1. Metodi Quantitativi per Economia, Finanza e Management Lezione n°2

2. Management & Quantitative Methods

3. 112 Keywords 57 Data Analysis & Quantitative Methods

4. Gartner's (*) Top Three Predictions for 2009-2010 IT Cut Costs. Inside of traditional Information Technology we're going to find a lot of new ways to quickly cut costs. …. High-Scale BI. Business Intelligence (BI) will require a move up scale to larger sets of data, larger sets of content, and more mingling or joining of disparate types of data and content in order to draw inferences about what the customers are willing to do and pay across both B2B and B2C activities. Social Data-CRM Mash-ups. The role of social media and networks will continue to grow and be impactful for enterprises, as marketers and sales-people begin to look to these organizations from the metadata and inference about what customers are willing to buy, particularly under tight economic conditions. There's going to be a need to tie traditional Customer Relationship Management (CRM) and sales applications with some sort of a process overlay into the metadata that's available from these Web-based cloud environments, where users have shared so much inference and data about themselves. I look for some mash-ups between social data and the sales and business development applications and data. (**) (*) Gartner, Inc. (NYSE: IT) is the world’s leading information technology research and advisory company. - Management & Quantitative Methods

6. Agenda: Business Intelligence & Data Sources Internal Data - External Data Le ricerche di mercato Il Campionamento Metodi Quantitativi per Economia, Finanza e Management

7. Business intelligence (*) (BI) refers to skills, knowledge, technologies, applications, quality, risks, security issues and practices used to help a business to acquire a better understanding of market behavior and commercial context. For this purpose it undertakes the collection, integration, analysis, interpretation and presentation of business information. BI applications provide historical, current, and predictive views of business operations, most often using data already gathered into a Data Warehouse or a Data Mart. BI applications tackle sales, production, financial, and many other sources of business data to support better business decision- making. Thus one can also characterize a BI system as a Decision Support System (DSS). (*) http://en.wikipedia.org/wiki/Business_Intelligence Business Intelligence

8. Business Intelligence systems are data-driven DSS. Internal Data Operational digital transaction CRM digital transaction External Data Public Data Base (Bureau of Census, Central Bank,..) Private Data Base (Consodata, D&B,..) Market Research Business Intelligence & Data Sources

9. Business Intelligence & Internal Data agents portals Management systems DW data collectiondata modelling & processing data analysis call center Business Intelligence Operational & Strategic Marketing Hints operations

10. Data Warehouse DMA Multi Level Summary OLAP Analisi Statistica Business Intelligence & Internal Data

11. Interaction between Customers & Company Digital transactions Billions of data Data Warehousing –Marketing Data Mart - Customer DataBase Data Mining (*) Customer Profiling (*) Data Mining is the process of extracting hidden patterns from data. As more data are gathered, data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling practices, such as marketing, fraud detection and scientific discovery. http://en.wikipedia.org/wiki/Business_Intelligence

12. Customer Profiling & Data Mining Marketing Datamart Strategic decisions Segmentation How to select target marketing segments? Make behavioural data available Analysis and classification Marketing plan implementation Evaluation of results Identify business area Marketing Datamart Tactical actions Propensity Models Who are the best prospect to target for the campaign? Extract sample data Scoring model building Campaignimplementation Evaluation of results Identification of prior cross-selling segment Marketing Datamart

13. Customer Profiling & Data Mining 1990 2000 Mail Order Finance Publishing Teleco New Media Scoring Model Behavioural Segmentation Credit Scoring Acceptance Score Card Credit Scoring Basel II Needs Based Segmentation Social Network Analysis