Social Analytics

By Ibrahim M.

Social Analytics is the process of collecting and analysis of statistical, digital day on how users interact with organization, practically online usage. Business use this analytics to see who their customers are and what they are doing on their website or social media site. There are many benefits on social analytics. According to Steve Hamby , there are 5 reasons why Social Analytics is a good thing. These reasons are, read more...

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Mobile Analytics with Websites, and Applications

By Aaron L.

In today’s growing age of technology, there are more smart mobile devices than there are human beings. According to GSMA Intelligence, there are currently over seven billion SIM cards that are active in the world (Mack, 2014). People use smart devices in their day to day lives to conduct banking, perform business transactions, and even entertainment. The prolific use of massive amounts of smart devices generates an immense volume of data, commonly known as big data. Big data is valuable especially to corporations, and enterprises, because big data contains consumer’s information. Big data could potentially explain a consumer’s spending habits, interests, hobbies, career, and other personal characteristics. Big data in itself is useless however, because it is just raw data, but that is where mobile analytics comes into play. Mobile analytics is the study of data specifically created from mobile devices. The source of data usually stems from traffic on mobile websites, or mobile apps. The importance of mobile analytics is on the rise, because the future is heading towards mobile devices. The use of mobile analytics can improve a company’s business model by analyzing data, and then altering the company’s mobile applications based on the data.
A company’s mobile website is one of the main mobile applications that can be greatly affected by mobile analytics. A company’s website can be thought of as the digital representation of a company, where consumers can intimately perform business transactions online. If consumers are dissatisfied with the company’s mobile website experience, then they are likely to not conduct business. Mobile analytics can identify the weaknesses of a mobile website, and the company can make the appropriate improvements. Weaknesses in mobile websites found using mobile analytics require tools and software, such as Google Analytics, to perform a data analysis. Mobile analytics can reveal a varying degree of information about the consumer, so that the company can make changes to the mobile website. For example, mobile analytics can reveal the type of device, and operating system consumers are using when visiting the mobile website. If the analysis reveals that there are less consumers using Android devices when visiting a company’s mobile website, then it could be an indication that the mobile website may not be optimized for Android devices. Another consumer characteristic that mobile analytics can identify is where the majority of consumers visiting a mobile website are from. By identifying what country, a mobile website receives the most traffic from, the company may update the mobile website with different language preferences. Changes to the mobile website can bring more traffic, and in turn generate more revenue.
Mobile apps found on Google Playstore, and Apple’s App Store are key subjects when involving mobile analytics. The reason mobile apps are subject to scrutiny within mobile analytics is because mobile apps are a billion-dollar industry. Most of the revenue results from the mobile gaming industry. In 2015, the mobile gaming industry made twenty-nine billion dollars, and is estimated to go as high as forty-nine billion dollars by 2018 (Day, 2016). Much like mobile web analytics, mobile apps analytics studies consumer data for patterns and trends in order to improve business model. Mobile gaming is relatively new, but mobile analytics has already identified important features that will maximize the return on investment on a consumer. Important features to include in a mobile game to maximize return on investment is multiplayer capabilities using a free to play model. Now that a standard for mobile gaming industry is out, companies need to use mobile analytics to gain competitive advantage in the industry.
Mainstream technology is shifting towards mobile devices. With the shift of focus towards mobile devices comes business opportunities. Companies creating mobile website for e-commerce, or developing mobile games generates an abundance of data. Fortunately, mobile analytics exists so that big data can be interpreted into meaningful data. Mobile analytics is used to study consumer data on their mobile devices, so that companies can better improve their mobile applications. With the betterment of a company’s mobile application comes an increase in revenue channels. There are people that oppose mobile analytics however. Critics claim mobile analytics is an invasion of privacy. A survey conducted by TRUSTe, a data privacy management company, showed that seventy-eight percent of smartphone users will not download an app they do not trust. (Professional Services Close-Up, 2013). Despite the critics claim of privacy, mobile analytics is the future of data analysis. read more...

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Future Decisions using Mobile Analytics

By Jimmy L.

Mobile analytics is usually split between mobile web and mobile applications. Mobile web refers to web pages being browsed by mobile devices like iPads, iPhones, tablets, or anything that uses a mobile browser. Mobile applications refer to applications on created for mobile devices. Using mobile analytics has become increasingly important because consumers have started using their mobile devices to browse the web more than their desktop or laptop. With consumers using their mobile devices more and more, it has become very important for businesses to analyze what they are doing, what they are looking at, and what they are buying. This allows business who use mobile applications or websites to market, advertise, or interact with their consumer base to see what is doing well, doing bad, and what they need to change to become more optimized.
Mobile traffic is only increasing as time goes on because the technology is becoming more and more accessible to everybody. Sean MacNeill states in the article, Openwave Launches Mobile Analytics Service, that “Business intelligence is the key element to monetizing the mobile internet.” By saying that better understanding mobile data, which can deliver critical information, will it be able to help generate higher revenue by knowing what the consumers want. This in turn can give provide information about the consumer such as what their current lifestyle is like, what their income is, and how much they are willing to spend.
Google Analytics is a free tool that can be used to analyze both mobile applications and mobile webpages. Google Analytics would be able to determine how long a user stays on a page, what they browsed at, if they created a new account, what device they used, where they are located at, etc. However, there is a problem with one feature of the free tool is that the, “Bounce Rate”, which determines if a user goes to that page, does not interact and immediately leaves without navigating it. The “Bounce Rate” is important because it can help give information about what is good or bad about the application or website. As stated by Jay Peyton in his article, What’s the Average Bounce Rate for a Website, that an excellent bounce rate is 26 to 40 percent, 41 to 55 percent is average, 56 to 70 percent is above average, and anything above 70 percent is bad. This can show that if the website has a high bounce rate then it is because the website is designed in an unappealing way or it could be compatibility issues. The way Google calculates the “Bounce Rate” is the percentage of single page view visits to a website. However, that doesn’t mean that it is all bad because if the website is only a single age website and the user finds what they need then leave doesn’t mean that the website was bad. Using the information that Google Analytics provides then the business can be located where their market base is or where it has yet to penetrate. It can also show how much in demand their website or application is in with unique page visits or new users amount.
Mobile devices are constantly growing and with the amount of time that is being spent on mobile device. Companies and businesses want to know how consumers are spending their time on these devices. With mobile analytics, they are able to manage and read the data. Companies and business can improve by seeing what part of their online presence is useless and replace it with something else that can bring in more revenue. read more...

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Web Analytics

By Janice K.

In today’s era, lots of businesses already have websites to promote their goods, or even allowing customers to buy their goods online. Having a website certainly helps giving additional, more detailed, information regarding the goods or the business itself. The website can, not only increase the number of customers, hence increasing profit, but it can also help business owners to see the number of people visiting and their activities while visiting. After obtaining data, owners can analyze it and use the analysis to help make decisions. The whole process is known as web analytics, which can be defined as “information technology tool that collects, stores, analyzes, and graphically presents data collected from websites” (Algalith, 2015). read more...

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Web Analytics

By Gavini K.

Web analytics plays a huge role in many different ways through today’s technology. It helps many industries like health, finance and business. Web analytics is the gathering of data through the web, and analyzing them and making predictions. “Using machine-learning algorithms, and artificial neural networks, Web analytics software finds useful hidden information and patterns in the data and uses them to form new rules and predict the future behavior of customers, turning that mountain of data “Big Data” into valuable knowledge and untapped business opportunities and to enhance customer experience management (CEM) and customer relationship management (CRM). Customer relationship management system is an information system that provides an integrated approach to all aspects of interaction a company has with its customers (Brown, 2012).” Web analytics has become a huge impact on the world, most importantly in business. It has given us so much information to which it has shown businesses a path to making the companies succeed and make the customer relationship strong. There are three examples that prove just this. read more...

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Future Business Decisions with Prescriptive Analytics

By Jerome F.

We live in an age where technology has far surpassed our expectations and has exponentially grown over the course of the past several decades. With these rapid technological advancements, it is has become more increasingly complex for organizations to examine data that will benefit their own business. Organizations remedy this issue by examining these raw data through the utilization of data analytics, a concept that is used by implementing three key ideas to create better efficient business decisions. Prescriptive analysis, the third and final phase in this process, wraps everything up and formulates recommended actions for organizations to move towards for desirable outcomes. read more...

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Business Intelligence & Descriptive Analytics

By Carlos A.

Business intelligence is the process in which a business collects data and information from its operations and environment to help make strategic decisions. Business intelligence includes many difference types of applications, systems, and tools that are used to collect data and give the data meaning. An important area of Business intelligence is descriptive analytics in which a company performs an analysis of data to gain insight into its business’s past performance (Bertolucci, 1). Descriptive analytics are a form of analytics that help describe what has happened in the past and make it easier to notice changes and trends in a business. read more...

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Problem Solving Using Descriptive Analytics

By Jeffrey A.

Descriptive analytics has to do very heavily with business intelligence. It is often considered the first step in gathering business intelligence because of its relation to big data, which is large collections of information gathered by corporations or other entities. This is often done for the purpose of developing reports or creating forecasts, but it is not possible without accurate and proper data collection methods. Other forms of analytics include predictive and inquisitive analytics that deal with different areas of analyzing data. Descriptive analytics is not to be confused with these though because they deal more with data after it has been organized and formatted. Descriptive analytics is the most important form of analysis when gathering business intelligence.
Descriptive analytics is very well described in an article by Bertolucci Big Data Analytics: Descriptive Vs. Predictive Vs. Prescriptive. Bertolucci defines descriptive analytics and its simplistic importance by saying “The purpose of descriptive analytics is to summarize what happened. Wu estimated that more than 80% of business analytics — most notably social analytics — are descriptive.” Not only is it the simplest but it is also the most basic and the other forms of analytics are vitally dependent on it. According to an article by Shankar V titled Business analytics driven students likings on social media there are many ways social media utilizes descriptive analytics. It is directly written “SNS contains exponential amount of user generated data which helps business analytics to analyze, summarize information for displaying proactive alerts in dashboards.” It gathers data through surveys or through monitoring habits of its users. Using this raw data, it can formulate specific advertisements for users that will appear on their webpages while they browse. It allows them a more responsive way to interact with users. It can also collect data on usage of certain web applications and can better help monitor for errors or malfunctions that could cause irritation for the user. Another article titled Big data in Government Services gives examples of how government agencies collect data and how they use it. The many uses include combatting terrorism and crime prevention by gathering data from convicts. “IBM has a big data analysis platform known as IMB Watson Foundation that has the capability to create solution of all data related to many government duties like threat prediction and protection, social program fraud, tax compliance, and crime prediction and prevention.” The IBM Watson Foundation provides a perfect example on what descriptive analytics can provide to the world. This massive collection of formulated data causes tremendous good, and it genuinely benefits the world.
Other forms of business intelligence are incredibly important, such as predictive analytics, inquisitive analytics, and prescriptive analytics. Each has an important part in gathering information for businesses, though they offer less importance in the big picture. Descriptive analytics allows businesses to firmly address the issues and the questions, and without a firm understanding other forms of analytics can do very little. It takes great understanding to make an informed decision and that is precisely what descriptive analytics specializes in.

Shankar, V. (2014). Business analytics driven students likings on social media. Advances in Management, 7(12), 22. read more...

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By Jose Y.

The vast amounts of information that our devices are gathering and generating has paved the way for big data. Companies like google that receive extreme amounts of data or tech startups that does not need a full blown database solution has pushed for a non relational type of implementation. There are differences in schema, cost and data models between both types of database. read more...

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Big Data in Agriculture

By Michael W.

The influence of Big Data has been felt in a variety of fields, but there is one that most people wouldn’t initially think of and that is agriculture. The current trend of Big Data has had such a huge impact in agriculture that it even goes by a different name known as precision farming. In this process, “real time and historically generated data is collected in structured and unstructured datasets” (Bendre 2015). Farmers are well versed in knowing the several factors that can affect their crops and livestock from producing the best results possible, but there is only so much they can do within a given time. This is why the effect of gathering useful data and analyzing it through the assistance of Information and Communication Technology (ICT) is crucial to maintain efficiency. With the help of this not only will farmers be able to make smarter decisions on what their next course of action should be but also how they will “figure out how to feed the 9 billion people that will be on this planet by 2050” (Gilpin 2014). The old methods used in agriculture used thus far will not be enough to solve issues of the future.
The Indian company, Chitale Dairy, has gone a similar route by increasing the overall quality of milk production from their cows by having Radio Frequency Identification tags (RFID) placed on each cow to transmit information to the cloud and mobile devices. In order for farmers to do everything that is instructed correctly, “the farm then sends a to-do list to farmers in their local language each morning on what each cow needs based on the data collected from the RFID signals” (Horowitz 2015). The execution of this allows farmers to do everything needed which will also inform them of any warning signs a cow may give off indicating illness.
Despite the clear positives of Big Data’s use, there are many issues that result from it as well. As with anything else involving technology, maintaining security is one of the top priorities for farmers. By having so many devices with special sensors attached to the transferring data to its respective cloud, it runs the risk of having valuable information accessed from a threat. As stated by one farmer, “the overwhelming fear is that it falls into the wrong hands, be it a neighbor, a seed retailer, a fertilizer company, or a big agriculture corporation. And then that data is used against the farmer by being sold to a competitor or undercutting a neighbor for a better deal on land prices” (Gilpin 2014). Another issue that needs to be addressed is how ethics is involved. As Dennis Ludena has stated in his work, due to the recent popularity of Big Data, a significant amount of people haven’t fully grasped the consequences of showing only portions of data that looks pleasing to other individuals after “cleaning” the data sets.
Being at the forefront of creating a greater yield of products consistently has been the driving force of using Big Data today and it will only continue to grow from here. Even though there are some clear problems dealing with the use of this valuable information once it is obtained, I strongly feel that it is the right way to go about solving pressing issues in agriculture. With the help of this, there can be a way for farmers to have a greater output with the same amount or maybe even less input. read more...

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Big Data on Customers

By Kyle W.

Big data is becoming much more common and popular in many industries. The last decade has seen a huge increase in the amount of data that is continuously being generated and collected in a rapid rate, creating pressure among businesses to stay competitive that has amplified to a whole new level. Due to this, companies understand that customers can be assisted through big data analytics. Not only does Big Data help companies stay competitive, but it also helps create better customer relationships and experiences. read more...

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