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82157 - DATA ANALYSIS FOR MARKETING DECISIONS LABORATORY

Anno Accademico 2017/2018

  • Docente: Gabriele Pizzi
  • Crediti formativi: 3
  • SSD: SECS-P/08
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Bologna
  • Corso: Laurea Magistrale in Direzione aziendale (cod. 0897)

Conoscenze e abilità da conseguire

This course is designed to give students an appreciation of the scope and nature of marketing models analytical techniques. The goal of the course is to make students knowledgeable users of secondary and primary marketing data. The course has a methodological orientation; it introduces the concepts and methods of data analysis for marketing decisions. Specifications and interpretation of these models represents an important part of the conscious manager’s toolkit, and offer value to future managers interested in pursuing CRM (customer relationship management) activities. Students work with cases, and assignments that show how specific methods pay off in terms of better targeting and in turns increased customer profitability. The course uses readings, case studies, computer lab exercises, and team work projects. The main objectives of this course are: - To familiarize students with different types of real world data, and some advanced statistical techniques that can be applied to analyze customer-level data. - To provide students with the analytical and empirical skills required to develop predictive modelling processes and apply them to problems of managerial interest - To provide students examples and tools to develop good instincts to judge the appropriateness, performance, and value of different marketing models.

Contenuti

    1. CustoCustomer Satisfaction measurement and analysis
    1. Survey Preparation
    2. Segmentation, Targeting and Positioning
    3. Cluster analysis and customer segmentation
    4. Multi-dimensional scaling and perceptual maps
    5. Pricing and Promotion Strategies
    6. Conjoint Analysis and pricing/product decision
    7. Principles of retailing and channel management
    8. Category management: a customer-based perspective on assortment strategies; implementation of the card sorting technique
    1. Customer Satisfaction measurement and analysis
    2. Survey Preparation
    3. Segmentation, Targeting and Positioning
    4. Cluster analysis and customer segmentation
    5. Multi-dimensional scaling and perceptual maps
    6. Pricing and Promotion Strategies
    7. Conjoint Analysis and pricing/product decision
    8. Principles of retailing and channel management
    9. Category management: a customer-based perspective on assortment strategies; implementation of the card sorting technique

    alue Analysis: valore per il cliente e valore del cliente

    · Segmentazione, Targeting e Posizionamento

    · Cluster analysis e segmentazione della clientela

    · Multi-dimensional scaling, mappe percettive e posizionamento

    · Strategie di prezzo e di promozione

    · L'Analisi Congiunta e le decisioni di prezzo e prodotto

    · Fondamenti di retailing e gestione dei canali distributivi

    · Category management: una prospettiva analitica basata sul cliente per la definizione dell'assortimento

    · Metodologia sperimentale

    · Raccogliere e analizzare dati sperimentali

    Customer Value Analysis: valore per il cliente e valore del cliente

    · Segmentazione, Targeting e Posizionamento

    · Cluster analysis e segmentazione della clientela

    · Multi-dimensional scaling, mappe percettive e posizionamento

    · Strategie di prezzo e di promozione

    · L'Analisi Congiunta e le decisioni di prezzo e prodotto

    · Fondamenti di retailing e gestione dei canali distributivi

    · Category management: una prospettiva analitica basata sul cliente per la definizione dell'assortimento

    · Metodologia sperimentale

    · Raccogliere e analizzare dati sperimentali

    Customer Value Analysis: valore per il cliente e valore del cliente
  • Segmentazione, Targeting e Posizionamento
  • Cluster analysis e segmentazione della clientela
  • Multi-dimensional scaling, mappe percettive e posizionamento
  • Strategie di prezzo e di promozione
  • L'Analisi Congiunta e le decisioni di prezzo e prodotto 
  • Fondamenti di retailing e gestione dei canali distributivi 
  • Category management: una prospettiva analitica basata sul cliente per la definizione dell'assortimento 
  • Metodologia sperimentale
  • Raccogliere e analizzare dati sperimentali
    1. Customer Satisfaction measurement and analysis
    2. Survey Preparation
    3. Segmentation, Targeting and Positioning
    4. Cluster analysis and customer segmentation
    5. Multi-dimensional scaling and perceptual maps
    6. Pricing and Promotion Strategies
    7. Conjoint Analysis and pricing/product decision
    8. Web Analytics

    Testi/Bibliografia

    The course is mainly practical in its nature. Therefore, the best way to learn is actively participate in class discussion and laboratory sessions. Lecture slides can be used as a tool to support learning in class. There are not mandatory readings for this course. However, students might make reference to the following two books aimed to deepening either the theoretical concepts or the methodological issues.

    1) “Marketing Management (4th Edition) – Winer & Dhar – Pearson Ed.

    2) "Statistics for marketing and consumer research" - Mazzocchi, Mario - Sage, 2008.

    Metodi didattici

    The course is a combination of theory and practice.

    Therefore, each topic tackled in this course requires an overview of the relevant theory (2 hours) and the related analyses in the lab (4 hours)

    Modalità di verifica e valutazione dell'apprendimento

    Team-work assignment presentation during the last class;

    Written Exam consisting of open-ended questions in which students are asked to explain and discuss some outputs from the analyses learnt in class.

    Strumenti a supporto della didattica

    Lecture Slides made available to students on the AMS Campus platform;

    SPSS datasets for lab sessions

    Orario di ricevimento

    Consulta il sito web di Gabriele Pizzi