Navigating with Data: Marketing Information Systems for Decision-Making

Learning Outcomes

In today’s data-driven world, organizations rely on accurate, timely, and actionable information to make informed decisions. This chapter explores the critical role of marketing information systems (MIS) in transforming raw data into meaningful insights. By integrating tools such as internal records, marketing intelligence systems, and decision support systems, organizations can navigate complex markets with confidence.

This chapter also examines marketing research processes and the use of both qualitative and quantitative data to address challenges and seize opportunities. Real-world examples from sectors like tourism and hospitality illustrate how these systems and methods enhance strategic decision-making.

After reading this chapter, you should be able to:

  1. Define and explain the components of a marketing information system (MIS).
  2. Distinguish between different types of data used in marketing research, including primary vs. secondary and qualitative vs. quantitative data.
  3. Evaluate the advantages and challenges associated with various data collection methods.
  4. Describe the role of customer relationship management (CRM) systems in managing the customer lifecycle.
  5. Analyze how CRM systems integrate with and support the components of a MIS.
  6. Identify emerging trends in marketing research and their potential impact on the industry.
  7. Apply concepts of marketing information systems to real-world scenarios in the tourism, hospitality, and recreation sectors.
  8. Discuss the benefits of using marketing information to inform strategic decision-making.

Opening Thoughts

How Bad Data Keeps Us From Good AI

In this engaging TED Talk, Mainak Mazumdar highlights a critical issue in the age of artificial intelligence: the impact of bad data on AI’s effectiveness. Through relatable examples, such as comparing urban data from Shanghai and New York, Mazumdar reveals how biased or incomplete data can lead to flawed AI-driven decisions. He emphasizes the need for robust data infrastructure to ensure ethical and accurate AI applications. This talk is especially relevant for marketers, as it underscores the importance of high-quality data in building reliable marketing information systems and driving effective decision-making.

“How Bad Data Keeps Us From Good AI” [9:59 min] by Mainak Mazumdar[1]

Chapter Topics

  1. Marketing Information Systems
  2. Marketing Research
  3. Customer Relationship Management Systems
  4. Using Marketing Information to Inform Strategy
  1. Mazumdar. M. (2020, October). How bad data keeps us from good AI [Video]. TED Salon: Dell Technologies. https://www.ted.com/talks/mainak_mazumdar_how_bad_data_keeps_us_from_good_ai ↵

License

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The Marketing Map Copyright © 2024 by Lian Dumouchel, Thompson Rivers University Open Press is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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