Summary: Big Data Marketing

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• 1 Week 1

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• What is one of the biggest challenges for today’s management?

  The increasing prevalence of "big data" -> increasing digitalisation of our society, business and marketing. 
  This is considered a major business challenge

• What can we say about Big Data?

  It's not a revolution, it's rather an evolution of the increasing availability of data observed in recent decades as a result of data developments -> leads to new data sources

• Big data have now become the norm and firms havestarted to understand that they might be able to compete more effectively by analysing these data. What are the problems with creating value from big data?

  • Lack of knowledge & skills
    
  • Lack on how to analyse & use these big customer data

  
  As a consequence, firms invest heavily in big data but are likely to face a negative return of their big data investments

• According to David Meer, what are the 3 stages firms typically go through? Why is this a bad vision?

  Data enthusiasm - Investment phase
  Data disappointment -Frustration disinvestment phase
  Data realism - Reinvestment phase
  
  This model leads to value destruction, negative ROIs, waste of resources, and enormous frustration.

• According to the authors of this book, they propose that firms should have sound initial expectations on the value of potential big data.What are the 4 elements of the Big Data value creation model?

  1. Big data assets
     
  2. Big data capabilities
     
  3. Big data analytics
     
  4. Big data value
     

• What's the role of culture in Big Data?

  Traditionally: marketing was a function that tended to rely on intuition and gut feeling
  
  Now: only having good ideas is no longer good enough. Now there is an increasing trend towards more data-driven or fact-based decision making

• When discussing Big Data Analytics, we make a distinction between 2 different forms of analytics. What are they and what do they consist of?

  Gaining insights
  Descriptive findings resulting from data analyses that provide input into marketing decisions
  
  Develop models to improve decision making
  Developed to direct and support marketing decisions. Analysts work to an end goal on a model, which is accepted by the management of the department and users of models
  
  The developed insights and models can create value for firms in 3 ways:
  

  • Decision support for marketing
  • Improved actions and campaigns
  • Information-based products and solutions

• According to Leeflang, what are the 2 different models that can be developed to drive marketing decision making?

  • Idiosyncratic - usually more sophisticated models developed to tackle specific marketing problems
    

  
  

  • Standardised - have become important tools to improve the quality of tactical marketing decisions
    

• Data allows customers to make more informed decisions. What at the strategies for analysing Big Data?

  It provides huge opportunities for analytical teams. 
  One of the easiest ways of using it is probably just to start up analyses and start digging into the available data. 
  With this, one might gain very interesting insights, which can guide marketing decisions

• Big Data is changing analytics, as it has specific characteristics that pose specific challenges for researchers and managers.What are they?

  Volume - scale of data
  Velocity - analysis of streaming data (faster analysis and action)
  Variety - different forms of data
  Veracity - uncertainty of data (not all data is reliable)
  Value - what is captured from analysing and using data