Driving Better Business Decisions through Superior Customer Insights

 by Prof. Arvind Sahay

Customers tend to behave differently from how they are expected to. And it is difficult to understand how and why they behave the way they do. Many business decisions, no matter which sector they are in, require accurate inputs from the world of customers. To name a few: pricing, investment in new capacity, strategies for business differentiation, market expansion (of the blue ocean kind), improving profitability, accelerating growth, strengthening market position through segmented strategies, extracting more value from an existing customer base, increasing or improving quality of market share, etc. Traditional inputs are still leading to high failure rates - partly due to execution issues - but also because many of the present methods have reached their natural limits. Technology and the digital world are mega transformers of not only their own lives but also of consumption choices available to customers. This leads to enormous complexity in how people think and behave, process value and make decisions, etc., and requires a broad and sophisticated array of methods to understand it better. This course, probably a first of its kind, combines insights from three different approaches, anthropology, neuroscience and big data, to attempt to achieve a higher level of insights.

Anthropology, with its focus on culture rather than individuals, offers a unique way to understand consumers and the texture of consumer experience rather than measurement of attitude or behaviour or demographics. It thus adds new dimensions and possibilities to business problem solving. Student gets exposed to some key anthropological frameworks and concepts and their use in business problem solving. Many problems in business benefit from a linear and rational approach, while other, less straightforward challenges benefit from the kind of insight that anthropology can provide explorative inquiry rather than hypothesis-based inquiry; qualitative evidence rather than just quantitative evidence; contextual, “thick” data about consumers rather than just “thin” (big) data.

Since human decision making is a combination of reason and emotion, conscious and unconscious, neuroscience has the potential to offer a lens to generate consumer insights by directly peering into the working of the human brain. With the development of different methods, there are now ways to understand the working of the brain that allow us to develop a framework to understand how the brain works through high level brain operating principles and through a mapping of neurological substrates, areas of the brain, and activity levels of various areas of the brain onto attitudes and actions of consumers. We provide deeper insights into the neuro-physiological activities and substrates of the brain that lead to attitudes and behaviour, and into the methods to generate these insights. Development of such insights would help managers generate managerial actions that are more likely to be successful with customers.

Big data is now becoming increasingly ubiquitous in areas as diverse as fintech, telecom, retail, healthcare and others. With the ubiquitousness of technology, there is a mass of data automatically captured from several sources and all talking to each other. This enables the detection of patterns that can be used to discover new insights, insights that will not be limited by the problem solvers’ ability and knowledge to hypothesise. Big data, therefore, offers another approach to generating customer insights and is the third lens in this course to generate customer insights that can lead to a better understanding of customer behaviour.

We integrate these three approaches, anthropology, neuroscience and big data, to develop a framework for arriving at better business decisions that flow from deeper and better customer insights.

Note: This course is offered by Rama Bijapurkar, Arvind Sahay, Julian Cayla and Srikumar Krishnamoorthy.

About The Author

Prof. Arvind Sahay

Prof. Arvind Sahay

Ph.D. The University of Texas at Austin