Why People (Don’t) Buy: The GO and STOP Signals. Amitav Chakravarti and Manoj Thomas. Palgrave MacMillan. 2015.

Why People Don't BuyWhy People (Don’t) Buy: The GO and STOP Signals is a new publication from Amitav Chakravarti, Professor of Marketing in the Department of Management at LSE, and Manoj Thomas, Associate Professor of Marketing at Johnson School of Management, Cornell University. The main thesis of the book is that crafting successful marketing strategies requires two skills: the ability to diagnose why consumers buy and, more importantly, do not buy, as well as the capacity to predict which marketing actions can influence their behaviour. In order to set clear guidelines that can help the reader in developing these skills, Chakravarti and Thomas utilise three different tools.

First, the authors draw from a rich repertoire of behavioural theories to understand purchase signals. This approach relies on consumers’ actual behaviour rather than classic economic models. Normative economic models are based on the assumption that individuals are rational and are driven by the desire to maximise utility and minimise payouts. In contrast, descriptive behavioural models consider how cognitive limitations and affective responses challenge this assumption, and document decision-making patterns that systematically deviate from rationality. Relative to other books that have similarly promoted behavioural sciences as a way to predict real-world consumption decisions, such as Nudge by Richard Thaler and Cass Sunstein or The Last Mile by Dilip Soman, Why People (Don’t) Buy focuses on the behavioural underpinnings of pricing strategies.

Second, the authors employ a series of interesting cases from both business and public policy domains to illustrate their insights. These cases address questions such as: why are 100-calorie packs appealing to consumers? Why did the heavily touted ‘Fair and Square’ pricing model adopted by JC Penney fail? In what circumstances do monetary incentives succeed in encouraging socially responsible decisions and in what circumstances do they miss the mark?

One of my favourites of the cases provided in the book is that of Tata Nano, a city car manufactured by Tata Motors. Tata targeted low-income Indian families that rely on two-wheel transportation by proposing a safer and more convenient alternative at a comparable price. The Tata Nano was rolled out at $2000, slightly more expensive than the traditional two-wheelers, and positioned as ‘the world’s cheapest car’. Despite the Nano’s undeniable functional and economic benefits, its launch was deemed a failure because of low sales. According to Chakravarti and Thomas, Tata’s main mistake was to underestimate consumers’ symbolic needs, focusing on price at the expense of the sense of pride that low-income consumers experience when buying a car.

Another favourite case is that of ‘Cash for Clunkers’, a US programme aimed at increasing sales of greener cars. This programme identified the main obstacle in personal monetary costs, rather than personal non-monetary costs – such as the hassle of changing the car – and social costs – such as signalling low environmental concern to others. The programme therefore offered cash incentives to car owners to trade in their old cars for newer, more fuel efficient cars. These cash incentives were successful in convincing current car owners to switch to greener cars, and translated into a significant improvement in fuel efficiency. Through these practical examples of ‘misses’ and ‘hits’, the reader is able to gain insights into the factors that determine marketing successes and failures, with a focus on pricing decisions.

Third, the authors propose a unique ‘GO-STOP Signal Framework’ to structure the analysis of consumer behaviour and guide the implementation of action plans. This framework allows managers to understand why they normally make strategic mistakes and how to avoid them. The correct identification of the ‘stop’ and ‘go’ signals, as well as the prediction of their interaction, are key for the correct adoption of the framework. In this respect, the ‘GO-STOP Signal Framework’ advocates a rigorous, data-driven methodology based on the ‘Predict, Test, and Learn’ (P-T-L) model. This model fosters hypothesis testing through experimental research as a complement or alternative to more traditional research methods, such as focus groups and surveys. Despite the powerful insights that the P-T-L model can provide, few companies regularly use experiments when conducting consumer research.

Overall, I like this book because it combines a scientific, top-down approach based on classic and contemporary psychology and behavioural theories with a bottom-up, practical approach to addressing and solving managerial problems. It is also noteworthy that the book exposes readers to experimental research in a non-threatening fashion as a means to understand what makes consumers ‘go’ and ‘stop’ in their purchase decisions. Why People (Don’t) Buy: The GO and STOP Signals is a rare mix of rigorous thinking and managerially relevant examples. It is also an engaging read, thereby offering marketing enthusiasts and practitioners access to behavioural theories and methods in a way that is easy to understand, but never trivial.



  • This post was originally published on LSE Review of Books.
  • You may also like to listen to a podcast of a lecture by Amitav Chakravarti, recorded at LSE on 11 June 2015. 
  • The post gives the views of its author, not the position of LSE Business Review or the London School of Economics.
  • Featured image credit: Anthony Albright CC-BYSA-2.0

simona_bottiSimona Botti is Associate Professor of Marketing at London Business School. Prior to joining LBS, she was a faculty member at Johnson Graduate School of Management, Cornell University, and at SDA Bocconi, Bocconi University. Simona received a BA from Bocconi University in Milan, Italy, and a MBA and PhD in Marketing from the University of Chicago. Her research is on consumer behaviour and decision-making, with a focus on the psychological processes underlying perceived personal control and how different ways of providing and exercising control (choice, information, power and mastery) influence well-being.