The Business Market Or Service Determines Their Revenue, Sustainability, And Longevity

It has recently come to my attention that Target Co. utilizes data mining to extract a wide spectrum of information about its customers by accumulating, analyzing and storing data about customer purchases. While I understand that this practice enables Target Co. to simultaneously deliver individually targeted advertisements across its diverse customer groupings, thereby increasing the potential for sales and improving customer retention, I also understand that large amounts of data unearthed by data mining can be manipulated to uncover hidden purchasing patterns to predict and shape future purchase decisions. Therefore, although there are significant benefits to using data mining, there are also serious costs associated with data mining that

Data is an important component used by all technology and businesses to gain insights and refine their marketing techniques to improve customer experience. Through the use of data analysis companies can capture a large amount of data, and retrieve information regarding the company’s trends. In Richard’s case using data analytics allows him to gain better insights on customer behaviors, in which he was able to determine which factors influence a user to purchase the eReader early. These factors will allow the team to develop new business models and improve their marketing strategies to capture these individuals (“Big Data Analytics”, 2017). For example, if most of the early users are from California, it would be beneficial to promote the eReader

It became an issue for consumer, and they felt uncomfortable due to companies invaded consumers privacy without their consent. Another issue regarding data mining is there no clear policies around how the company uses data once they have collected the information. After Target received negative publicity regarding its original data mining approach, they change their strategy by mixing all their ads, so it not that obvious that they were spying on them. It makes customers’ to assume that everyone else gets same coupons and ads. Data mining has given Target awareness into the relationship between product sales and online reviews. Target retailers identify guests how write reviews, examining their history of purchasing and invited to write review on their products. This program was highly successful, leading Target to obtain incremental reviews and increase sales of those key products. More importantly, data mining has empowered companies to find new opportunities for growth, make better decisions to succeed business goals and safe money. The retailer industry utilizes data mining and customer analytics to support customer decisions. Exploring how collected data can be manipulated to identify customers buying patterns and increase profitability is a growing business

This gives businesses the opportunity to create product differentiation strategies that will help them establish and maintain a competitive edge in the market. This information also helps identify specific opportunities for further growth and development with existing products and services as well as potential opportunities for new products and services. The data gathered in this way helps businesses create successful marketing strategies that will appeal to customers personally and help promote great brand recognition. This area is so intriguing and worth more knowledge and development because it creates opportunity to get a better understanding of how people personally identify with the product or service they use and the why behind it. This method goes against the grain of management skills in which they stress the idea behind information is only as valuable as the money it can produce as this often refers to concrete numbers or dollars and sense and qualitative data is not captured in that way. It brings back the idea of getting to know your customers on a more personally level which helps to build trust and relationships that can be lost when looking at big box industries.

Kudler is looking for ways to increase sales and customer satisfaction. To achieve this goal Kudler will use data mining tools to predict future trends and behaviors to allow them to make proactive, knowledge-driven decisions. Kudler’s marketing director has access to information about all of its customers: their age, ethnicity, demographics, and shopping habits. The starting point will be a data warehouse containing a combination of internal data tracking all customers contact coupled with external market data

Data mining uses computer-based technology to evaluate data in a database and identify different trends. Effective data mining helps researchers predict economic trends and pinpoint sales prospects. Data mining is stored in data warehouses, which are sophisticated customer databases that allow managers to combine data from several different organization functions.

The government collects all kinds of useful information about our population. How many people live where, incomes, family sizes, ages, do they rent or own a home, and lots more demographic data that is free for the asking. Modern computer programs make possible for any company to take the masses of demographics and analysis segment populations. This has propelled data mining to the forefront of making customers relationships profitable (Ogwueleka, 2009). This will help Swan understand his customers better and find association between each segment. Customer have life cycle due in part to the time of year, so Swan can now structure his advertising and see results based on a better segment model rather than just counting customers. Data mining can also be used in customer retention applications identifying

When consumers shop online, data mining is collecting their buying habits and other online searches. With every search they do, their information is collected by companies as Acxiom. These companies collect data such as age, race, sex, education

As coined in an article in the St. Louis Post-Dispatch by Aisha Sultan, “Data is the new world currency.” Data mining is the process of analyzing data from different perspectives and then summarizing it into useful information. In essence is it applying all different types of what if scenarios on large swaths of data to get possible results to aid in better decision making. This sort of decision making isn’t something new, it’s the technology aiding the decision making that is new. This has reduced the amount of time it takes in the decision making process and given the

According to Competing on Analytics: The New Science of Winning, the critical value of analytics is important in today’s forward-looking enterprises, especially in a new data age. Every company and organization should strive to become an analytical competitor. Competing on Analytics reveals how companies think about their data and their exploitation of that data. Also, it highlights how companies such as the Boston Red Sox, Netflix, Amazon.com, CEMEX, Capital One, and Harrah’s Entertainment use analytics to build their competitive strategies and make better decisions in the severe competition. These companies and organizations use analytics to identify the most profitable customers, accelerate product innovation, optimize supply chains and pricing, and leverage the true drivers of financial performance.

Data mining can aid direct marketers by providing them with useful and accurate trends about

To compete effectively in an era in which advantages are ephemeral, companies need to move beyond historical, rear-view understandings of business performance and customer behavior and become more proactive(tableau). Predictive Analytics is the use of data science for audience profiling. Generic audience profiling involves determining specific characteristics of your target audience and creating specific personas to represent each type of person within your target audience. Predictive analytics is essentially the same process, but from a data perspective (koozai). Predictive analytics can be used in wide areas in the industry, it’s importance is not constrained to a particular domain and ranges from marketing, telecommunication, retail, banking, etc. For example, the telecommunication industry has noticed a high customer churn since the switching costs are slim to none. So telecommunication companies operating in this industry are looking for new ways to differentiate themselves from competitors in order to retain customers. By using predictive analytics as a solution to this problem, they would be able to understand the customer needs, requirements and retain them also allowing them to acquire new ones more effectively. With predictive analytics, companies can predict trends, understand customers, improve business, drive strategic decision making and predict behavior. A company named Cox Communications, the third largest cable entertainment and broadband

Perhaps the most misunderstood use of such information happens in the advertising business. Advertising companies specialize in selling products to clients, and what more efficient way is there than to use results extracted from datasets to make accurate speculation and target customers individually based on their purchase patterns? This is a practice known as customer profiling: creating a portrait of many individuals purchase patterns to discover correlations and more effectively advertise products. The misunderstanding lies in where the information that the companies use is obtained.

This has taken the competition in this ever changing globalized world to another level quite literally. There is no room for outdated or 'gut feeling' method of conducting businesses. Predictive Analytics is a real game changer and s here to stay. From inventory planning,

Predictive Analytics are able to help companies make since of their data that have gathered throughout their lifespan. This opens up the door to a lot of potential advantages. Many organizations in the past have based decisions based on what they believe to be true. They have had very little means to actually being able to know for sure if they were making the most logical decision possible. Don’t get me wrong there have been very intelligent people making these decisions that have been able to lead many successful companies. If these executives were already able to lead very successful companies based on theory imagine what they can accomplish after they are able to make since of all of their data.