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Program

Wednesday 10th November 2010
John Hancock Hotel & Conference Center
Boston, MA
USA
 
1. Realizing Tangible Benefits from Marketing & Advanced Analytics: 
Customer Success Stories
  • How did your company go about setting realistic goals and ROI metrics for marketing & advanced analytics?
  • Who was responsible within the organization and who participated in setting goals and/or metrics?
  • What organizational challenges need to be overcome or addressed?
  • Lessons learned?  What worked or didn’t work?
  • Tangible ROI achieved? 
Session Chair:
Hannah Smalltree
Editorial Director
TechTarget Inc.
 
Panelists:
Nauzar VimadalalManager of Marketing Operations, Staples
Jean-Paul IssonVice President, Global BI & Predictive Analytics, Monster
 

2. Adding Value through Advanced Marketing Analytics 
How marketing analytics can help drive customer loyalty and growth
  • Linking marketing analytics to overall marketing capabilities
  • Cross-selling and account penetration
  • Customer segmentation and lifecycle management
  • Pricing and profitability management, including price elasticity and price optimization
Speakers: 
Johnathan CopulskyCMO, Deloitte Consulting LLP
Charlie Veers, Manager, Deloitte Consulting LLP
 
3. Cross-Sell, Up-sell, and Influence: The Virtues of Affinity Analysis
  • Affinity Analysis: The different types and how they differ
  • Association Analysis and Sequence Analysis
  • Using Affinity Analysis to discover product affinities and purchase paths;
  • Alternative techniques for solving similar problems, e.g. collaborative filtering.
Speaker:
Dr Rex Davis
Director
dunnhumby
 

4. Show & Tell with Predictive Modeling:  “How Monster.com created Global Competitive Power with BI & Predictive Analytics”
  • Following Monster Worldwide BI  Evolution from good to great
  • Developing a BI vision and implementing it: Successful business intelligence implementation models
  • Making the right decisions at the right time and measuring ROI through a baby steps approach
  • Avoiding common change management challenges in sales, marketing, customer service, and products
  • Addressing business challenges with  BI solutions
  • Using predictive analytics as a business driver to stay on top of the competition
Jean-Paul Isson
Vice President, Global BI & Predictive Analytics
Monster
 
5. Exploiting Customer Data with Advanced Marketing Analytics
  • What are the gold nuggets in your data?
  • How do you extract those gold nuggests?
  • How data quality impacts analytics?
  • What is advanced analytics
  • Case studies in marketing analytics (retail, social media, trade promotions)
Alberto Roldan
Enterprise Analytics Practice - North America
Cognizant Technologies

6. Developing Analytical Solutions and Boosting Marketing Returns with External Data
  • Types of external data available to support B2C and B2B marketing
  • Analytical and marketing applications of external data – including online targeting
  • The landscape of data providers
  • Selecting the best external data source(s) for your needs – what to look for and what it will cost
Speaker:
John E. Young
Senior Vice President, Strategic & Analytic Consulting Group
Epsilon
 
7. Customer Segmentation: Who Achieved What, When and How?
  • Typical use cases for successful segmentation projects
    o Large multi-channel retailer trying to understand their customer base
    o Mid-market retailer trying to better tailor promotions
    o Large financial services company trying to improve predictive models
    o Large retailer trying to improve stocking decisions by store segmentation
  • Review of segmentation goals and challenges
  • Quick look at segmentation techniques
  • When segmentation is the wrong approach for a project
Speaker:
Steve Gallant
Director of Data Mining Services
KXEN
 
8. Web Analytics: Beyond the Hype
  • What Web Analytics can deliver and the approaches that are used
  • How Web Analytics relates to Marketing Analytics
  • How data used for Web Analytics differs from the sources used for offline Marketing Analytics
  • How Web Analytics should be integrated with analysis of customer behaviour offline?
  • Application in practice – 3 Case studies
Speaker:
David Hastings
Director, Advanced Business Analytics COE, Retail, Hospitality, Travel & Transportation
Teradata

Panel Session:
9. Advanced Marketing Analytics + Customer Intelligence = ROI: Lessons Learned in the Trenches
  • What actionable next steps should your organization consider based upon one of 4 levels of maturity:
    o Mature: we have customer intelligence processes, models, methodologies, best practices and enabling technologies in place and know how to exploit them.
    o Average: multiple non-integrated systems are utilized; ad hoc analytical processes, data integration and/or best practices in place, some third-party engagement on a project basis.
    o Limited: analytical tools are utilized within disparate organizational silos without integration, processes or best practices in place.
    o Nascent: finance or IT does all of our operational reporting and/or we use excel for everything
  • What pitfalls are commonly encountered, and how should they be avoided/overcome?
  • What are the organisational and cultural issues, and how should they be handled?
  • How should we justify the investment to get the budget approved?
Session chair:
Leslie Ament
VP Research & Client Advisory
Hypatia Research, LLC
 
3-4 panelists:
Amit BoobPractice Head – Analytics, Business Advisory Services, Retail, Consumer Goods, Transportation, Government SBU, Wipro Technologies
 
Jean-Paul IssonVice President, Global BI & Predictive Analytics, Monster
 
Marianne Slight, Vice President, Perioperative and Critical Care Solutions, Picis
 
10. Software Showcases
 
(i) Software showcase from Portrait Software:

Uplift models:
Do traditional modeling methods have you predicting the wrong thing and targeting the wrong customers?

Traditional models predict customers that are likely to buy given “business as usual”.  But targeting most-likely buyers means wasting money on customers who would buy anyway, rather than focusing on those who would be persuaded by your marketing message.  Uplift models solve the right business problem, predicting how much your marketing treatment will change each customer’s behavior.  In this session, you’ll learn how to:
  • Stop targeting individuals that will buy anyway, will never buy, or will react negatively to your marketing message
  • Focus on the “persuadables” to reduce campaign costs and simultaneously improve net campaign revenue
  • Apply best practice approaches for Uplift implemented by U.S. Bank and Lloyds TSB General Insurance 
Patrick Surry, PhD
Customer Analytics Solution Owner
Portrait Software
 
(ii) Software Showcase from KXEN
 

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