The Importance of Google Analytics on E-Commerce

Google Analytics is a valuable ally of e-commerce in the battle for consumer money. It gives you rich information about your site, your visitors and where they came from. All of this information can be used to find new customers and increase conversions. For many e-commerce owners who are just starting out, Google Analytics may seem like a big mess of technical reports with information difficult to understand and navigate.

How to set up Google Analytics in your store? What are the basic reports you should always be checking?

These are important things to know as well as a few other little things that will help you improve your knowledge and drive sales.

Why do you need Google Analytics?

If you have a physical store, you can see your customer. You can notice their habits and habits and talk to them. Without e-commerce analytics (as we'll now call Google Analytics in your e-commerce), a virtual store leaves you blind about so much information about your customers and visitors that you would normally be able to see. Using Google Analytics can help you improve the understanding and effectiveness of your marketing campaigns, better understand your visitors, and optimize your store for conversions and sales.

Configuring the tracking of Google Analytics e-commerce:

Google Analytics is pretty easy to set up, but the exact steps will depend on your e-commerce platform. Whether you use Santive Commerce or OpenCart is very simple. Just create an account in Google Analytics, copy the tracking and paste in the corresponding field in the configuration area of ​​your store.

Cloud Computing

A project under development with a semiconductor manufacturing company can monitor the detection and classification of failures in real time. With stream computing, failures in chips being manufactured are detected in minutes rather than hours or even weeks. Defective wafers can be reprocessed and, more importantly, adjustments can be made in the manufacturing processes themselves, in production.

Additionally, we may think that cloud computing is also a booster for Big Data because public clouds can be used to support huge amounts of data. The cloud's elasticity characteristics allow us to power virtual servers on demand only at the time of processing these data.

Anyway, Big Data is knocking on our doors. Its potential is not yet fully recognized, but we already see clear signs of this importance to solve diverse problems such as socioeconomic issues and even epidemic prevention.

As for companies, Big Data opens up a new and still unexplored territory. We lack knowledge, experience and even professional expertise. It starts talking about new functions as data scientists, but it is inevitable that the CIOs have to put Big Data on the screen of their radars.

The opportunities that the five "V" s bring can not and should not be wasted.

The other day I wrote a post with a simple formula to conceptualize Big Data. It is equal to volume + variety + velocity. But I usually add two more V's to this equation: veracity and value. Let's detail these topics a bit more.

Volume is clear. We generate petabytes of data every day. It is estimated that this volume doubles every 18 months. Variety also, since these data comes from structured (now minority) and unstructured systems (the vast majority), generated by emails, social media (Facebook, Twitter, YouTube and others), electronic documents, Powerpoint presentations, instant messages, sensors , RFID tags, video cameras, etc.

A Summary in Big Data

The term Big Data is increasingly popular, although it is still misunderstood. I observe in many lectures that there is no consensus as to what Big Data really is. And there are still many questions about how to make the concept tangible, that is, how to get out of the concept and create business solutions that add value to the companies. Eliminating these doubts is essential, as well as being the first step for companies venturing into Big Data projects.

To put the term in context, Big Data has been drawing attention to the accelerating scale at which ever larger volumes of data are created by society. We have already talked about petabytes of data generated each day and zetabytes starts to be a real scale, no longer imaginary and futuristic. What was the future a decade ago, terabytes, we already have in our own homes today.

The technologies that support Big Data can be analyzed from two perspectives: those involved with Analytics, Hadoop as the primary technology, and infrastructure technologies that store and process data petabytes. In this aspect, the NoSQL databases stand out.

Why these technologies? Why Big Data is the simple practical realization that the sheer volume of data generated each day exceeds the ability of today's technologies to treat them properly.

The 5 V's in Big Data

The proposal for a Big Data solution is to offer a consistent approach to addressing the constant growth and complexity of data. To do so, the concept considers the 5 V's of Big Data: Volume, Velocity, Variety, Veracity and Value.

Volume: The volume concept in Big Data is best evidenced by everyday facts: daily volume of exchange of emails, banking transactions, interactions in social networks, record of calls and data traffic in telephone lines. All these serve as starting points for understanding the volume of data present in the world today.

It is estimated that currently the total volume of data circulating on the Internet is 250 Exabytes per year. Every day 2.5 quintiles of bytes are created in data form, currently 90% of all data that is present in the world was created in the last 2 years (IBM). It is also important to understand that the concept of volume is relative to time variable, that is, what is great today, may be nothing tomorrow. In the 1990s, a Terabyte was considered Big Data. In 2015, we will have around the world approximately a volume of digital information of 8 Zettabytes, an infinitely greater value.

Velocity (Speed): Would you cross a blindfolded street if the last information you had was a photograph taken from traffic circulating 5 minutes ago? Probably not, because the 5 minute photo shoot is irrelevant, you need to know the current conditions to be able to cross the street safely. (Forbes, 2012) The same logic applies to companies as they need current data on their business, ie speed. According to Taurion (2014) the importance of speed is such that at some point there must be a tool capable of analyzing the data in real time. Currently, data are only analyzed after they are stored, but the time taken for storage itself already disqualifies this type of analysis as a 100% real-time analysis.

Information is power, and so the speed with which you get this information is a competitive advantage of companies. Speed ​​can limit the operation of many businesses, when we use the credit card for example, if we do not get a purchase approval in a few seconds we usually think of using another payment method. It is the operator losing a business opportunity by the failure in the speed of transmission and analysis of the data of the buyer.

Variety: Volume is just the beginning of the challenges of this new technology, if we have a huge amount of data, we also get the variety of them. Have you thought about the amount of information scattered in social networks? Facebook, Twitter and others have a vast and distinct field of information being offered in public at every second. We can observe the variety of data in emails, social networks, photographs, audios, telephones and credit cards. Whatever the discussion, we can get infinite views on it. Companies that can capture the variety, whether from sources or criteria, add value to the business. Big Data scales the variety of information in the following ways:

Structured data: are stored in databases, sequenced in tables;

Semi-structured data: follow heterogeneous patterns, are more difficult to identify because they can follow different patterns;

Unstructured Data: A mix of data with diverse sources such as images, audios and online documents.

Of these 3 categories, it is estimated that up to 90% of all data in the world is in the form of unstructured data.

Veracity: One in three leaders does not trust the data they receive. In order to reap good fruits from the Big Data process it is necessary to obtain true data, according to reality. The concept of velocity, already described, is well aligned with the concept of veracity by the constant need for real-time analysis, that is, of data that are consistent with the reality of that moment, since past data can not be considered true data for the moment Which is analyzed. The relevance of the data collected is as important as the first concept. The verification of the data collected for adequacy and relevance to the purpose of the analysis is a key point to obtain data that add value to the process.

Value: The greater the wealth of data, the more important it is to know the right questions at the beginning of the analysis process. It is necessary to be focused on the direction of the business, the value that the collection and analysis of the data will bring to the business. It is not feasible to complete the entire Big Data process if you do not have questions that help the business realistically. In the same way it is important to be aware of the costs involved.

Visual Appealing Data Visualization: It's All About a Good Storytelling

Infographics and visualizations of data have become essential for journalism with the emergence of digital media, where large volumes of data need to be interpreted and communicated simply to the audience. To explore the potential of online news, more and more journalists and professionals of the area are willing to learn how to build their own interactive graphics and illustrate their stories, a task previously restricted to designers. The tools mentioned on the previous post are a great resource for professionals who don’t know how to work on InDesign and Illustrator, which are usually used by designers. It doesn’t matter how you will display data, but the storytelling has to be very clear. The tools mentioned previously were great examples (Infogr.am, Easel.ly, Tableau, Timeline and Mapbox) and they help professionals to do that.

As I designer, I got to design many infographics, but there is a specific one I have designed that serves as a good example of how “boring” data can look fun. Once I designed an infographic for a Fortune 500 software company that builds mainframes for companies such as IBM. They had just launched a security software for mainframes and they wanted to create an infographic saying information about data loss and hacking that happens in many business because companies don’t protect their mainframe. Ok, you probably got lost on the first sentence, right? Anyways, I was assigned to design this infographic that displayed stats about the topic to help selling the software. Check it out below.

It doesn’t sound that boring, right?

After the success of the infographic, the company asked me to create an animated video of that infographic, which can be watched here.

Tools for Data Visualization

Below are some data visualization tools for presentations and developers, which will make it a cinch for users to understand their numbers and turn their static data into a visual feast for the eyes.

1.     Infogr.am

This tool is a find for anyone crafting professional graphic design programs. It offers six themes (layouts) and 14 types of graphics (bars, pizzas, lines, among others) to build interactive visualizations. To avoid getting lost in the options, just remember that the choice of elements must take into account what will be represented (functionality). For example, bars are usually better than circles for more accurate. When editing the chart, include the data that will be illustrated or import a ready-made worksheet. After all the adjustments, just publish and publicize your project or incorporate it to your site (by copying and pasting the HTML code of the embed).

2. Easel.ly

This online infographic creation service (still in beta) is super intuitive and offers some features that we did not find in the previous tool, such as the flexibility to freely organize the grid and restructure the pre-defined themes. There are 15 themes available, but the service promises others soon. In the editing screen, features such as backgrounds, shapes and text are activated by drag-and-drop. It is possible to change the color and change the position of the elements, write texts, change the background, insert shapes (arrows, circles, balloons) and even upload images of files from the computer.

3 - Tableau Public

More complex than previous tools, Tableau Public is an interactive data visualization program that also does not require programming skills, but requires a good understanding of the organization of databases and chart formats. After downloading and installing the program, the first step is to insert data from text files, Excel spreadsheets or Access databases into the editing area. If the file you choose is formatted and organized correctly, the data is automatically separated and you can drag it to the column and line spaces to form the graphics. There is a wide range of editing features and it is possible to join tables and graphs to build more complex visualizations. The site offers tutorials and training for anyone who wants to explore the features of the program.

4 - TimelineJS

TimelineJS is very useful for providing context and creating temporal narratives, so they are among the most common infographics in news vehicles. No registration is required to access the resource, but you need to have an account with Google because the preview entries are made to a preformatted worksheet that's stored in Google Drive. To get it, simply click on "Google Doc Template" after accessing the "File Formats" link in the main menu of the site.

5. Mapbox

This tool allows even users with no experience in data georeferencing to build custom and interactive maps. After logging in to the site and clicking "new map", the only job is to add the information in the bookmarks (title and content) and position them on the map. There is a search field that helps you locate specific points such as neighborhoods, rivers and roads. Once you've placed all your bookmarks, just publish. In fact, the publishing feature allows you to not only copy the embed HTML or the map url ready, but also integrate it into a more advanced version for those with more developer spirit. On the other hand, this version does not allow the import of a data sheet, which can make the task of presenting a large volume of information difficult. Also, you can prepare maps from extensive databases, but you need to add columns with the geographic coordinates and understand (at least the basics) of CSS.

Source: Design Tools For Data Visualization
14 Best Data Visualization Tools 

All About Making it Visual Appealing

As a graphic designer, I like to see things on my day-by-day that are nicely done and designed. It doesn’t matter what the content is, I give extra value to what was well designed and thought through. Something that has gotten very popular in the past years is infographics, which most of the times have boring information or complicated stats, but when are well done, they are very enjoyable to understand.  Data is something people tend to run away from, but its visualization is based on several of the same principles of web design, which should be useful and enjoyable.

A nice website naturally appeals to us, but it is when we extract some value from it that we decided to stay there (not just go through it). The same rules apply to data visualization: it's about presenting all of our data in a way that is easy to understand and intuitive to navigate - interaction is the key.

We gather more and more information every day, and this has led to the incredible popularity of infographics - an easy way to "digest" numbers that, without a graphical representation, just seem blank. Since our brains are capable of processing images at a faster rate than they process numbers, all content on websites and infographics is becoming more and more visually "data-driven", and tables, pie charts and bar charts are now common elements for every graphic designer.

And the deal is this:

If you want to create awesome data visualizations, but you are not a graphic designer like me, see some recommendations on my next post!