Fundamental disruption in big data science


Walmart appeals to a special type of customer: one who is looking to shop for bargains in a retail outlet center where virtually everything can be purchased—from groceries to fuel to oil changes. Walmart is a store where all products are stocked and ready to be sold for bottom dollar so that consumers can save money. This paper will examine this company’s typical consumer and assess how the business can obtain more data on the consumer in order to develop a strategy for increasing its business revenue.

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Who are Walmart’s Consumers?

A graph of the breakdown of Walmart’s business says a lot about who its customers are. The chart below shows that most customers in Walmart are there to shop for groceries and consumables. Fuel and other categories make up the next biggest segment. Entertainment, apparel, home, and health products make up the other portion of products that customers at Walmart are buying. In other words, customers shopping at the retail giant and shopping for their everyday basic needs: but they are also looking for deals and cut rate prices that can help them to save money.

With total household income stagnating over the past 10 years (since the Great Recession of 2007), customers are looking for the things they need at the lowest possible prices—and that is the target customer that Walmart has in mind when the company goes to stock its shelves.

Source: FRED (2018)

In terms of rank order and segment, consumers who are doing their everyday grocery shopping and consumable items purchasing are the number one target for Walmart. These customers are also looking for deals that they can use to save money: “Wal-Mart reaches out to the lower, middle class and the poor in the society who strive to meet their daily needs. This category of the market is the largest in the US and many other countries where it operates. This policy has made it a very popular name in the US. It also confirms why the company has a retail outlet in every city in the country” (Ferrell & Hartline, 2008).

Key Customer Data

Key customer data used by Walmart includes market segmenting and analyzing variables among its customers. The segmentation variables that Walmart utilizes include consumer behaviors as well as other variables demographics, geographical location, and psychographic characteristics. Walmart members have their purchases analyzed by the company so the business can identify trends in the shopping behaviors of its consumers. This helps the company to establish customer profiles that it can use to set up tracking measures to see how customers are responding to ads, to sales, to seasonal changes, and to the types of products that are offered. By analyzing customers’ Big Data, the company can also take advantage of web browsing information and online shopping mannerisms of its customers (McAfee et al., 2012; Swan, 2013; Wambler, 2015).

Customers who shop online want to be able to read about the product before they buy—and that includes both information provided by the producer as well as information provided by consumers. Customer reviews play a big part in how consumers shop—and Amazon has been very good about allowing customers to leave reviews and highlighting those reviews on its web pages. By analyzing customer reviews and obtaining information from surveys, interviews, and online questionnaires, the company also engages with consumers to find out what is important to them, what their shopping needs are and how they want their Walmart to best meet their desires.

Gathering Data from Employees

Employees serve as a great source of information when it comes to understanding customers. Employees are on the front lines, interacting with consumers and engaging with them on a daily basis. They hear consumers’ questions, they listen to their complaints, they receive their recommendations, and they see first-hand what customers are gravitating towards, what they are buying and what they are avoiding. Employees in Walmart stores know the customers because they see them every day. For corporate leaders in Walmart, interacting with employees and obtaining their views on who the customer is and what the customer wants can be one of the best ways to figure out the needs of the customer, target the customer and bring the customer into the store—i.e., converting marketing into sales.

Employees can be used to obtain observational data, information from discussions, focus groups and surveys. Each of these methods can be helpful in obtaining the kind of important data needed to form a well-rounded picture of the consumer (Chen & Tung, 2014). For the best results, observation methods will help Walmart to better understand its consumers and its employees can help to achieve this aim fairly easily while working onsite.

Observations will be conducted by stationing employees at strategic locations throughout the store so that they can monitor areas of the store that are of particular interest to the company—such as grocery, home, entertainment and health departments. Employees will browse these aisles along with consumers and note how consumers examine items on the shelf, whether they are looking for specific items or whether they are comparing prices and opting for the lowest priced item on the shelf.

The employees will carry notepads with entry marks where they can note down the types of behavior that customers demonstrate. For example, if a customer is a mother with children and lets the children pick out the breakfast cereal they would like to have, the employee will note this and record it in the data sheet in a column that lists products picked by children. This will allow the company to know how many times children themselves are allowed to pick out their own items. If the number is considerable, the company can begin to market products that might appeal to children so that they leap off the shelves more readily.

Employees will assess monitor for customers who seek out price differences in products. Some customers may demonstrate more brand loyalty than others and not pay attention to product differentials with respect to pricing. However, if customers are not interested in brands but are shopping for best prices, this information will be recorded in the data set carried by the employee. Employees will pay special attention to aisles where brand products are competing with off-brand products that are on sale. The observation of customers as they negotiate these aisles are choose between brand and off-brand products will be highly useful information for the company as it compiles its data into records that can then be used to conduct campaigns and marketing initiatives for specific consumers. Employee can also make special note of areas where consumers stop to shop and browse, such as the technology department or in the children’s toy department.

Employees will also record the estimated age and gender of the consumer, whether the consumer is shopping alone or is with children or friends, the amount of time that a consumer spends in any one aisle, the aisles that the consumer goes into, and the number of products the consumer buys. Some employees will focus on specific aisles and other employees will track individual customers as they enter the store in a randomized gathering of data. Randomized sampling can help to give a better perspective of who is buying in general and that statistics obtained through a randomized sample of observations can be useful when applying the data across the general target consumer segment.


In summation, Walmart’s customers are looking for the best prices for products that can be purchased all in one location. The goal of Walmart’s customers is to get great products at low cost so that they can save money. Potential customers that Walmart aims to attract are consumers who are looking for the best deals. However, in order to attract these consumers, the company has to be able to find out what they like and what appeals to them. By observing customers in the store, how they behave, where they linger, and what they look at, employees can help the company to obtain data about them and where they spend most of their time in the store. This information can be used to design marketing campaigns that target this specific consumer segment so that the company can increase its business revenues and stay competitive around the world and in emerging markets as well.


Chen, M. F., & Tung, P. J. (2014). Developing an extended theory of planned behavior

model to predict consumers’ intention to visit green hotels. International journal of hospitality management, 36, 221-230.

Ferrell, O. C., & Hartline, M. D. (2008). Marketing strategy. Mason, OH: Thomson

South Western.

FRED. (2018). Household income.

McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big

data: the management revolution. Harvard Business Review, 90(10), 60-68.

Swan, M. (2013). The quantified self: Fundamental disruption in big data science and

biological discovery. Big Data, 1(2), 85-99.

Wambler, S. (2015). Relational Databases. Retrieved from


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