Chat with us, powered by LiveChat Data analytics plays an important role in marketing management. There are many types of data to be gathered and studied. Structured data are quantitative data that can be stored in - Writeedu

Data analytics plays an important role in marketing management. There are many types of data to be gathered and studied. Structured data are quantitative data that can be stored in

Deliverable Length:   400–600 words

Primary Discussion Response is due by Thursday (11:59:59pm Central), Peer Responses are due by Saturday (11:59:59pm Central).

Data analytics plays an important role in marketing management. There are many types of data to be gathered and studied. Structured data are quantitative data that can be stored in a fixed format such as a spreadsheet or list. These data can be easily processed by computers. Examples of structured data are the following: 

  • E-mail address 
  • Home address 
  • Age 
  • Gender 
  • Credit card number

Unstructured data are not easily put into categories. Examples of unstructured data are the following: 

  • Internet search results 
  • Body of an e-mail 
  • Data from social media sites, such as Facebook or LinkedIn 
  • Photos 
  • Text messages 
  • Voicemails

Semi-structured data are a combination of both structured and unstructured data. An example would be an e-mail. The to and from fields would be considered structured data that are easily categorized, and the body of the e-mail would be unstructured, which is not as easily categorized. All of these data combined, along with other types, contribute to big data

Watch the following video for more information about big data and analytics in marketing: The Importance of Big Data and Analytics in Marketing

Using what you have learned, use the following questions to guide your response: 

  • How are these data used by companies? For example, a company that makes video games for Xbox or PlayStation can track the common actions that their players take before making an in-game purchase. 
  • Describe 2 ethical dilemmas that business organizations face when using big data. For example, sharing private customer information with your best friend without the customer’s consent would be a potential ethical dilemma because that is private information held by the business.

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