What is Mystery Shopping? – A Tool For Retail Optimization
Mystery Shopping is a fascinating method of gauging customer experience where individuals are recruited to portray actual customers that shop at a store. Feedback is then taken through these ‘mystery shoppers’ and the company uses it to evaluate how close is the actual experience of the customers to the desired one. It prompts the company […]
Features of CRM
Customer Relationship Management is a strategy which is customized by an organization to manage and administrate its customers and vendors in an efficient manner for achieving excellence in business. It is primarily entangled with following features: Customers Needs- An organization can never assume what actually a customer needs. Hence it is extremely important to interview […]
Corporate Governance and Financial Crisis
The ongoing financial crisis has proved that Corporate America and the Corporates in other countries around the world have exhibited behavior that can be described as mismanagement and not keeping in tenets of good corporate governance. In this respect, some of the criticism that has been directed at corporate leaders and the bankers in particular […]
Types of Retail Outlets
Retailing refers to a process where the retailer sells the goods directly to the end-user for his own consumption in small quantities. Types of Retail outlets Department Stores A department store is a set-up which offers wide range of products to the end-users under one roof. In a department store, the consumers can get almost […]
Relationship Management is not a Marketing Strategy Alone
Customer Relationship management is a two way interaction. The Organisation has got to devise ways and means to reach out to the customer and more importantly receive the feedback received from the customer. There are two important aspects to be considered in a Customer Relationship Management. First is the customer interaction in terms of quality […]
If marketers had all the data about consumers that they can then use to predict consumer behavior, which would be the marketers dream come true. Until now, marketers had enough data about consumers that they then modeled to arrive at probable consumer behavior decisions. This data culled from marketing research was adequate until now when the extrapolation of the trends could translate into predictions of consumer behavior.
However, in recent years, marketers are going one-step ahead and instead of extrapolating data to predict consumer behavior, they are now turning to Big Data or data about virtually all aspects of consumers that would help them in predictive analytics or the art and science of accurately mapping consumer behavior.
In other words, Big Data is all about how marketers collect everything possible about consumer behavior and predict not only consumer behavior but predict what they are doing and how they would behave in future. For instance, Big Data provides marketers with the ability to identify the state of the consumers as can be seen in the recent prediction by the retailer giant, Target, about a woman being pregnant based on her consumer buying data.
This is the promise of Big Data that goes beyond merely extrapolating trends, instead, identifies, and predicts the next move of the consumer based on his or her current state. This would be like getting inside the minds of the consumers and instead of merely knowing what they would probably purchase, marketers would know with accuracy about what consumers are likely to do in the future.
The term Big Data has been coined because it gives marketers the bigger picture and at the same time lets, they model consumer behavior at the micro level. The integration of the macro data and the micro trends gives marketers’ unparalleled access to data, which can then be used to accurately predict consumer behavior.
The collection of Big Data is done not only from the consumer buying behavior but also from mining all the available data in the public and private domains to arrive at a comprehensive picture of what the consumers think and how they act.
The promise of Big Data is boundless for marketers who can now think ahead of the consumers instead of the other way around as well as preempt possible consumer behavior by targeting products aimed at the future actions of the consumers.
Of course, the promise of Big Data also comes with its perils as the tendency to be the master of consumer behavior can lead to serious issues with privacy and security of the data available with the marketers.
The example of Target predicting whether the woman was pregnant or not based on her shopping habits was received with both enthusiasm as well as alarm. The enthusiasm was from the marketers whereas the alarm was from the activists and experts who deal with privacy and security of data.
The point here is that Big Data places enormous responsibilities on marketers and hence, they have to be very careful about the data that they hold and the prediction models and simulation that they run.
If they chose to predict whether someone is going to do something next based on the results from the model, this prediction can also be used for unwelcome purposes and as can be seen in the recent revelations about tracking and surveillance, the data can be compromised or used to target innocent consumers. This is the reason why many experts are guarded as far as Big Data is concerned and they are waiting for the marketers and the regulators to frame rules and policies on how Big Data can be used in practice.
Finally, it must be mentioned that whichever stance one might have about Big Data, the potential uses of it for predicting the outbreaks of diseases and controlling crime are indeed boons to the regulators and the law enforcement agencies and therefore, it would be better for all stakeholders to decide on the kind of purposes for which Big Data can be used.
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