Product Margins
I was honored to have my book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die reviewed by Shakthi Poornima in Product Margins. Here is an excerpt from the review.
The power to predict who will click, buy, lie or die
Working in the field of Big Data means taking into consideration not hundreds or thousands, but millions, billions, or even bigger datapoints. And underneath all that data, lies unparalleled potential. Just imagine being able to predict one’s location up to multiple years beforehand by using GPS data (Microsoft), or being able to predict one’s risk of death in surgery (Riskprediction.org.uk). That’s what the book, “Predictive Analytics: The power to predict who will click, buy, lie or die” is about. It covers building applications in marketing, health care, fraud, finance, human resources., etc by a variety of parties — companies, banks, governments, even universities. Everyone has an interest in data.
…overall, the examples in the book are well-researched. What was interesting to me was the possibility of taking the predictions from various studies to building new products.s For example, Orbitz found that Mac users book more expensive hotels. “Orbitz applies this insight, altering displayed options according to your operating system” (p.81). A different study found that one’s inclination to buy online varies by the time of day: 8pm for retmail, late night for dating, 1pm for finance, and so on. Combining the insights from both studies can come in handy for marketing a new product, or starting an A/B test for that product. The potential for meshing various different types of data grows as different applications are developed around same or similar datasets, and as these datasets grow in size.