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Digital Marketing - Study Notes:

Data protection

Remember that there are a number of data protection considerations associated with web analytics. As a result of regulations such as GDPR in the EU, tracking personally identifiable information – or PII – now requires explicit consent from the consumer. For example, you need to get consent if you are collecting cookie data from website visitors for analysis or in order to personalize advertising experiences. Many analytics programs anonymize user names, IP addresses, and other PII, but you still need consent to share website visitor data anonymously with third parties, such as Google Analytics, or with ad platforms.


In relation to GDPR, you must manage personally identifiable information correctly, and within the terms of the consent provided by your website visitors. Collecting PII as part of your analytics program, and then mismanaging that information, can risk a data breach for improper use of PII.

Data policies

To ensure this doesn’t happen, your company should have a clear policy or guidelines in place detailing how the analytics data you collect is used and managed. This should include explicit opt-in visitor consent to track user visits, collect anonymous cookie data, and share anonymously with third-parties such as Google and Facebook for personalization of ads.

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Jack Preston

Jack Preston is a Data Scientist working within marketing analytics, with a particular focus on strategic customer loyalty. Jack has experience working in both small-scale startups and large corporates, including dunnhumby and Notonthehighstreet. He also holds an MSc in Business Analytics from UCL where he graduated with distinction.


Jack Preston
Skills Expert

This short course covers the principles of analytics and demonstrates techniques and useful tools that you can use to develop and refine your knowledge of data analytics.

You will learn:

  • The fundamentals of data, collecting data, and processing data, including best practices, techniques, and challenges
  • The principles of web analytics, the benefits and limitations of Google Analytics, terminology for reporting, and the legalities around consent and data privacy
  • The concepts of Big Data, the processes around data, including mining, scraping, cleansing, and de-duping, and the various languages and programs for testing your data
  • The importance of AI, Machine Learning, analysis types, the value of testing hypotheses, and forecasting based on the data available
  • How best to report and present data findings to management and the different tools available to you

Approximate learning time: 3 hours