Marketing Management
Analytics – How does it measure success?
What is Analytics?
Analytics is the use of data, statistical analysis, explanatory and predictive models to gain insights and act on complex issues. Simply speaking, Analytics is the tool of discovering the pattern in different form of information, for instant text and survey, in order to visualize the data and have insights into business decision making.
Analytics work with wide ranges of metrics like statistics, computer programing and actual operation research to quantify and qualify performance. There are different areas in Analytics, including predictive analytics, business decision making, web analytics and marketing optimization. Take marketing optimization as an example,
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The world is changing every day with flowing and scattered information. There are about 80% of data existing in unquantifiable content, like images. The challenge today is to put all data together and make the right decisions or gain faster insight about your customers, competitors, new goods and services. Analytics help companies to draw the picture of what the customer’s want, who they are, the buying patterns by analyzing different data such as demographics, product purchase history or internet experience. Analytics help turning data and information into insight and company can develop their own comprehensive strategies to gain the competitive edge.
Analytics can show more comprehensive overview of your business, reducing the risk of making decisions on personal bias and of utmost importance to plan a more efficient future.
How does it measure success?
The groundworks of Analytics can be divided into 3 stages: Descriptive, Predictive and
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After the first stage of gathering and simple analyzation on information and data, Predictive analytics works further on detecting the correlation and trends. It helps organizations to use both historical and real-time information to predict behavior or outcomes, which helps the company to move from past view into forward looking perspective of the customer. Take Amazon as an example, the home page of yours and the others will be different because Amazon will constantly track the information you have browsed and your purchasing records. Then they will adjust the messages sent to each customer and provide a personalized experience to them. This stage helps organizations to understand the relationship of the past, present and future of the data. It helps to forecast the possible future including the what-if scenarios and risk
Google Analytics data collected on behalf of Peg and Kris, LLC for the company’s website domain, www.pegandkris.com, suggests that the company needs to change its current online marketing plan (Google Analytics, 2016). Weaknesses revealed by the data included overall low sales conversions, insufficient sales from social media and email campaign groups, and an usually high amount of sales conversions occurring on a desktop computer despite a larger number of visitors from mobile devices. Strengths included a sufficient number of visitors to the website and decent purchasing behavior from return customers (Google Analytics, 2016).
The Human and Ethical Aspects of Big Data, quickly outlines an array of ethical problems that big data has had and will continue to develop in the upcoming years in our society. The author begins by giving an example of the earliest use of big data, the census. Census data can provide a plethora of benefits to society, representation in government, civil planning, such as road and water treatment, as these take years to construct and having the population and these necessities, Time align is crucial. As the author, uses the example of the internment of Japanese-Americans in 1943. Here is big-data supposed to help the citizens of the Unites States, the big data that is supposed to be private. Now in 1943, big data being used to discriminate
7. Ledford, J. L., Teixeira, J., & Tyler, M. E. (2010). Google Analytics (3rd ed.): Wiley Publishing,
Marketing Analytics is another concept that is very essential for your business or company. It comprises of all the technologies and process that would allow you to evaluate the performance of your marketing campaigns and initiatives.
The statistical inferences I have observed are mostly in one dimension. The use of Dash Boards (unfulfilled orders, open tickets, etc.) the creation of Fusion Center used in many occasions as past performance but not to try to anticipate future behaviors or to capture changes in demand on the spot. The spreadsheets, and graphs that are displayed are at most per supply chain and not as a metric compared to the standard metrics decided by senior leadership. The intention of senior leadership is to go in the direction of enterprise analytics but I see it is relatively in its
The management can make use of the reports to track progress and attain its goals. Additionally, it can control the expenditure and increase the revenue. By analyzing the business reports you can gain an insight into the trends and take effective strategies to increase profits. In most cases, the managers review the reports and check it for anomalies. Helps adopt right
If the organization is unable to spend huge amounts on this web analytics tools and the corresponding resources it is better to spend some money on the
Data can give you quite a bit of information about your customers. By examining it, you will be able to begin to see patterns and learn the habits of your customers. This could mean that you are able to provide the correct number of products at the perfect time instead of having a shortfall or being left with additional stock long after interest has fallen in the product.
Google analytics can be applied in big as well as small businesses to support decision-making processes. In sense, each kind of business has its own
You may ask what big data analytics is. Well according to SAS, the leading company in business analytics software and services describes big data analytics as “the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions.” As the goal of many companies which is to seek insights into the massive amount of structured, unstructured, and binary data at their disposal to improve business decisions and outcomes, it is evident why big data analytics is a big deal. “Big data differs from traditional data gathering due to that it captures, manages, and processes the data with low-latency. It also one or more of the listed characteristics: high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, web, and social media which much of it is generated in real time and in a very large scale.”(IBM) In other words, companies moving towards big data analytics are able to see faster results but it continues to reach exceptional levels moving faster than the average person can maintain.
Before I entered college, I already had an idea of what I want to study and pursue in my future. In Middle school, I found Math and Geometry incredibly enjoyable, and I was always good at solving various quantitative problems. In High School I took my first economics class, and I could not find anything more interesting and engaging than this subject. Enjoying quantitative courses in school and having many family members working in the business field, I made a decision to pursue my higher education in economics and business and I could not see myself in any other field. At Cornell, Economics and Business Department offers a variety of majors with different concentrations. My deep interest in Business Analytics arose after I took my first
All companies obtain information on their customers or on their product. All these information may help a business to develop new strategies. They can also forge ahead by treating these big data. All companies have in their possession those information, so use it can be very useful. A company can identify for example their weaknesses and can improve their strategy to become the best on the market. It will help to create more opportunities for the company and maybe create a real competitive advantage.
Companies have transformed technology from a supporting tool into a strategic weapon. ”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.
Analytics means using data and performing statistical analysis on it, applying quantitative and predictive models, in order to arrive at a certain decision. Analytics can be the first step in a process or can rather be an intermediate step as well. Analysis can be done using different set of tools that are available in the market or it can done manually using different concept and formulas. Business intelligence firms like Cognos, SAS and BusinessObjects have developed different tools that are readily available in market that assist in analysis and decision making. Analytics is used in order to find solutions to the problems and the solutions provided enables us to be successful and in the business world allow us to compete with our contenders.
The dynamics of our society bring many challenges and opportunities to the business world. Within the last decade, hundreds of jobs have emerged particularly in the technology sector to help keep up with the ever-changing world and to compete on a larger and better scale than the competition. Two key job markets and the basis of this research paper are business intelligence or BI and data mining or DM. These two fields play a very important role in small to large companies and are becoming higher desired sectors within the back offices of the workplace. This paper will explore what the meaning of BI and DM really is, how they are used and what we can expect as workers and learners of the technology and business fields for the future.