Sunday, April 30, 2017

Future of big data “Everything is touched by data is going to be improving and is going to give a value”. 


Bid data is not big anymore. It is massive, huge, and mammoth. Future of big data will be all about developing technology to manage and more specifically to analyze big data. We all know that information and data are the basis of any commercial enterprise, and it is crucial to know how to get value out of big data and how to turn volume into value.  There is no way that data will stop be generated. Data will still grow larger and faster as long as mobile and internet devices are expected to grow in the coming years.

In the future of big data, we hope that machine learning will assist in data preparation and predictive analysis. Organizations will be no longer focus on analytics tools. Instead, they will put emphasis on machine learning to take a step further in analyzing data and predict insights for making business decisions. Data as a service is expecting to be popular in the future. Organizations will attempt to analyze their data for business insights in order to monetize their data.

Algorithm market will increase. Organizations will try all the possible ways to make analyzing data easier. Businesses would purchase algorithms instead of programming them and adding their own data. Therefore, algorithm markets will cater to this need.

In the future, all businesses are going to understand how they can become a platform for the collection and the analysis of data. They will be optimizing everything people do on society by collecting more information and learn from it. Every data generated by the internet users or any connected devices will be collected because there will be a value in this data that is linked to a new economic input or a new approach to business. Everything is touched by data is going to be improving and is going to give a value.

In terms of medical industry, the future of big data is promising in improving personalized medicine. Sam Madsen explained that when he said, by looking at the unique say a genetic makeup of each individual, we can understand the treatments that are going to be most effective for each individual. That can be done by comparing, for example, your genetics to every other person who has come into the hospital and received treatments and finding the once that is similar to your genetic. Moreover, by finding the medicine that has been the most effective for that person that his or her genetic is similar to yours, we may be able to personalize the delivery of the medicine for you in the future.

Big data is going to get bigger than it is today, and companies must start thinking about how they can embrace it Robert J. Abate when he said in his article 25 predictions about the future of big data that data is going to become the next global currency and is already being globally monetized by corporations.
if they do not. Companies that use big data and learn from their data to predict the future of their business will find themselves at the top level in the industries comparing to companies that do not empower their data will find themselves far behind everyone else.


 Every time we use the internet and sign up for a website’s feeds we give data about us, and this data is going to be collected and analyzed for better use if the website in the future. Again the idea of big data in the future is how turn volume into value.  

Monday, April 24, 2017

Is personalization the new content marketing trend for 2017?


What is personalized content marketing?
Personalized content marketing is the process of using consumers’ data to personalize messages targeting them on different platforms. Marketers believe that personalized content brings more consumers’ engagement. According to Kimberlee MorrisonWhen marketers take advantage of the data they collect, personalized messaging can yield big rewards when it comes to conversion and engagement”.
“74% of customers get frustrated with websites when content appears to have nothing to do with their interests”
However, personalization is more than just adding the person's’ name or the company’s name through email marketing. The new trend of personalization is more about personalizing content not just to the audience or devices they are using but also to the stage that they are at in their buying journey. 73 percent of global marketers believe they must deliver a personalized experience to be successful. Marketers will put a lot of effort to be able to send personalized content to the right person at the right time with the right content.
Understanding and analyzing the consumers’ data and their buying behavior will be the key factor to achieve a great personalized content marketing for 2017.  Again personalized content is not just about adding the consumer's’ name but also suggesting products that they are really looking for based on their buying journey.  
Who is the winner Snapchat stories or Instagram stories?



It is clear now that most social media channels starting to launch story feature among their own apps which obviously puts Snapchat in danger. 78% of millennials said they use Snapchat every day. However, after Instagram launched its story feature in 2016, it is reported that 200 Million users use Instagram story every day which is more than what Snapchat reported. Snapchat reported that 150 Million users use Snapchat of 2016.

A lot of people use Snapchat and Instagram stories at the same time especially influencers and advertisers. It is expected that one day those who use Snapchat and Instagram together will make a decision about which app they will be using. But, the question here is that, which app are they going to choose? Cathey Boyle from eMarketer reasonably answered this question, she said: “If Instagram already has a strong foothold in key advertising markets worldwide and the adoption of Stories continues to grow among that user base, that will make it harder for Snapchat to differentiate itself and attract users in those markets,”.

Therefore, the winner is going to be the one that has a huge user base of people.

Sunday, April 23, 2017


8 Most Popular Data Analytics Tools.

What is data analytics: Capella University defined data analytics as the science of collecting, organizing, and analyzing very large sets of data in order to identify patterns and draw conclusions. In other words, business users use quantitative and qualitative tools to enhance their ability to make precise business decisions and improve productivity.
Why you need to use data analytics tools:
  1. business analytics tools will enhance analyzing big data.
  2. Simplifying data and convert it into actionable information that can help organizations to achieve their goals such as growing revenue and increasing profitability.
Data analytics tools have been around to meet the expanding needs of businesses of all sizes and industries.
Here are the most common data analytics tools:
1. Tableau Public: It is one of the most popular free tools to analyze data. It allows you visualize data and share it with others in a way they can understand it. Tableau Public offers two services for free which are Tableau Public and Tableau Reader.
2. OpenRefine: OpenRefine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it; transforming it from one format into another, and extending it with web services and external data.
3. KNIME: one of the data tools that allow you fast and easy access to your data and help your organization drive innovations. “Our KNIME Analytics Platform is the leading open solution for data-driven innovation, designed for discovering the potential hidden in data, mining for fresh insights, or predicting new futures”.
4. Rapidminer: is also one of the data tools that will make your data analysts more productive through a unified platform for machine learning procedures and data mining including data visualization, processing, statistical modeling, deployment, evaluation, and predictive analytics.
5. Google fusion tables is a popular free data tool that works more with merging data from multiple tables and conduct details discussions about the data and also it works with visualizing data on maps.  
6. Nodexl: NodeXL Basic is a free, open-source template for Microsoft® Excel® 2007, 2010, 2013 and 2016 that makes it easy to explore network graphs.  With NodeXL, you can enter a network edge list in a worksheet.
7. SAS: Is one of the most powerful data analytics tools. SAS will help visualize your data and make them in a format that is easy to understand and will enable you to tell a story with your data.
8. Dataiku DSS is a collaborative data science software that allows multiple users work on the same project together. Dataiku thinks of collaboration in two ways Synchronous collaboration and Asynchronous collaboration. Synchronous collaboration multiple people work on the same project at the same time. Asynchronous collaboration multiple people work together but not on the same project and at the same time. This video will explain more how Synchronous collaboration and Asynchronous collaboration are used:

All these data analytics tools will help you analyze data and provide answers to questions regarding your company’s performance and improvement. You also need to know the basic data analytics technique as a data scientist beside those data analytics tools. Data analytics techniques require a high understanding of statistical techniques such as understanding the correlation between two variables in a large database. You need to understand the data analytics techniques so you become able to analyze data and predict actionable information that can be used for achieving companies goals.
Reference:

Sunday, April 16, 2017

How content marketing benefits your brand.

Content marketing is defined as distributing valuable and relevant content to attract your target audience and ultimately to drive them to take a profitable action. Companies start using content marketing to build their brand credibility and therefore increase their consumer loyalty. Here is a great example of content marketing in building a brand's credibility:  

 

Content marketing will drive more traffic to your website as long as you provide valuable content to your target audience. There are many content marketing tools that companies use, but you should consider the most effective one that is tied to your marketing objectives.

Also, companies can distribute valuable content on their social media channels, and this content can be linked to their website to increase the traffic. Content marketing has been used to educate new consumers about the products and services a company is offering. Word-of-mouth has been a powerful impact on consumers’ purchase decisions. 82%of American still looking for recommendations before they make a purchase. That means if you provide valuable content on your social media channels instead of pushing a product, people will interact with this content, type comment about their opinions, share their experience, and have the pleasure to share it with others.     
Why companies use content marketing.

Companies have to deliver content to their audience when they want it, how they want it, and where they want it. There are many reasons why companies use content marketing but main five are:
  1. To educate- companies use content to educate their target audience about their services and products. This purpose is usually used by new companies or businesses so they can increase their brand awareness.  
  2. To entertain- the main purpose of entertaining content is emotional. Companies can use entertaining content to entertain the audience and make them want to share this content with others. This will increase the brand popularity.   
  3. To increase sale- content marketing affects consumers’ purchase decisions. 78 percent of people say that a company’s social media posts impact their purchase decision.
  4. To persuade- in this stage consumers want to know why they should buy your product. They want to be educated consumers about your products and services and how it will benefit them. Try to find the best way to persuade them in educational tone.  
  5. To improve services- companies provide content on their social media channels and open a line of communication with their audience to use their comments and opinions in improving their services for the future.    
How to monetize data and How it works.
prd3.jpg
Data monetization has been used to improve a company’s revenue. It works with a lot of data that is called big data. Big data is information that a company has gathered through its business practices. This information will tell a story at the end, so the more information your company gather, the clear and correct the story will become. Monetizing data helps companies see things in completely new perspectives by analyzing the smallest details and turning it into the broadest frame of understanding.     
Why Companies use data monetization.
Companies use data monetization to enhance their revenue in different ways.
First, improving the internal business environment: companies use consumers’ data to enhance consumers’ experience, service and product quality, increase product and services innovations, and increase sell opportunities. In addition to that, companies use sentiment data related to consumers’ behavior on social media channels to facilitate targeting them through more engageable content. With data based on consumer insights and precise business decisions, companies will deliver more valuable services and satisfied customers’ demands.Pattern_user-data-monetization.jpg
Second, using data to make money: companies sell their consumers’ data to generate new revenues for the company. Companies can invest their consumers’ data if this data is consistent with the full conditions of credibility and accuracy. If your company owns consumers’ data such as their buying habits, products feature they are looking for, and what they are interested in buying, you can sell this data to other partners and increase your revenue.
However, This article is not only about big data and why to use it, but also is about learning how to sort and monetize data instead of being crammed somewhere.
How to turn data into dollars?
  1. Ask the right questions.
Start with asking questions related to your company performance and things you want to change or to improve, and try to find sufficient data to answer those questions. If data you collected did not answer those questions or did not help you to come up with the right decisions, then your data is completely inaccurate and insufficient.
2. Understand your consumers.
You should deeply understand your consumers’ needs and preferences because this will be a key factor in enhancing products and services, and therefore filling your consumers' unmet needs.   
3. Sophisticated information technology infrastructure.
Traditional tools of analyzing data are no longer work with big data because of its size. Therefore, make sure that your company is using information technology that is sophisticated,so you do not lose the value of your data and your consumers’ data privacy. Paule Blase mentioned this in her article “ How Businesses Are Transforming Revenue Models by Monetizing—and Protecting—Customer Data”
”It’s clear that businesses will be unable to generate new revenue from data sources without leading-edge data management and analytics capabilities—and data-privacy processes that underpin customer trust”.

 Finally, data monetization is all about using data and transforming it into currency by deeply understanding your consumers’ and your company’s performance. Identifying your target consumer's needs, requirements, and desires will help you effectively map your data and make changes to the way you do your business. 
Try to choose the right business model to monetize your data, and think about improving your current business and offering new products and services. You should never underestimate the power of data monetization in improving your revenue through increasing your business opportunities in online space.
sufficiently, this data coming from marketing analytics will show you social media channels which your target audience are active on. In addition, this data will facilitate targeting them, and providing content that will make them engage with your social media platforms and your brand. So, all data that you monetize will turn at the end into profits.