5 Incredible Examples of Visual Storytelling on Social Media

There’s a power in storytelling that compels us to continue to read, to buy a product, to be loyal to a brand. While slogans can be extremely powerful (just do it, anyone?), people today are becoming more visually oriented, and they need stories and images to get and keep them captivated. Below are some incredible examples of visual storytelling by some of the biggest names.

1. Acceptance: Airbnb2

Airbnb has done an amazing job of responding in real time to a few pressing issues. After renters went to social media to complain about being discriminated against by Airbnb hosts because of their race, Airbnb immediately apologized and enacted a series of anti-discrimination policies. As part of this effort, and in response to Donald Trump’s heavily criticized travel ban, the company ran a commercial during the superbowl to launch their #WeAccept campaign, which highlights people of different ages, races, and religions along with inspiring quotes. “No matter who you are, where you’re from, who you love, or who you worship, you deserve to belong,” says Airbnb CEO Brian Chesky. The combination of visuals of real people, along with short, personal text helps people to identify with and feel connected to the brand.

2. Giving Back: Heinz Ketchup

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Heinz consistently shows up as one of the best brands on social media. They’re funny and they do good. Check out their campaign to make the Monday after the Superbowl (Smunday) a national holiday (Heinz gave all their employees the day off). They received over 70,000 signatures on their online petition at Smunday.org, which they are sending to Congress! They also launched their “Selfie for Good” campaign, celebrating “Giving Tuesday”, where the company will donate up to $1.57 when users take a selfie with their Heinz Ketchup bottle at participating restaurants. As of the beginning of February, they had already reached their goal of donating $200,000 to Stop Hunger Now. Both campaigns speak to issues that are important to people, on a personal and a more global level. By giving back to the people, and encouraging them be an active part of their campaigns, people feel more connected to the brand and like they are a part of something bigger than themselves, which always inspires loyalty. Also…who doesn’t love ketchup!?

3. Rewarding Fans: Expedia

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It’s always nice when a company offers cash prizes to its users…especially when it’s user generated content (UGC). Instead of spending money on a campaign, the brand is connecting with users by asking them to send in their own photos and experiences.

4. Process + Awareness + Celebs: Google

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Google doesn’t really need to do much  marketing at this point (perhaps you’ve heard of the company?), but nonetheless, they like to keep their fans happy. One of the ways they do this is by giving their audience a peek into the inner workings of Google. In an effort to highlight the impact of climate change, Google recruited Game of Thrones actor Nikolaj Coster-Waldau to trek in southern Greenland to capture scenes of nature affected by climate change. Coster-Waldau is the first celebrity to be kitted out in Google’s Street View trekker backpack to collect imagery. This photo does a lot of things: It gives users a view into what it actually looks like when Google employees go out capturing street views; it brings a high-level of awareness to a serious, global problem, and it uses a celeb as the vehicle for the first two. Kudos, Google.

5. Humor Gets Them Every Time: Grammarly

With our 21st century stressed out lives, who doesn’t need a little giggle now and again? Grammarly, self-described as the world’s best grammar checker, does a great job at showcasing their services with funny (and sometimes cheeky) posts. By using humor and grammar, they are able to get their point across about what they do and why it’s important. It doesn’t get much better than that.

These are only a few examples of some amazing visual storytelling out there on the interwebs.

Here at DEEP, we investigate the world of knowledge visualization, so stay up to date with us as we share our findings!

Share your Experience

If you have any great examples of visual storytelling that  you’d like to share, let us know in the comments section!

 

AI for Beginners: We’re All Going to be Replaced by Robots (How AI and Machine Learning Can Shape the Future)

Do you keep hearing the phrase “AI” and wonder what it’s all about? Well if you need a crash course in AI (or machine learning, as it’s often called), we got you covered! So then…what do the self-driving Google car, Netflix recommendations and handwriting recognition software all have in common? They signal the eventual takeover of robots from humans (we kid!). They all use AI, or machine learning, which allows computers to identify patterns and operates under the theory that computers can learn without programming them for specific tasks. Scientists want to find out if computers could learn from data, therefore, the more data they are exposed to, the more they are able to adapt independently.

There has been a long standing quest to infuse intelligence into computers and machines in order to get them to work for us. Japan is currently planning a robotics revolution, envisioning a world where artificial intelligence is integrated into everyday life, helping with things such as carrying bags in airports, caring for the elderly, and ferrying us around in robot taxis. While some of us in the West may be seeing visions of Westworld or the Terminator, Japan (and many other countries) are embracing the integration of robots in society.

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In more and more cases, machine intelligence is becoming superior to human intelligence. Machines can assist humans in a variety of ways, and one reason for this is because machines are way more accurate than humans. Machine vision is better than human vision, self-driving cars are more secure than human driving cars (looking at accidents per mileage), as the robot vision system is much more accurate and predictable than human action. Machines are also not ruled by emotion, so they can always act clearly according to their programming. Of course this can have ethical and moral implications (should a self-driving car hit a child crossing the road if it can’t turn in time?). However, it seems as though we are increasingly able to outsource some of our tasks and brain power to robots and machines.

Boy in robot hat/mask, kid smiling in robot costume.

Now perhaps machines will be able to write our stories as well.  There has already a lot of experimentation in creating content by extracting data from images. Using something called “attention network”, a computer can be shown a scene of a picture that can help it to tell a story. The attention network can look at different areas of a scene and describe exactly what it sees. So by pointing out the different scenes or aspects of various photos, and putting them together, it is possible to create a story. However, what is missing from machine learning and AI in storytelling is that it lacks context. Context is something that is extremely difficult to replicate or represent in computers. For now, it seems to be a uniquely human trait.
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One popular method in AI is “word embedding”, which allows the machine to identify a word by the company it keeps. So if the machine can recognize a word by other words around it, it can figure out the word through association. This algorithm will then try to look at a word and predict perhaps 5 words that usually come before and after. What’s cool about this is that the algorithm continues to learn with every word is correctly predicts, so it trains the machine to learn dynamic lexicons, and human language. This is some of the machine learning and AI that we use here at DEEP. While focusing on sports, for example, we may want to collect data on injuries.

Well in sports, there are thousands of injuries and many different ways to describe them, so we had to be smart about our method. We programmed the algorithm with common injuries such as ankle sprains, concussions and torn ACLs, and then used them to see injuries that are similar. This expands the types of injuries we can identify because the computer has already seen tons of data with injury language and can make the connection based on similarity of language.

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It’s impossible to predict where the future of AI and machine learning will take us. Looking ahead in a positive light, machine learning can help augment all the areas where one really needs to have a wide or deep knowledge of a subject (or many subjects). Lawyers, doctors, and transportation are already being transformed before our very eyes.

What kind of AI or robot do you wish you had in your life?

Here at DEEP, we investigate the world of knowledge visualization, so stay up to date with us as we share our findings!

 

Top 5 Data Visualization Authors to Follow in 2017

Do you ever find yourself sitting in front of a screen, blank page taunting you with all its white space, unable to think of a way to create content that appeals to your audience? Have some boring data you want to make interesting and more engaging?

Well, have no fear! We’ve collected a few top data visualization books to give you inspiration for the new year. These books and their authors can help give you inspiration while you’re on your data viz journey.

1. Data Visualisation: A Handbook for Data Driven Design by Andy Kirk

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Andy Kirk has written the ultimate tome on mastering data visualization. The author, founder of the company Visualizing Data ltd, managed to compress a lifetime’s worth of data viz expertise into this beautiful and easy-to-follow book. Not only does Kirk offer chapters and chapters of information and examples, he also includes sections at the end of each chapter to enhance your experience and help give you the upper hand.  If you’re looking for a challenge (or are a teacher’s pet nerd), this section is for you, and the book as a whole will help anyone looking to hone their data viz skills or understand the field better.

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You can also check out his cool project on “graphically exploring the fluctuations of success across the film careers of a selection of actors and directors” called “Filmography” here

2. The Best American Infographics 2016 by Gareth Cook

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Pulitzer Prize-winning journalist Gareth Cook has edited one of the best (!) books of infographics this year, “The Best American Infographics”.  This year’s group of infographics can make even the most boring subjects perk right up with colorful, unexpected and unusual visuals. It also takes some very fascinating subjects and brings them to life. Take for example, this visualization of presidential doodles:

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Reagan is a surprisingly good doodler!

This book covers topics including health, the arts, sports, culture, and of course, politics. In one of the most politically charged years to date, Cook included interesting data viz on how people in different occupations vote and who is buying the American elections. Cook brings stunning visuals and expert artistry to this interesting and thought-provoking compilation.

3. Cool Infographics: Effective Communication with Data Visualization and Design by Randy Krum

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Krum makes data memorable by fusing together creative design and the science of infographics in this book packed full of gorgeous and useful information. This how-to provides both newbies and seasoned pros with the fundamentals of infographics, including process, software tools, marketing uses, and presentation tips. Krum also goes a bit political in this election year with an interesting, Candyland-like infographic on how a bill becomes a law:

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Beyond tools and techniques for creating great infographics and even online data viz marketing (including social media and SEO), Krum really goes in-depth on the science behind data viz. If you’re looking for a comprehensive look on how to make your infographics work for you, this is definitely it.

4. Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations by Scott Berinato

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Dataviz is bringing in the big guns: Scott Berinato, Senior Editor at the Harvard Business Review and dataviz maven. In this essential guide to visualizations, Berinato outlines how visualization works and best practices for thinking visually. Although tricks and tips are included, this is more than just a rule book for turning data into visuals. As you would expect from Harvard Business School, this book uses established and leading-edge research to discuss neuroscience and visual perception in relation to dataviz. It also explores the very new field of visualization science, and gives practical and actionable advice.

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One of the biggest takeaways? Rather than creating charts right off the bat, Berinato suggests investing time in establishing what your message is, who you’re speaking to, and what the setting is. This equation will set you up for success on your dataviz journey.

5. Visual Miscellaneum: The Bestselling Classic, Revised and Updated: A Colorful Guide to the World’s Most Consequential Trivia by David McCandless

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This book is pure fun for the senses. Updated and revised over the years, “The Visual Miscellaneum” provides a “colorful guide to the world’s most consequential trivia”. This reference book gives context to our world and helps us understand all the information thrown at us on a daily basis, including advancements in technology and health breakthroughs. McCandless also adds tons of fun through culturally relevant and interesting data viz, such as hangover remedies from around the world, insurance value based on body parts (don’t show that one to the kids), and a great visual of calories in different foods next to how many calories are burned doing various physical activities (helps us put our New Year’s resolution to lose weight into perspective).

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We don’t know about you, but we can’t do anything without a good, strong cup of joe

McCandless really understands how to make data relatable, informative, and fun. This essential handbook to visual culture will leave you interested, laughing, and stimulated.
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Did you know? Visuals are processed 60,000X faster in the brain than text.

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Here at DEEP, we investigate the world of knowledge visualization, so stay up to date with us as we share our findings!

Share your Experience

If you have any data-driven storytelling tricks, tips or ideas of your own that you’d like to share, let us know in the comments section!

 

Data-driven Storytelling: Top Tips For Making the Most Out of Your Story

How to Get More Bang for Your Data Visualization Buck

You may remember in our last post that we talked about the importance of telling your story through data visualization. Data-driven storytelling is a way for people (and companies) to effectively communicate data insights, using a combination of data, visuals and narrative. The data-driven visual helps to tell a story in a way that words or pictures alone simply cannot achieve.

However, storytelling is not an inherent skill-it’s more of a science….and we’ve kind of always wanted to be scientists (thanks to Mrs. Miller’s third grade volcano project).  There are many different components that go into data-driven storytelling, including context, audience, choosing the right data and visuals, and much more. It’s also really important to leverage the power of visual storytelling to connect with your audience and provide them a message that resonates. Remember: people remember 80% of what they see, but only 20% of what they read, so if you’re making a visual, make it good. Did you remember that? Because it wasn’t a visual, so we won’t blame you if you didn’t.

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We’re rich! (data-rich visuals, that is)

Here’s a few tips to help you make the most out of your story.

1.The Five-Second Rule

This rule doesn’t only apply to the time you need to pick food up off the floor before you can eat it. According to research, people’s attentions spans are shrinking every year, down from 12 to 8 seconds, in the last 15 years. If you can’t grab someone’s attention within the first few seconds, you’re pretty likely to lose them all together. That’s also why it’s important to create a clear visualization, so people know where to look and what they are looking at.

Caveman Sitting Outdoors Using Stone Tablet with Touchscreen
It can be 6 seconds only if it’s your favorite flavor of ice cream

2. Data Viz Should Complement Your Narrative

If your data visualization is any good, it should be able to tell a story all on its own. Let’s say it’s taken out of context or used in a different site, your reader should still be able to understand the story that the visualization is trying to tell. This means it should be clear, simple, and easy to grasp. As storytellers, we’re always tempted to add in different angles, gizmos and gadgets into our content, but it’s important to start with something simple, and layer on the data from there.

Caveman Sitting Outdoors Using Stone Tablet with Touchscreen
Hi, I’m Bob…that’s my story, and I’m sticking to it

3. Simple Over Sexy (aka smack them in the face with your data)

As noted above, if a visual is too complicated, it can turn your audience off. People are using enormous amounts of brain power on big, important (and small, unimportant) tasks every day, so you’ve got to make it easy for them to grasp the point. Take out anything that’s truly unnecessary, and keep your visual simple. Just because you have the capability of making something complicated, doesn’t mean you should. Interaction with your data viz should be easy and intuitive….like working with DEEP!

Caveman Sitting Outdoors Using Stone Tablet with Touchscreen
Easy does it

4. It’s Not the Size of the Boat, It’s the Color of the Ocean

Now that you know to keep your data viz simple, easy to understand, contextual and attention-getting, now’s the fun part….color! But you want to be sure that your visualization is not only colorful, but uses color in order to be stunning and effective. Primary colors are good, but a bit blah. Be sure to put a little pep in your step by reading up on color theory. Different colors can cause different emotional responses, and if used correctly, you can align your visuals with the feeling you’re looking to elicit from your users.

Caveman Sitting Outdoors Using Stone Tablet with Touchscreen
Hahaha, look how small their visual data is

5. Don’t Be a Chatty Cathy-Avoid Using Too Many Words

It’s called “visualization” for a reason. If you’re using too much text to accompany your data viz, the “viz” part gets lost. Rather than worrying about words, focus on the concept and message you’d like to communicate to your users, use words sparingly, just to get your point across. Be sure to refine and trim down your copy as much as possible, and let your visuals do the talking.

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Guuuuurl, you should have seen all the words on his data viz

Here at DEEP, we investigate the world of knowledge visualization, so stay up to date with us as we share our findings!

Share your Experience

If you have any data-driven storytelling tricks, tips or ideas of your own that you’d like to share, let us know in the comments section!

Data-driven Storytelling: What Does it Mean and Why Should You Care?

Did you know that over 23,000 breast reduction surgeries are done every year in the US…on men? This blog has nothing to do with breasts, surgery or even man boobs, but that line got your attention, right?

And that’s kind of the point. Since people are inundated with content these days, you have to grab them right away (ahem…grab their attention, that is). Usually, text plays second fiddle to visuals when attempting to keep a reader on your page. People remember 80% of what they see, but only 20% of what they read, so visuals really are king these days. However, not just any visual will keep people engaged.

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Do you understand the words that are coming out of my mouth?!

What is Data-driven Storytelling?

Would you believe us if we told you it was a man in a car named “Data” who likes stories? No? Ok, well here’s the real deal, then: Data-driven storytelling is a way for people (and companies) to effectively communicate data insights, using a combination of data, visuals and narrative. The data-driven visual helps to tell a story in a way that words or pictures alone simply cannot achieve. When you are using visualized data to tell your story, readers become more engaged in the content. When you are providing beautifully visual, informational insights into a sports player, an actor or a movie, it helps to give the reader a new angle through which to see and understand the subject.

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Hey ladies…want to see my data visualizations?

The Importance of Data-driven Storytelling

Everyone has heard the phrase “a picture is worth 1,000 words” and no one knows that better than content creators (and…uh…maybe Picasso). Even cavemen and Egyptians, back in the day, communicated through visuals in order to transmit information and tell stories.

However, the time of cavemen and Egyptians was a simpler, less-connected time: no social media, living in the dark (literally), and only worrying about being eaten by a large animal. But since then, life has gotten more complicated and infinitely more complex: since 2013, more data has been created than in the entire history of the human race and ten percent of all photos ever taken were taken in the last 12 months. Whoa. Most people, particularly online consumers, want information, but in order to process and sort through all this data for the relevant info, they need it in a visual, bite-sized, and mobile friendly way.

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Cavemen used tablets, too! Ba dum ching

The Science Behind the Story

Let’s put on our Pinky and the Brain hats and back up these claims with some science. We know that the visualization of data allows the brain to process information more easily and at a faster rate than it would with just facts and figures alone. The two sides of our brain process data very differently, and at different speeds, with the right side (visual, perceptive, more abstract) processing at a quicker and more efficient rate than the left side of the brain (the cognitive, thinking side). Data visualization stimulates both sides of the brain, as well as supercharges and optimizes brain power (however dataviz stimulates only the brain…sorry guys).  

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You can believe us because we said “brain science”

This method of looking at data is powerful because it takes advantage of the brain’s ability to process information by shifting the balance between perception and cognition. Therefore, data visualization is a more effective method for the brain to understand information. Our brains are infinitely happier and work better when we give them visuals and text in a balanced and manageable format. And who doesn’t want to make their brain happy?!

We also know that the brain is really just a big computer, with software and memory and storage components. (So, basically….we’re robots with hair). Our brains are receiving tons of information-in fact, neuroscientists estimate that up to 100 megabits of information flow into each eye every second, comparable to the fastest broadband connections.  And we just threw out the word neuroscientist, so you know this has to be true.

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Your brain on DEEP

Studies done on memory and attention show our growing inability to multitask and retain the ever-increasing amount of information that is coming our way. Therefore, we must rely on external forms of information storage, which can be done by encoding information visually. This allows more information to infiltrate the brain’s memory. Aka our brains can’t handle all the info that’s being thrown at it, so we have to outsource it to visuals.

Here at DEEP, we investigate the world of knowledge visualization, so stay up to date with us as we share our findings!

Now that we know how important dataviz is, stay tuned for our next post on tips to make the most our of your data visualizations.

Share your Experience

If you have any data-driven storytelling tricks, tips or ideas of your own that you’d like to share, let us know in the comments section!

 

Old School vs. New School Knowledge Face-off: Winner Takes All

Imagine life 2,000ish years ago: a long-haired hippie named Jesus was preaching peace in the Middle East, Africa was mostly undiscovered and coffee didn’t exist yet (gawd, how did people live?!). One of the earliest encyclopedias to make it to modern times can also be traced back to that time, around 77 AD, when Pliny the Elder compiled and published his work of over 20,000 facts from 2,000 works by over 200 authors.

While society has evolved and changed and improved (Starbucks, anyone?),  encyclopedias have remained much the same. This is puzzling, as knowledge is one of the most popular topics on the internet. In October 2016, Wikipedia received 5B monthly visits, and the largest online publications got around 10% of that traffic (BBC 568M, CNN 528M, ESPN 470M). IMDb has 670M monthly visits, which is more than all the traffic of all the entertainment publications combined.

And although Wikipedia made a huge impact with its debut in 2001,  its interface and delivery of knowledge has evolved minimally. (Which is kind of crazy, considering 65% of digital media time is spent on mobile and the traits of Millenials-hyper connectivity, content consumption, creation and curation- have now been adopted by users of all ages.)

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The knowledge industry needs a facelift, and quick. Technology is changing rapidly, and users habits have adjusted to accommodate the devices they use to consume information. Additionally, attention spans have gotten shorter and users expect a little pizzazz with their text-interactivity, visualization, pretty interfaces.

Let’s wrap this up since you’re probably already focused on something else (yes, people with short attention spans, we’re talking to you).

The knowledge industry can become so much more relevant- meeting users where they’re at, creating an environment where information is dynamic, allowing users to interact with the data they are seeking.  Challenge accepted 🙂

 

Our Story, Chapter 1

Once upon a time, in a corporate far far away, lived a rag-tag team of designers, techies and marketers with a genius idea.

It all started with DEEP’s founders and core tech team, who all used to work together developing interactive interfaces for TV services. One day, they had the idea to provide TV viewers with the relevant background information that could be quickly brought up on mobile while watching their favorite shows.

As they investigated, they realized knowledge in general was a hot topic, but that the current online knowledge solutions weren’t a good fit for most users, specifically Millennials. They weren’t quick, visual, mobile, and they didn’t offer a good discovery experience.

They felt that Google and other search engines answered a question very quickly, but, discovering  more was a lengthy process. IMDB and Wikipedia were good for giving the full background on TV, movies and celebs, however, their solution is text heavy.

Therein came the team’s first of many A-ha! moments: they should make knowledge fun, visually appealing, and easy to use. How could they build something to fill the gap?

With the blessing of the large corporate that bought the previous company where they all worked, they founded DEEP. Their first thought was “We want to reinvent the way knowledge is offered to the masses.”

They came up with a plan, focused on the following tenets:

  • Knowledge should be offered in bite-sized portions
  • It must be visual, mobile friendly, and engaging
  • Knowledge cannot just sit there quietly waiting to someone to search for it

Where have we gone since then? Check out our timeline for the company story. Strap on your seat-belt and enjoy the ride!

So, knowledge world, wait no more! We’re here to rock you.

The End.
Just kidding. We’re just getting started!

 

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