Importance Of Data Technology

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

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.

Companies now bombard consumers with popups, online advertisements and commercials. It is now virtually impossible to escape advertisements because they come at you on virtually every platform. So much so that advertisements go unnoticed by the consumer due to their sheer volume. The companies methods are changing as well. While advertisements for necessities are often shown on the street to appeal to a wider range of consumers, data from out computers is used to market to each consumer individually.

For years, companies have been relying on market research, data tracking, and data warehousing to help create marketing strategies. Marketing managers rely on this data to spot opportunities and problems and try to stay ahead of the competition.

Deeper, more textured and widespread data exists in automotive today than ever before. We know our customer’s purchase habits, their equity position, what cars they are interested in, how often they view inventory - where they travel digitally. Data is important, but not the end game. The end game is what we can do with the data. Walking the exhibitor’s hall, I saw some fresh, innovative and sometimes disruptive solutions. I saw a few others that may not make it but out of the group, many will. More encouraging, solutions providers view data as a tool to solve problems plaguing our industry. This is a change in direction from an industry that saw the data itself as a product.

Growing up in a business background where my family had been in the international trade business for the last hundred years, I was always amazed to see how data science gradually involved in our family business. I have also gained insight into the data science tools and how data science improved our business decision-making and performance. During the past three years, I have found my post-graduation in Marketing and Finance comes out to support my success on my professional career path, where I experienced various school projects on the real expanse of marketing and developed my analytical skills. Moreover, studying Marketing, Finance, Statistics and Mathematics has evolved my analytical thinking, logical reasoning and decision making skills and incited me to delve further into the data science field.

But knowing exactly where a shopper is in-store opens up a wealth of other functions that will mean their favourite device, the smartphone, will almost certainly be the retail brand’s main communications channel going forward.

Advertisements have become more popular within the past few years. The reason for this is because this generation, Generation X, is much more virtual friendly and much more reliant on technology. Bert Markgraf, the freelance writer and graduate of McGill University, speaks about this, saying:

Data Science can have innumerable advantages. It can be used as a powerful tool in decision-making.

Consumer behavior has changed and along with it the practice of marketing. More than a century has passed since John Wanamaker, the recognized founder of the department store, famously remarked, “Half my advertising is wasted – I just don’t know which half.” What Wannamaker was struggling with was an inability to accurately assess the effectiveness of his advertising and marketing campaigns. He knew that his marketing had some effect, since he was successful in selling, but since he did not have the tools available to directly measure his advertising and marketing efforts he could not discern which ads or marketing efforts were directly contributing to the awareness, sales and furthering of customer relationships. Even today, one hundred years later, reaching the right audiences, developing ads and implementing marketing programs that can be directly attributed to consumer engagement, satisfaction and sales remains a vexing challenge for many marketers. Fortunately, however, with recent advances in marketing technology, including ad-tech, mobile, social, content, and analytics, the days of “wasted” marketing may soon be behind us. Marketing leaders are reaching and responding to individual consumers with timely, relevant messages and offers, via both owned and paid channels, at every stage of the customer journey and at the moments that matter most to consumers; as a consequence, they’re

According to Provost and Fawcett (2013) data-driven decision making refers “the practice of basing decisions on the analysis of data rather than purely on intuition.” For Example, a seller could select the advertisement based on his long experience in that field or his eye for what will work. He can also do the selection on the analysis of data regarding how the people will react to different advertisements. In today’s organization, managers make a great effort to use data driven decisions because data-driven decision helps in gaining competitive advantage and it can be most interesting and transformable. A study from the MIT center for Digital Business found that the organizations driven most by data-based decision making had 4% higher productivity rates and 6% higher profits. (Rouse)

Over the last several years, advancements in technology have changed how everyone is living their daily lives. This has transformed the way that various stakeholders are interacting with each other on a regular basis. However, with any kind of transformations is when the experts will predict that society is undergoing a major shift. Yet, in the long run these changes will have a limited impact. As the increases in the total number of improvements for IT and mobile phone technology are leading similar claims. To fully understand how these transformations are different requires: carefully examining the way these shifts will occur and the impact of target based advertising on a user's location. Together, these elements will highlight how: distribution, retail, wholesale and marketing strategies are shifting.

Organizations may apply analytics to business data to describe, predict, and improve business performance. Specifically, areas within analytics include analytics, prescriptive, enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modelling, web analytics, sales force sizing and optimization, price and promotion modelling, predictive science, credit risk analysis, and fraud analytics. [1]

These ads can be modified to achieve a more particular, focused on gathering of people on account of programming that "peruses" the site or data people are looking for on their cell phone and showing ads that identify with that data. Advertising is made more powerful by this customization, and in light of the fact that most clients/ potential clients dependably have a cell phone helpful, their presentation to ads is expanded

is more tailored to the consumer. Using a customer’s location, behaviors, preferences, and demographics helps businesses personalize this content so that the advertisement will be more likely to gain the viewer’s interest. With all the digital and mobile devices being used, the IoT has plenty of room to grow in this industry. (EMarketer)