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

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

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

3. Business Intelligence 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

4. Business Intelligence & Data Sources 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

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

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

7. Business Intelligence & Internal Data • 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

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

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

10. Business Intelligence & External Data • Public Data Base (Bureau of Census, Central Bank,..) • Private Data Base (Consodata, D&B,..) • Market Research • Interaction between Customers & Company • No digital transactions • Sampling • Few data – Customer Table • Classical Statistical tools • Demand Segmentation – Competitive Positioning

11. Le ricerche di mercato Ricerche Qualitative L’obiettivo è approfondire la conoscenza di un fenomeno di mercato, mediante la raccolta e l’analisi di dati qualitativi destrutturati. Ricerche Quantitative L’obiettivo è fornire un’accurata misurazione del fenomeno oggetto di ricerca, mediante la raccolta e l’analisi di dati quantitativi e/o dati qualitativi strutturati.

12. Le ricerche di mercato Cati Indagini quantitative Capi/face-to-face Metodi basati su questionario Cawi Postali/fax/autocompilazioni Indagini qualitative Focus group Interviste in profondità

13. Le ricerche di mercato L’esecuzione di una ricerca di mercato può essere schematizzata in quattro fasi: a)-fieldwork:la raccolta dei dati elementari; b)-trattamento elementare dei dati raccolti; c)-analisi daidati; d)-presentazione dei risultati.

14. Business Aim Targeted population Characters to be assesed Sampling error Choice of sample Fieldwork Techniques of data collection Data Audit Set-up questionnarie Data Analysis Pre-test questionnarie Presentation Quantitative Market Research Set-up Protocol

15. Le ricerche di mercatofieldwork Sondaggio È assimilabile ad un’intervista individuale, veicolata su un sottoinsieme (campione) di una “popolazione” di riferimento. L’intervista presenta delle peculiarità: • Ha forma strutturata • Limitato numero di domande aperte/ molte domande a risposta chiusa • Modalità di contatto usate: - telefonica - personali - postali - web- based

16. Le ricerche di mercatofieldwork Questionario E’ il format con cui vengono raccolti dati qualitativi strutturati e/o dati quantitativi La costruzione del questionario avviene attraverso: • Disegno del suo schema concettuale • Redazione • Verifica Modalità omogenee di rilevazione dei dati: le domande devono essere uguali per tutti gli intervistati e non devono lasciare spazio ad interpretazione soggettiva

17. Questionnaire & Information • Personal Data • Cultural/Social/Hobbies • Behavioral • Preferences • Quantities • Distributions • Importance/Satisfaction • Scales • Preference/Conjoint • Possible scenarios • Assessment

18. Questionnaire & Information • Qualitative Questions • Defined answer range • Non open questions • Quantitative Questions • At least 30-40 • Not ambiguous • Measurement • Absolute values • Percentages • Scale scores • Conjoint Section • Scores • Ranks