Data Privacy Strategy

eCornell

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  • online
  • on demand

eCornell

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Who should attend

  • CMOs
  • CIOs and CTOs
  • Mid- and senior-level marketing managers
  • Brand and product managers
  • Data scientists and analysts
  • Web developers
  • Tech leaders and IT professionals
  • Consultants

About the course

With the expansion of regulation and consumer protection mandates, data privacy has emerged as one of today’s most urgent and complex marketing and technology issues. It’s now something for which every organization must develop an effective strategy.

Many countries have passed restrictions on how marketers can use data in order to protect customers. While this can limit the business value of data, there are solutions that can enable you to provide data protection while also maximizing the data’s business value.

In this certificate program, you will explore your organization’s data privacy journey. This starts with examining the types of data you collect and the privacy risks associated with this data. In particular, you will focus on privacy challenges that arise in customer relationship management and digital marketing data, along with possible solutions. Next, you will examine privacy policies of today’s leading companies and audit your own company’s privacy policy. You’ll have the opportunity to calculate various accuracy metrics to measure loss of business value due to privacy approaches such as aggregating or anonymizing customer data. Finally, you will explore emerging issues with newer forms of data such as text, geolocation, images, and IoT data.

Throughout this program, you will calculate accuracy, uniqueness, privacy violations, and other metrics that will enable you to implement appropriate data policies and strategies that will enhance privacy while minimizing negative impacts to your business.

To be most successful in this program we strongly recommend having prior experience in statistics or marketing analytics. For the best experience in this program, it is recommended to take these courses in the order that they appear.

Data Privacy in Marketing

In this course, you will explore your organization’s current data privacy approach and assess how vulnerable your customers’ personal identification data is to data breaches. First, you will explore various categories of data breaches, both intentional and unintentional. You will then determine the privacy risk for your customer data by classifying each data element’s identifiability and sensitivity. Next, you will explore the Organization Data Privacy Journey model and assess where your firm is in that journey. By the end of this course, you will have drawn the connection between data privacy and risk through the exploration of customer relationship management and digital advertising use cases.

Defensive Data Strategies

In this course, you will determine the best defensive strategy for data usage under privacy constraints. You will explore the relationship between transparency and control by conducting an audit of your organization’s privacy policy. You will evaluate high-level protection approaches to masking customer data and examine data from a customer acquisition campaign to assess accuracy of the metrics. Finally, you will measure profitability loss from defensive data protection measures.

KEY COURSE TAKEAWAYS

  • Map your organization’s data privacy journey
  • Assess risks and vulnerabilities to customer data in your organization
  • Determine the best defensive strategy for data usage under privacy constraints
  • Create the best data protection solutions to maximize your marketing insights
  • Determine strategies to handle privacy with unstructured data

WHAT YOU'LL EARN

  • Data Privacy Strategy Certificate from Cornell Johnson Graduate School of Management
  • 40 Professional Development Hours (4 CEUs)

Experts

Sachin Gupta

Sachin Gupta is Henrietta Johnson Louis Professor of Marketing at the SC Johnson Graduate School of Management. Professor Gupta''s research focuses on analytical models of marketing phenomena, including discrete choice models of consumer behavior, marketing mix models, measurement of returns on m...

Matthew Schneider

Matthew Schneider develops data protection methodologies for real world data sources (e.g., text, customer-level data, or third party datasets) to protect consumer privacy. Importantly, his methodologies also preserve the value of a variety of business use cases. He is an Assistant Professor of B...

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Data Privacy Strategy at eCornell

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