Predictive Analytics And The Retail Industry

He explains how big companies like ‘Xerox’ use data collected from social networks to hire people, or to collect data about what other things, company users like or dislike so they can change to make sure that users will like them even more.

“Predictive analytics uses technology to predict the future and influence it.” [27] It is predominantly being used to improve business processes, which is a great opportunity for entrepreneurs to achieve positive business outcomes [26]. The goal of this white paper is to discuss the impact of predictive analytics in today’s world and the various concerns that come along with it. The paper addresses key research questions like what are the legal and ethical concerns that rise from predictive analytics? And where can we use predictive analytics to get positive results? We have tried to analyze the current market situation in order to answer these questions, focusing on the key areas where predictive analytics has had positive and negative impact. After intense scrutiny of the facts and details encountered by us, we have come up with some recommendations and solutions to address the issues caused by the use of predictive analytics and how their effects can be balanced by organizations.

In order for a business to maintain a competitive edge, they need to be able to understand in real time the needs of their customer base. With the advancement of social media, information that once was a trickle has now become a flood and businesses who want to remain competitive must be able to capitalize on information quickly. By analyzing data, businesses are better able to directly focus their marketing efforts and prices to gain their customers notice and stay ahead of their competitors (Savitz, 2012).

The ability to compete on analytics is made possible by certain qualities some companies possess which allows them to collect and use immense amounts of data in a way that differentiates the success and practices of those companies amongst any other businesses. Davenport and Harris (2007) define analytics as “extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions” (p. 7). Therefore, to be able to compete on analytics, a firm must not only use the data to extrapolate and execute strategies and models in order to drive business, but also to use that data better and smarter than their competitors. This requires forward thinking and continual developments of current analyses and practices. With regard to Davenport and Harris’s criteria and concepts on the ability to compete on analytics, Old Navy LLC’s practices will be analyzed to find whether the company is able to compete, is a competitor, and how it competes, if at all.

The increasingly popular terms “big data” and “predictive analytics” have become so widely discussed that, in many ways, they lack a cogent meaning – even within the financial industry. The Capstone team used the literature review as an opportunity to scan the field for defining characteristics, resulting in a suggested guide for how the Federation should articulate these concepts. Generally speaking, big data is about the growing availability of data, as well as the tools needed to analyze the information. Predictive analytics refers to the analysis of big data which can help uncover patterns, correlations and trends that were otherwise unknown to the organization. Predictive analytics is also known as

We are at the forefront of an information revolution. Firms are increasingly relying on data to drive strategic and business decisions. Upstart companies are giving market leaders a run for their money by tapping into advanced data analytics, statistical modeling and open source software. Multi-billion dollar companies like Uber and Airbnb have shown a groundbreaking data-driven way to connect its products & services to their customers. We are living in a world where every customer touch point with a digital device is being recorded and monetized. Every business has to reinvent, transform, and adapt its products and services to meet the demand of its digital savvy customers or face the risk of becoming obsolete.

One example of data collection that can be valuable to businesses is the monitoring of a customer’s shopping habits. For example, a twenty three year old female who lives in Atlanta and goes shopping at Target in March to buy the following items: a purse that is big enough to function as a diaper bag, cocoa butter, a bright blue rug, and magnesium supplements. Based on this data Target states that there is an 87 percent chance that this woman is pregnant. Target will then begin to send her directed advertisements that they know will entice her to buy something. The collection of the data is used to trigger habits in Target’s customers that ultimately leads to increased profits for the store (Duhigg,

Data helps teams create broader and deeper customer insights. We can now intentionally track a prospect’s purchase history, product usage patterns, and social media behavior.

The topic of the article is about a company called Acxiom. A company that uses large-scale data mining and analytics to receive information based on public records, surveys and other items consumers searched on the internet. The author’s argument is that data mining is an invasion of privacy for the consumer. While some consumers may benefit from data mining to receive personalized offers from companies, others may feel it’s stalking and may not want it. The author’s use facts from several interviews conducted with privacy advocates to persuade readers. Therefore, this article is valuable since it informs consumers that the information they are putting on the web is appearing into a database. Plenty of consumers would rather have their information private. Therefore, if companies are using our information in a database, they should need permission from the consumer. Acxiom sells Consumer Data Products Catalogs, which offers hundreds of details on consumers, to

Technology is another segment that will have a major impact on Best Buy in the near future. Predictive analysis, social media, and multichannel retailing are trends that are most important in Best Buy’s general environment. Knowing your customers is a critical part to any industry, and predictive analysis is becoming one of the best ways to accomplish that objective. By correctly using technology to control the high volume and availability of data, companies can understand customers’ wants. A core competency of both Amazon and Netflix predictive analysis; based on previous purchases or views

The sections below go into greater detail about how organizations can use analytics as a competitive weapon to introduce new goods and services and support existing ones.

Walmart is the biggest retailer in the world and handles more than one million customer transactions every hour and generates more than 2.5 petabytes of data storage (Venkatraman & Brooks, 2012). To put this into perspective, this data is equivalent to 167 times the number of books in America’s Library of Congress (Venkatraman & Brooks, 2012). So how can Wal-Mart use this massive amount of data and what useful information can this data provide? This paper will provide a brief overview of the importance of Business Intelligence (BI) and how the largest retailer in world, Walmart, is using it.

In today’s business world, more than 90% of businesses engage in social marketing. Social media ‘…when it is done right, can lead to more customers, more traffic and more conversion (DeMers, 2014).’ Big Data can be used to extract customers’ information that can shed light on patterns and behavior. This information can lead to product

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Wal-Mart’s advanced data-mining tools allow them to fine tune and improve customer responsiveness, giving customers what and when they want in offer. It can be compared to