1. DMX GROUP Business Intelligence A Solution by DMX Group and Microsoft November 9, 2005 Jaime Charaf Vice President, Operations for Europe, Africa and the Middle East (Jaime@DMXGroup.com) Myrna Sabbagh Manager – Projects, DMX Group EMEA (Myrna@DMXGroup.com) Rawad Yazigi Senior System Engineer, DMX Group EMEA (Rawad@DMXGroup.com)

2. DMX GROUP Today’s Agenda Who is DMX Group? Why is a data strategy necessary? What is Business Intelligence? - DMX Group perspective –Data Mining deep-dive The most powerful tools combined with Excellence in Consultancy ( The DMX Group Mechanics ) DMX Group Solution - Specific BI and data mining modules Questions

3. DMX GROUP DMX Group Background Started as Venture Capital-funded company in March 2000. Headquartered in Bellevue, Washington $45 million in funding – Mayfield, Mohr Davidow, American Express, Deutsche Bank Grew to over 120 employees 35 patents in technology and processes Both technology and services

4. DMX GROUP DMX Group Background Beirut, Lebanon Office – May 15, 2005 –Fransabank Implementation Started –Significant expansion in Lebanon –Staff Amman, Jordan office –Opened November 2003 –Staff and offices –Regional product support center –Fully scaled data center

5. DMX GROUP Example Customers (1 of 2) Manufacturers (especially Auto) Financial Services/Publications Telecommunications

6. DMX GROUP Example Customers (2 of 2) Retailers Media & Portals Technology

7. DMX GROUP DMX Group Principals Dr. Usama Fayyad – World-renowned authority in data mining, one of founders of field, editor-in-Chief of technical journal, academic and business leader, authored 2 books and over 150 technical articles. NASA, Microsoft, and technology companies leadership roles Mr. Bassel Ojjeh – Expert in data warehousing, BI, and data operations, built some of largest DW in the world at Microsoft and DMX Group, built and shipped major products at Microsoft and Fox Software over 20 year career in DB, BI and IT. Mr. Jaime Charaf – 15 years experience as a large systems integrator with EDS. 5 plus years experience building IT outsourcing organizations. Expert in advanced engineering CAD/CAM and data management systems with General Motors at the General Motors Tech Center and at the Milford Proving Grounds.

8. DMX GROUP DMX Group & Microsoft Solution Internationally and locally based –.Net web services expertise Advanced and Advancing BI capabilities at little extra software costs –IT World’s leading company, dedicated to advancing BI tools Industries most efficient use of hardware Scales to largest BI projects in the world ( terabytes ) New generation data mining algorithms integrated into DMX Group Solutions Close partnership over the past 16 years

9. DMX GROUP DMX Group Mission Make enterprise data a working asset across the Institution: –Data strategy for the business –Implementation of BI and data mining capabilities –Enable companies to truly access data on an enterprise level –Illuminate business issues around data Look for the possibilities Expose data it to business users Train people and change processes –Integrate with existing operational systems

10. DMX GROUP The myths… Companies have built up large impressive data warehouses True data mining is pervasive across verticals Large companies know how to do it Off-the-shelf tools effectively discover valuable information at an enterprise-wide level

11. DMX GROUP The truths… Data is not organized or integrated, most data mining efforts end up not benefiting from existing data infra-structure Firms care a lot about data Firms are very concerned with understanding customer behavior An extremely small number of firms are successfully mining data Tailored BI and advanced mining solutions are always optimal

12. DMX GROUP Progress Who is DMX Group? Why is a data strategy necessary? What is Business Intelligence? - DMX Group perspective –Data Mining deep-dive The most powerful tools combined with Excellence in Consultancy ( The DMX Group Mechanics ) DMX Group Solution - Specific BI and data mining modules Questions

13. DMX GROUP Business data strategy How can your data influence your revenues? How do you optimize operations based on data? How do you increase customer retention based on data? How do you utilize enterprise data assets to spot new opportunities: –Cross-sell to existing customers –Grow new markets –Avoid problems such as fraud, abuse, churn, etc

14. DMX GROUP Why care about data strategy? Data is the primary enabler of fact-based decisions in all departments: –Marketing Identify long-term targets Determine optimal customer mix Attract, retain and maintain profitable relationships Target intelligent offers to specific customers –Product Management Support product design, pricing, packaging, and relationships Assist in future product and offer development and testing

15. DMX GROUP DMX Group Strategy Strategies, Solutions, and Technologies That Bring the Power of Business Intelligence to the Business Decision Maker. Business Users Marketers  PhDs,  Statisticians

16. DMX GROUP Progress Who is DMX Group? Why is a data strategy necessary? What is Business Intelligence? - DMX Group perspective –Data Mining deep-dive The most powerful tools combined with Excellence in Consultancy ( The DMX Group Mechanics ) DMX Group Solution - Specific BI and data mining modules Questions

17. DMX GROUP What is Data Warehousing? Much confusion exists about the following terms –Data Warehousing –Data Model –Business Intelligence –Data Mining –Artificial Intelligence –Executive Information Systems

18. DMX GROUP Data Warehouse - Summary Billing Roaming Mediation CDRs Customer Care Data Warehouse Customer Segments Business Intelligence Targeted Recommendations KYC SMS Prepaid Behavior Revenue Analysis Profitability

19. DMX GROUP Data Warehouse / Business Intelligence

20. DMX GROUP The Data Model –An Example

21. DMX GROUP What is Business Intelligence? Gartner, coined the term “business intelligence” during the 1990s. BI is the transformation of raw data companies collect from their various operations into usable information. BI software comprises specialized computer systems that allow an enterprise to easily aggregate, manipulate, and display data as actionable information

22. DMX GROUP What is Data Mining? Finding interesting structure in data Structure: refers to statistical patterns, predictive models, correlations or hidden relationships Interesting: is what is important to accomplishing the Enterprise’s goal – The Data Strategy!! Examples of data mining tasks –Predictive Modeling (classification, regression) –Segmentation (Data Clustering ) –Affinity (Summarization) This is relationships between fields, associations, and visualization

23. DMX GROUP Data Mining and Databases Many interesting analysis queries are difficult to state precisely Examples: –which records represent fraudulent transactions? –which households are likely to prefer one service or provider over another? –Who’s are the best credit risks in my customer DB? Yet database may contain the needed information –Good or bad customers, profitability –Did or did not respond to mailed survey...

24. DMX GROUP Specific database queries “Drill-through” reports OLAP Cubes Custom Reports Export to Excel Lists of Users Tracking Segments of Users Data Templates N one of these tell you anything beyond the answer to a well- formulated question NOT DATA MINING What is Data Mining?

25. DMX GROUP Data Mining Tasks Descriptive Analysis: to provide a concise and succinct summarization of a collection of data and distinguishes it from others. Association: to discover relationships or correlation among items in transactions. Prediction: to predict the value of a variable (the class) based on a set of training data based on values of measured variables.

26. DMX GROUP Data Mining Tasks Segmentation (Clustering): To identify clusters of data objects that are similar to one another. Time series analysis: To analyze large set of time series data to find certain regularities and interesting characteristics, including search for similar sequences or subsequences and mining sequential patterns, periodicities, trends and deviations.

27. DMX GROUP The Predictive Modeling Process Define the Problem Process the Data –Collect the Data –Clean the Data –Encode the Data –Transform the Data Run and Evaluate Experiment s –Try different learning algorithms –Try different models –Try different data processing Select Final Model Test Final Model Apply the Model

28. DMX GROUP X1 Class1 Class 2 X2 Classification To analyze a set of training data whose class label is known and to construct a model for each class based on the features in the data. Then to classify a given input into these categories (classes).

29. DMX GROUP Segment 3 Segment 2 Segment 1 Segmentation & Clustering X1 X2 To identify clusters embedded in the data, where a cluster is a collection of data objects that are similar to one another. Unlike classification, segmentation doesn’t associate categories to inputs. Instead, the division into groups is based solely on the geometrical structure of the input data.

30. DMX GROUP Association To discover relationships or correlation among a set of data. It’s a predictive modeling task whose goal is to reveal combinations of items or events that often occur together. Once identified these associations can be used to improve decision-making in a wide variety of applications.

31. DMX GROUP Progress Who is DMX Group? Why is a data strategy necessary? What is Business Intelligence? - DMX Group perspective –Data Mining deep-dive The most powerful tools combined with Excellence in Consultancy ( The DMX Group Mechanics ) DMX Group Solution - Specific BI and data mining modules Questions

32. DMX GROUP Database queries - SQL “Drill-Down” reports Data Base / OLAP –SQL Server 2005 Cubes Export to Excel * (Clear example) Lists of Users (Black Lists) Tracking Segments of Users Powerful Tools

33. DMX GROUP BI Solutions do not come in boxes BI Tools used to build your roof are not BI

34. DMX GROUP Implementation of BI – Service Model In-depth interviewing of Department Heads and End Users –Define the specific reporting capabilities needed –Allows Tailored Solution – Size as needed Locating data required by specific reports – The hunt Top down analysis of needed data –Granularity is not beneficial if not necessary –From “your questions” to the data warehouse not vice versa –Avoid the “Data Tomb” Cleaning data –Data that has never seen the light of day is always interesting! –Erroneous data extract reports are imperative E/T/L Custom reports Custom data mining algorithms

35. DMX GROUP Data Warehousing / Cubes / Data Marts Extraction and Loading Business Intelligence Data Mining Portals & Reports User Interface Data Integration Data Discovery and Data Transformation Level of Time and Effort E/T/L Communication ? Months A BI Implementation Two Months One Month Two Days

36. DMX GROUP A Brief History of BI - Yesterday In the beginning there was Artificial Intelligence ( Data Mining ) and all tools were built by data miners Scientists built and exclusively used the first BI/AI applications Think about this…the same scientist that wrote 10,000 lines of AI code was creating HTML and basic queries in order to get this information to end Users Data mining methods have their origins in a variety of fields: Statistics, Databases, Pattern Recognition, AI, Visualization, High-Performance Computing, and Information Retrieval. Successful deployment of these technologies to e-business enterprise data requires: data warehouse construction, mechanisms to efficiently update the warehouse, integration of data mining technologies, and delivery of results in a form consumable by business end-users. – Dr. Usama Fayyad, April 2000

37. DMX GROUP A Brief History of BI - Today Each year BI tools grow more powerful Today we are rolling out one of the most powerful BI tools yet created Today’s successful data warehousing implementations MUST combine –The most powerful BI and Data Mining tools –The most experienced implementation methodologies –And yet must reduce costs to BI customers

38. DMX GROUP A Brief History of BI – Tomorrow DMX Group’s R&D organizations are studying how to get out of the UI, E/T/L, and data base building business – SQL Server 2005 helps us… Mass produced tools significantly lower BI costs We are excited about Microsoft’s Investment in BI This allows DMX Group to focus on –Refined Implementation Methodology Tailoring to meet each customer’s specific needs –Patented Data Mining (AI) Algorithms –More Exact Behavioral Prediction and Segmentation models –Industry/Environmental Specific Data Models

39. DMX GROUP Interesting… Abraham Lincoln was elected to Congress in 1846. John F. Kennedy was elected to Congress in 1946. Abraham Lincoln was elected President in 1860. John F. Kennedy was elected President in 1960. Lincoln's secretary was named Kennedy. Kennedy's Secretary was named Lincoln. Andrew Johnson, who succeeded Lincoln, was born in 1808. Lyndon Johnson, who succeeded Kennedy, was born in 1908. John Wilkes Booth, who assassinated Lincoln, was born in 1839. Lee Harvey Oswald, who assassinated Kennedy, was born in 1939. Lincoln was shot at the theater named "Ford.“ Kennedy was shot in a car called "Lincoln" made by "Ford." Lincoln was shot in a theater and the assassin ran to a warehouse. Kennedy was shot from a warehouse and the assassin ran to a theater. Both Presidents were shot in the head. Both assassins were known by their three names. Both names are composed of fifteen letters. Booth and Oswald were assassinated before their trials. A week before Lincoln was shot, he was in Monroe, Maryland. A week before Kennedy was shot, he was with Marilyn Monroe.

40. DMX GROUP Progress Who is DMX Group? Data Strategy – A critical success factor Evolution of data management What is Business Intelligence? - DMX Group perspective –What data mining is… What data mining is NOT BTW: Why am I talking about services more than products? DMX Group Solution - Specific BI and data mining modules Questions

41. DMX GROUP How it Works ATM Data Trans - actions Product Customer Data Warehouse Customer Segments Analytics Targeted Recommendations Operational CRM Internet Banking SMS Banking Credit Cards Loans

42. DMX GROUP Advanced Mining Modules Available Customer Segmentation Cross-sell / Up-sell Churn Prediction Marketing Campaign Analysis Fraud Analysis (Due Diligence) Customer Life Time Value  Advanced Mining module available on top of Business Intelligence system

43. DMX GROUP BI and Advanced Modeling Modules Customer Loyalty Modeling and Prediction

44. DMX GROUP Client Analysis Customer Interaction Base 1 1 Sample Database Build Churn Model 2 2 3 3 High Risk Score Database 4 4 Assign Customer Value 5 5 Med Risk Low Risk High Val Med Val Low Val 6 6 6 6 High Val High Risk High Val Med Risk High Val Low Risk Med Val High Risk Med Val Med Risk Med Val Low Risk Low Val High Risk Low Val Med Risk Low Val Low Risk Risk Value Customer/Account Data

45. DMX GROUP LTV and Its Application A customer’s life-time value (LTV) is the net value that a customer brings in to a business by the end of their service. I.e. their profit contribution. LTV modeling allows for decisions to be made about individual customers that optimize return- on-investment (ROI). Examples: –Aggressive retention programs, such as account upgrade and Card renewal for high LTV. –Differentiated customer care treatment for reactivations/loyalty by customers with low LTV

46. DMX GROUP Cost Rules Applied… Cost Rules are introduced to define value For Example: –Deposit Value –Product mix –Average. daily balance –Monthly service fees –Technical operations/Support costs –Branch/teller usage –Late payment/Overdraft history –Interest rate –Contract term –Credit Score –Employment history/Income

47. DMX GROUP Sample Analytics Region 2 Region 1Region 3 Region 5 Region 6Region 4

48. DMX GROUP Map Segments to Actions High Low High Nurture / Maintain Aggressively Defend Cautiously Defend Grow Margin Change Bad Behavior Let them go Account Upsell Feature Add Card Renewal Save Program Elite Program Loyalty Programs Feature Use Migration Cost Reducing Programs Churn Probability Forecasted LTV Negative NSF, high-costs

49. DMX GROUP Sample Analytics Segment 1Segment 4 Segment 2 Segment 3Segment 5

50. DMX GROUP BI and Advanced Modeling Modules Customer Segmentation

51. DMX GROUP Customers Are Segmented Customer Segmentation Data Mining Engine (Clustering)

52. DMX GROUP The Challenges Marketers can’t manage online customer segments in the language of their own business With current solutions, marketers are forced to think in terms of DB Queries and complex data operations Out of the box solutions are not flexible enough to meet a variety of customers Marketing doesn’t have time to sift through the raw data and interpret complex customer interaction data

53. DMX GROUP The Answer - Customer Segment Manager Customer Segment Manager empowers Marketers to… Easily segment their customers in the language of their business Manage customer segments through targeted marketing campaigns Track most valuable customers over time

54. DMX GROUP Key Benefits Boosts revenues –Market to precisely segmented groups –Reach customers with campaigns tailored to their interests –Develop customers from low-value to high-value groups Reduces marketing costs  Rifle vs. shotgun approach eliminates wasteful marketing  Automated customer intelligence gathering Improves customer loyalty, retention, & satisfaction  Targeted, personalized offers to customers

55. DMX GROUP Sample Segment Imagine the following Customer Segment –Employed long term –Consistent monthly deposits –Age: 25 – 55 –No past delinquent payment issues –No outstanding mortgage loan –Similar Spouse Situation

56. DMX GROUP Resulting Marketing Campaign Marketing Campaign –Mortgage Loan Offer Increased Customer Profitability Increased Customer Satisfaction

57. DMX GROUP Wealth Market 1Wealth Market Upscale Retired 2Affluent Retired 3Comfortably Retired Upper Affluent 4High Asset Pre-Retired Investors 5High Asset Suburban Boomers 6High Asset Exurban Boomers 7Elite Pre-Retired Spenders 8Metro Elite Boomer 9Exurban Elite Boomers 10Young Savvy Elites Lower Affluent 11High Asset Affluent Climbers 12Established Empty Nesters 13Metro Achievers 14Greenbelt Achievers 15Affluent Beginnings 16Affluent Renters Mass Market 17High Asset Mass Market Savers 18Pre-Retired Metro America 19Urban Boomer Builders 20Sunbelt Traditionals 21Country Builders 22Up & Coming Young Climbers 23Urban Mass Market Owners 24Rural Mass Market Owners 25Urban Boomer Spenders 26Aspiring Young Spenders 27Midscale Metro Renters 28Midscale Rural Renters 29Striving Young Metros 30Lower-Middle Metro Owners 31Lower-Middle Exurban Owners 32Lower-Middle Town Blues 33Young Urban Renters 34Lower Boomer Renters Midscale Retired 35Suburban Senior Owners 36Conservative Retireds Lower Market 37Lower Market Owners 38Metro Downscale 39Rural Downscale 40Inner City Strugglers Downscale Retired 41Downscale Sunbelt Security 42Downscale Struggling Seniors Segmentation Examples

58. DMX GROUP Developing Valuable Customers Bought Recently Bought Three Months Ago Buy Occasionally Buy Frequently High Value Customer Low Value Customer Use targeted offers to move customers…

59. DMX GROUP Questions? emails: Jaime@DMXGroup.com Myrna@DMXGroup.com Rawad@DMXGroup.com