With the huge amounts of data created, data analytics can help with decision making. This brief book is a good resource on market intelligence, with practical examples. It explains data analytics for market intelligence based on statistical methods. Its strength is that it gives real-life examples with easily understandable statistical analytics. Compared to other books in the field, Akinkunmi covers practical information in a concise way. This makes it a good book for beginners. Also, the book’s methodology is to introduce concepts with examples, which is an effective way to present data intelligence.
The book has ten chapters. It starts with an introduction to market intelligence. Chapter 2 gives the steps involved in conducting market research. Chapter 3 is about qualitative techniques: the self-administered method and the personal interview method. Chapter 4 presents quantitative techniques in three categories: mathematical, statistical, and programming. Chapter 5 looks at the different stages of data preparation involved in quantitative analysis: data validation, data editing, data assembling, data coding, and data transformation. Chapter 6 is about analyzing survey data and obtaining strategic insights from survey research. An index methodology is presented in chapter 7. Chapter 8 gives information about digital media and lists the differences between digital media and social media. Chapter 9 explains the components of causal evidence: temporal sequence, concomitant variation, and non-spurious association. Chapter 10 is about mobile data mining.
The chapters are written in a very readable way. Each includes an example. One weakness is that data mining is a very broad topic to be written about so briefly. The book’s title and content should only include market intelligence.
The book can be a good resource for academics, applied scientists, researchers, and practitioners interested in market intelligence. It may also be successful in sparking the interest of beginners in the field without intimidating them.