calculations and bottom-line analyses and talk through exactly what they're telling us. And we prepare for performance gotchas that sneak up on you.

  4. Management and project leadership for predictive analytics

    Although predictive analytics is technical at its core, it must be run as a business activity in order to generate customer predictions that have a business impact. This requires a wholly collaborative process driven by business needs and marketing expertise. This ensures that customer predictions are actionable within your company's operational framework, and that they have the greatest impact within your company's business model.

    Referencing the industry standard data mining process model (called CRISP-DM), we break down the requirements of a predictive analytics business initiative. We explore this process, by which analysts and managers collaborate to strategically position predictive analytics, sustain universal buy-in and understanding, and avoid common roadblocks and unforeseen hazards.

Interactive breakout sessions

Like sky-diving and SCUBA diving, after a few hours of learning predictive analytics, it's a good time to dive right in. To this end, the training program includes breakout sessions, which are integrated with the conceptual flow of topics covered. You will join a small team and actively collaborate to design deployment strategies for predictive analytics. Working together to solve specific business problems, you will design strategic processes that avert organizational challenges, and you will design a broad technical approach, including the data discovery, data preparation and evaluatory metrics needed to direct a predictive analytics initiative.

These engaging breakout sessions are conducive to exercising the concepts you've learned, making them more intuitive and ingrained, and also provide an opportunity to learn from colleagues.

You will also "get your hands dirty" by digging through some data with a hands-on exercise during the second day. Optionally working with a buddy for this short exercise of about 20 minutes, you will bring a predictive model to life and see it improve before your eyes.

Course information and registration

Attendees receive the instructor's acclaimed book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a course materials book, and an official Prediction Impact certificate of completion at the conclusion of the Predictive Analytics for Business, Marketing and Web training program.

Predictive Pnalytics - the book       predictive analytics training book       predictive analytics certificate (Click to zoom)
Book by instructor     Course materials book         Certificate of completion

See training seminar registration for course venue information, registration, and the $100 early-bird discount.

Feel free to contact Prediction Impact with any questions about this training program.

Start learning right now

The following short, published articles, written by the instructor, are a great place to get started. Note that these articles are not required reading; the material therein will be covered during the training program.

Seven Reasons You Need Predictive Analytics Today
Predictive analytics has come of age as a core enterprise practice necessary to sustain competitive advantage. This definitive white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act.

Predictive Analytics with Data Mining: How It Works
Get a handle on the functional value of predictive analytics for marketing, sales and product direction. DM Review's DM Direct

Driven with Business Expertise, Analytics Produces Actionable Predictions
Run data mining as a business activity to generate customer predictions that will have a business impact. CRM Magazine's DestinationCRM.

Predictive Analytics' Killer App: Retaining New Customers
Predictively targeted discounts convert new customers who would otherwise never return to become loyal customers. DM Review's Extended Edition.

Sneak preview video. View the 13-minute video overview of our online training program, which is largely descriptive of this in-person training seminar as well.

About the instructor

Eric
SiegelEric Siegel, Ph.D., is a seasoned consultant in data mining and analytics, author of the notable book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, an acclaimed industry instructor, and an award-winning teacher of graduate-level courses in these areas. Eric served as a computer science professor at Columbia University, where he developed data mining technology in the realms of machine learning performance optimization, integrating historical databases, text mining, and data visualization. The founding conference chair of Predictive Analytics World and Text Analytics World, Eric has authored 11 peer-reviewed research publications and ran an MIT-hosted symposium on data mining. He also co-founded two New York City-based software companies for customer/user profiling and data mining. With data mining, Eric has solved problems in CRM analytics, computer security, fraud detection, text mining and information retrieval.

Eric has taught industry programs through Prediction Impact, The Modeling Agency and Salford Systems. In addition, he taught many semesters of university courses, including data mining-related graduate courses as well as introductory lecture series for non-technical audiences. Two of these courses have been in syndication through the Columbia University Video Network. Eric also published three peer-reviewed papers on computer science education.


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About the Training
Course topics
About the instructor                Sneak preview video - Watch
Online course
On-site training
Advanced workshops at PAW

customer analytics
Registration fees and venue

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Free Book for Attendeees

Attendees receive a copy of this book by the instructor:

PREDICTIVE ANALYTICS:
The Power to Predict Who Will Click, Buy, Lie, or Die

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Read this rich, entertaining primer by Predictive Analytics World founder Eric Siegel. More info

 
Participant Comments
"The best training seminar I have ever attended. I loved how the seminar was geared around theory and application rather than learning about an individual statistical mining tool."

     Ryan Williams
     Mgr Customer Analytics
     GSI Commerce

"An excellent overview on how to start using predictive analytics in any organization! In just two weeks I already have buy-in from upper management to explore ways to use predictive analytics to improve up-sells, cross sells and to determine what lifestyle imagery to display to our users. I'm super excited about these projects."

     Jennifer Boland
     Onsite Marketing Analyst
     Sierra Trading Post

"At Intuit we're already using data as an asset on the web, but this course makes it very concrete how we can take it to the next level."

     Jared Waxman
     Web Analytics Leader
     Intuit

"The best part of this training program is the clear correlation to practical applications in everyday business."

     Reto Matter
     VP Business Intelligence
     PlanetOut Inc.

"Eric is an A+++ instructor with a great sense of humor."

     Ali Maleki
     Project Manager
     Computer Tech. Consultants

"A very insightful and interesting seminar. I plan to put data mining and predictive analytics to work for us right away thanks to your ability to make this an approachable subject."

     Rob Ford
     Director Pricing
     Getty Images

"Making predictive analytics clear, simple and even entertaining is a tall order, but this seminar does just that! There's a mammoth load of material here, presented in understandable, actionable terms."

     Whitney Sales
     Senior Account Manager,      Business Solutions
     LoopNet, Inc.

"Eric reveals a roadmap to the use of predictive modeling in achieving business objectives, emphasizing the alignment of the resources critical to success. He balances a refreshing confidence in academic models with a practical regard for the inevitable fallibility of real-world data, and leads the way with a contagious sense of exploration and discovery. I learned a great deal in two days and had fun doing so."

     David Becker
     Business Analyst
     Pilgrim Insurance

Much more testimony

 
Prior Attendees
Adobe
ADP Dealer Services
Aida Direct (Colombia)
American Cancer Society
Amway
AOL
Apple
ARAMARK
Autodesk
Avnet
Bank of America
Bayer
Beliefnet.com
Blue Cross/Blue Shield
Blue Shield of CA
BNSF Railway
Britannica
Boeing
Cable & Wireless Panama
Cablevision
Capital Group
Cavalry Investments
Cisco
Citco Fund Services
ClickValue
Cobalt
Cogeco
Corporate Express
Compass Bank
Deckers
Dell
Dentsu
DermStore
Digital River
Disney
DoubleClick
Dow Jones
DPS Telecom
Duluth Trading
eLayaway
Electronic Arts
ESPN
ExactTarget
Export Development Canada
Express Scripts
Extrovertic
Fandango
Federal Express
Fidelity Canada
Fire Mountain Gems
FriendFinder
Fujo
Geico
Genentech
Getty Images
Globo.com (Brazil)
GSI Commerce
Harbor Freight Tools
Hewlett-Packard
HowStuffWorks.com
Hotwire
HSN
HUB International
Human Rights Campaign
IADB
IBM
IBM Canada
IEEE
IMS Health Canada
Innoviate (S. Africa)
Intel
Interwoven
Intuit
iTVX
Jo-Ann Stores
Johnson & Johnson
Johnson & Johnson Vision Care
JPMorgan
Jupiterimages
KnowledgeBase Marketing
Lennox Industries
Liberty Mutual
Logitech
LoopNet
Loyalty One - Air Miles
lynda.com
MEC Interaction
Merck
MetLife
Microsoft
MITRE
Monster.com
MRM Worldwide
MTV
MySpace
NASA
NBA
New York Times
Nickelodeon
Ontario Lottery
Ontario Teachers' Pension Plan
Orbitz
PA State Govt
Panasonic
Pacific Bell (now SBC)
Panalysis
Paychex
PayPal
Penn State
PETA
Petro-Canada
Pilgrim Insurance
PlanetOut
PPG Industries
PricewaterhouseCoopers
Primedia
PSEG
Qualcomm
QVC
Qwest
Raritan
Rasmussen College
Razorfish
Reliant Energy
Research in Motion
Rogers
Ruby Nuby
S&S CRM Partners
SAIC
SAS
Scandinavian Airlines
Sciele Pharma
Shopping.com
Sierra Trading Post
SimpleTuition
Spiceworks
Synovate Healthcare
T-Mobile
The Ladders
The Vitamin Shoppe
Teleflora
Tourism BC
Totsy
TransCanada Pipelines
Transcom
Troxell Communications
Unidos Financial
US Auto Parts
US Census Bureau
US State Department
USA Today
USDA
Verizon Wireless
The Vitamin Shoppe
VSP
Wells Fargo
Wells Fargo Contact Center
West Monroe Partners
Wirestone
World Vision
Wright Express
Yahoo!
 
... as well as many other non-profits, direct marketing shops and small-to-medium online businesses.
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