How Facebook and Instagram Algorithms Work

In 2014, Mark Zuckerberg, CEO of Facebook, said that the main focus of the network is to become a "personalized newspaper for each person." Therefore, Facebook is constantly learning about the behavior of its users, seeking to empower them to come up with the definition of what actions define whether content is interesting or not. The goal is to keep visitors for longer on the social network, interacting with as many publications as possible.

The “like” button, implemented in 2007 - three years after the launch of the social network - was the first significant change in the algorithm aimed at mapping the level of relevance of content to users. The strategy developed until, in 2016, the reactions were launched, other buttons that aim to go beyond the approval of a publication: they seek to measure the engagement it generates, receiving positive and negative feedback.

Two of the aspects that guide this analysis are:

1. Origin of the publication

By 2015, after concluding that its users were very concerned about losing updates from their closest friends through news feed information, Facebook's algorithm allowed them to choose which pages or people they'd like to see the updates first. Before that there were only filters for what people did not want to see, with the option to hide posts and unfollow. Relevance of content and engagement with other users or pages was measured by tastings, shares and comments. At this point, the News Feed Preferences were launched to empower them in this choice.

2. Relevance of the publication

Based on the history of interactions, the Facebook algorithm can predict when a publication will be tanned, clicked, commented or marked as spam. The combination of variables creates the relevance score, which organizes the order in which the posts will appear for each user. The first that appears will therefore be the most capable of engaging at that moment. This calculation is always fed by positive and negative feedbacks. The same logic is used with Facebook Ads. If ads are expected to improve users' social network experience, the relevance score contributes to the identification of the target audience for companies that use that attraction strategy.

The Instagram Feed Algorithm

By the year 2014, Instagram had no algorithm that individually monitors users' activities for suggestion of photos in its "explore" tab. There, the most popular publications were shown among all users, without any specific guidance. In addition, the timeline showed the publications in chronological order, regardless of their relevancy. However, when acquired by Facebook, Instagram started to focus on improving the user experience, since it was estimated that they did not see 70% of the photos of their feeds in their visits to the social network. From the new algorithm, the order of publications in the Instagram feed is defined by the following factors:

- Number of likes and comments to measure engagement;

- Level of user interaction of the post source;

- Publication time, so the social network does not lose the chronological characteristic of the visualization;

- To whom the user sends direct messages and what type of content shared with these people.

Social Media Algorithm: How to Be Successful With It?

Of the largest social networks, the ones we know using algorithms are:

Facebook, Twitter, Instagram, Pinterest.

If a social network grows so much, it will begin to adopt a content algorithm. But what do social networks gain from it? Many are justified by bringing up the discussion about the user experience on the network.

Ad Profits

This first motive is the most remarkable. With organic reach declining, brands need to increasingly invest in ad platforms within social networks to be noticed by the crowd. The result we already know: the more investment in ads, the more profit for the platform. This is not to say that these social networks are villains. We can`t forget that they are also businesses and businesses need money to survive in the market.

The future of social networking for business shows more and more this increase in the use of ads to reach its audience. This is not the end of the world. Social networks are extremely competitive and one benefit of the ads is to reach exactly your persona and not any online user. The important thing is to know how to use these tools so you do not waste budget with something without results.

We all remember what happened to Orkut. The network gradually lost users until it died. The lesson we have is that a social network can`t survive without an audience. According to the social networks themselves, these algorithms seek to improve the user experience within the site by showing only content that would be interesting, so that they do not get annoyed by spending time looking at bad content and of little relevance to it. By improving the user experience on the network, they increase the time spent on the site and ensure that the audience does not leave the social network.

Facebook and Instagram are the best examples of this. Facebook, in the beginning, was just a content-sharing network. Gradually it has been adapting and now you can post videos, news and do livestreams with Facebook Live, all without having to leave the site.

Instagram is going the same way with the Instagram Stories, increasing its functionality so that users stay more and more inside the site without abandoning it to use other social networks. This is to centralize content distribution channels on a single platform.

What does this have to do with algorithms? Algorithms increase a user's downtime on the network and make creators more and more invest in relevant content within the social network to get people's attention. And one way to get that attention is to use the various features of the social network. Facebook, for example, prioritizes videos that are posted within the site, rather than videos shared by a Youtube link.

How to succeed in this reality? The algorithms do not go away. It is your responsibility as a brand or as a marketer to adapt to this reality and invest in alternatives to overcome this challenge.

Some tips that will help you in this:

- Create extraordinary content. Yes I know. You've heard this tip hundreds of times.

Engagement: with the algorithms, engagement is the most important metric for you. It will dictate whether your content will be displayed to users. So, as cliché as this advice sounds, it is the truest truth.

- Extraordinary content is content that will grab the attention of your audience and engender engagement - driving you out in front of other competitors.

- Research and understand what your audience is consuming. This is what will guide you to produce content of value to it.

- Choose your channel well and have a strategy.

- It's better to be an expert and have amazing results with just one channel than being median on multiple channels. It is better to have a consolidated strategy on Instagram, for example, than to constantly strive for the attention of the user on Facebook. It is very important that you understand well who uses each social network, what kind of content is consumed in there and what your goals are as a brand when using that social network.

With all of this in mind, you can create an effective social networking strategy that you choose for your business. The golden rule here is: do not shoot everywhere!

Although the three social networks have responded in different ways to the need to create more complex algorithms for the development of their users' experience in terms of Digital Marketing, these modifications lead to the same conclusion: the quality of content and advertising will be decisive for the organic reach and paid within the social networks. As important as recognizing good marketing strategies, minimizing the spread of low quality content and information is critical to retaining users on social networks. The algorithms are, after all, an incentive to good practices of target audience segmentation and the creation of campaigns and relevant content, essential for ensuring good results with Digital Marketing.

Many companies are desperate to realize that the organic reach of their content on social networks falls every day. Look at algorithms and changes as a chance to grow, experiment and connect more with your audience. They are not the apocalypse: they are an opportunity. Whoever is able to adapt to this and succeed is not forgotten in the future. 

Research, understand all about it and good luck!

What are social networking algorithms and how do they work?

2.34 billion people around the world use social networks, according to the Statist. The forecast is that by 2020 this number reaches almost 3 billion users, which is half of the world’s population. This number is very important and tells us a lot about the path we are going when we talk about internet and connectivity. There is no doubt that, along with Google, social networks were one of the greatest inventions of the internet. Everybody uses, all the time - they've become part of our routine. And the reason is one: with so many users on the network, it is inevitable that today's biggest social networks will create new ways to enhance the user experience (and obviously increase their profits). And that's where the subject of this text comes in: the algorithms of social networks.

Social networking algorithms are a controversial subject. A social network algorithm, in general terms, is a formula for prioritizing posts on social networks according to relevance to the user, abandoning the idea of ​​showing only more recent posts. Want to see your algorithm on Facebook in action?  Just watch your news feed in "Top Stories" mode. There, you can see exactly what content Facebook considers relevant to you. The algorithms basically have 3 rules:

1-    Who posted the content? That is, what is User Interaction with content (if you have previously commented, liked, or shared posts from a page / user)

2-    Content popularity (yes, content with more engagement has more priority in the news feed)

3-    Content type (photos and videos are more likely to appear in the news feed)

With this data in hand, social networks that use algorithms define which content will first be shown to the user.

Exploring Google Analytics For Your Online Store

Google Analytics allows you to extract data and relevant information to understand more about the consumer. With it, you can identify issues such as traffic origin, age and sex of customers, session time, and number of unique and recurring visitors, conversion rate and more. In addition, it is possible to go further and know how many pages have been visited, what the bounce rate is and what type of search has made the user reach the store. This information is available on topics in the dashboard and divided according to the highest occurrences. In addition, you can cross-reference different data, such as joining two metrics. By crossing the age of the buyer with the source of the traffic, for example, you can determine that the younger ones come, for the most part, from smartphones. So you can focus on promoting a particular product to the mobile. Google Analytics goes into history by allowing the complete and accurate measurement of the results, allowing you to identify the best features in each scenario. Fortunately, in Google Analytics this task is very simple and you can employ predefined goals to understand whether the test was a success or not. With the tool, you can make small changes both on the home page and on specific pages of products, aiming to increase the time of permanence, conversion or any other desired result. The test configuration is quite wide and you can do it with only one or several variables. From there, just follow the results offered by the tool itself. If you have an e-commerce, Google Analytics is an indispensable tool when it comes to monitoring the results and creating a more appropriate consumer profile. From its proper configuration, it is possible to extract the maximum potential of the tool, taking your virtual store to a successful path. 

How To Use the Privileges of Google Analytics on Your E-Commerce Site

Google Analytics is one of the most valuable features for any online business and with online stores it's no different. It is able to monitor from consumer profile characteristics to the way your customer acts. From the results it is possible to understand the strengths and weaknesses of the business in order to work to get more customers and sales. However, to fight the monster of the abandoned cart, everything must be configured correctly. Here, I’ll tell you how to use it, making the most of Google Analytics for e-commerce. Check it out!

How to create an account?

To use Google Analytics in an e-commerce, the first step is to create a (free) account, which must be linked to the Google AdWords account, if the store uses the sponsored links. It is highly recommended to do this integration, even if you have not yet announced it on Google, since in the future the business will be able to use AdWords without having to redo the process. In the part of creation and configuration of the account it is necessary to specify the destination page, but the most important moment is to configure it for e-commerce. While regular sites jump right to the code, an online store needs to report its activity to Google so that the algorithm can properly calculate the purchasing model.

Once the registration and configuration are done, it is necessary to copy the Javascript code and paste it into the code of your site. Thus, Google Analytics will be able to monitor all the information of who arrives to the site and makes purchases in general way.

How to make the best configuration?

Google Analytics provides valuable insight into customer behavior for an e-commerce. At the same time, not all the data obtained will be useful and a basic configuration will not meet the purposes of your business precisely because it is not customized. Therefore, it is important to properly configure this tool and this includes points such as:

Currency and Freight

Identifying transaction currency is not a must, but it will make it much easier for you to analyze the results. So when it's time to set up, it's worth stipulating the type of currency used in your transactions so that the record happens properly. Talking about freight is also not required, but it helps your results evaluation process.

Conversion Funnel

It is also important to set conversion goals, which are not always tied to the sales itself. Depending on your need, you can configure access to a particular page as a conversion. This type of configuration regarding the funnel is important to understand where customers are having difficulty completing the purchase. If you indicate that people are stopping the buying process in the calculation of freight, for example, it may be a sign that the value is high and unattractive.

Site search

Google Analytics also allows you to collect data related to searches within the e-commerce site. So you can know which are the most sought after products and what kind of behavior a particular customer has. This type of information can be important in increasing business intelligence so as to offer more accurately related offers. After all, it can be a source of ideas for varying the product mix. If a customer who purchased an item looks for another that is not available in the store and this is a recurring stock, there is an indication of a market opportunity being wasted.

Remarketing

Google Analytics for e-commerce still offers the ability to capture visitor data to enable remarketing. It works like this: the customer enters your site and leaves a "trail" of digital data. When it is off your site it will see offers and information related to what you were visiting before, increasing the chances that it will actually make the purchase.

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!