Predictive Analytics for Business and Marketing
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Predictive Analytics for Business and Marketing

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Predictive Analytics for Business and Marketing Predictive Analytics for Business and Marketing Presentation Transcript

  • © 2007 Prediction Impact, Inc. All rights reserved Predictive Analytics for Business, Marketing and Web Hosted by Prediction Impact, Inc. in association with the Emetrics Summit ________________________ Eric Siegel Ph.D. Prediction Impact, Inc. [email_address] (415)385-1313 Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Case Study: Direct Response
    • Company overview :
      • National veterans organization
      • Non-profit organization; fund raising
    • General Objectives
      • Find good donors
      • Recapture “lapsed” donors
      • Find “high dollar” donors
        • There is often an inverse correlation between likelihood to respond and dollar amount of gift.
      • Cost-effective fund raising—net revenue
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Problem-Solving Session Template
    • Overall strategy
      • Outline of initiative and its primary phases
    • Predictive modeling approach
      • Prediction statement/goal
      • Data required
        • Applicable segments
        • Predictors
      • Deployment: How the model will be integrated or otherwise made use of
      • Business case
    • Evaluation
      • KPIs (a la business goals)
      • Final AB test; control group
      • Baseline method for comparison
    • Challenges and bottlenecks anticipated
      • Organizational
      • Technical
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Problem-Solving Session #1: Retention
    • Business: Web-o-Rama House of Metrics (worhm.com)
    • Year: 2012
    • Type: B-2-B
    • Description: Web analytics services for small to medium businesses
    • Customer Breakdown:
      • 100k free subscribers
      • 30k premium subscribers
        • Credit card auto-bill monthly
        • High churn rate: 35% per year
    • Problem: Attrition rate has increased 20% since last quarter, while conversions have remained the same. Another team is working on increasing conversions.
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Summary of Killer Apps
    • Increased profit with response modeling for direct marketing
      • Increase response rate
      • Decreased spending
    • Increased customer retention by predicting defection
      • Retaining tenured customers
      • Converting first-time customer
    • Increased response with targeted content
      • Dynamic, behavior-based content selection
      • From AB selection to ABC...Z selection
    • Increased sales by predicting cross-sell opportunities
      • Recommendations engine
      • Collaborative filtering
    • Increased net worth by predicting customer lifetime value (LTV)
      • Higher valued acquisitions
      • Optimized retention targeting
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Jellybeans Brain Teaser
    • Good : red red red red red red red red red red red
    • Good : blue yellow green orange
    • Bad : black moive magenta beige turquoise fuisha
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved How a Crystal Ball Works Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Predict This!
    • Introduction
    • Data Overload
    • How Modeling Works
    • Statistical Models in Fashion
    • Modeling Methods
    • Deployment & Results
    • Conclusions
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Can Computers Think Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Next Steps for you
    • Moving towards a predictive analytics initiative
      • List your top 3 to 5 business optimization objectives
      • Match the list of killer apps to these objectives
      • Scope the data collections requirements
    • Other courses
      • The Modeling Agency's Level II and III Training
      • Tools courses, such as Salford Systems
      • These courses go beyond business apps to include science and engineering
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Recommended References Sources
    • Prediction Impact’s bi-annual email newsletter: Case studies, articles, events. Click “subscribe” at www.PredictionImpact.com .
    • www.KDnuggets.com : A comprehensive online reference and newsletter.
    • The UCI KDD Database Repository ( kdd.ics.uci.edu ): the most popular site for datasets used for research in machine learning and knowledge discovery. But all the core references such as this are found under KDnuggets, above.
    • The Cartoon Guide to Statistics , L. Gonick and W. Smith.
    • Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations , E. Frank and I.H. Witten.
    • Database marketing books for preliminary steps towards modeling, and for a more holistic, less technical marketing viewpoint:
      • Strategic Database Marketing, Arthur Hughes
      • See JimNovo.com for his “ Drilling Down ” book (first 9 chapters for free)
      • Email Marketing by the Numbers, Chris Baggott
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Predictive Analytics and Data Mining
    • Services:
      • Defining analytical goals & sourcing data
      • Developing predictive models
      • Designing and architecting solutions for model deployment
      • "Quick hit" proof-of-concept pilot projects
    • Training programs:
      • Public seminars: Two days, in San Francisco and other locations
      • On-site training options: Flexible, specialized
      • Instructor: Eric Siegel, Ph.D., President, 15 years of data mining, experienced consultant, award-winning Columbia professor
      • Training participants: Boeing, Corporate Express, Compass Bank, Hewlett-Packard, Liberty Mutual, Merck, MITRE, Monster.com, NASA, Qwest, SAS, U.S. Census Bureau, Yahoo!
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Predictive Analytics and Data Mining
    • Applications:
    • Response modeling for direct marketing
    • Product recommendations
    • Dynamic content, email and ad selection
    • Customer retention
    • Strategic segmentation
    • Security
      • Fraud discovery
      • Intrusion detection
      • Risk mitigation
      • Malicious user behavior identification
    • Cutting-edge research for groundbreaking data mining initiatives
    • Verticals:
    • Online business: Social networks, entertainment, retail, dating, job hunting
    • Telecommunications
    • Financial organizations
    • A fortune 100 technology company
    • Non-profits
    • High-tech startups
    • Direct marketing, catalogue retail
    Predictive Analytics for Business and Marketing
  • © 2007 Prediction Impact, Inc. All rights reserved Predictive Analytics and Data Mining
    • Team of several senior consultants:
    • Experts in predictive modeling for business and marketing
    • Relevant graduate-level degrees
    • Communication in business terms
    • Complementary analytical specialties and client verticals
    • Published in research journals and industrials
    • Extended network of many more:
    • Closely collaborating partner firms
    • East coast coverage
    Eric Siegel, Ph.D., President Prediction Impact, Inc. San Francisco, California [email_address] (415) 385-1313 For our bi-annual newsletter , click “subscribe” : www.PredictionImpact.com To receive notifications of training seminars: [email_address] Predictive Analytics for Business and Marketing