Data visualization is an incredibly valuable tool for marketers. It helps you communicate important insights in a visual way, helping you deliver your message more impactfully. But not everyone does data design right—even if they say they do. A good data visualization agency knows data is about more than charts and graphs; it’s about bringing your data to life.  

How to Find a Data Visualization Agency

To make the hunt a little easier, here are 8 great questions to ask to help narrow down your search for the right data visualization agency.  

1) Do they demonstrate their data expertise?

Many agencies can churn out an infographic, but a great data visualization agency knows the fundamentals of data. They don’t just design; they can analyze and dig into the data to uncover interesting insights. They should also demonstrate that knowledge and share their knowledge and expertise freely. You want to know you’re working with true experts.

2) Do they turn data into stories?

Data analysis is only step one of creating a great data visualization. Turning those insights into a solid narrative and using data visualization to support that narrative is what will make your project truly successful. You don’t just want a data visualization agency to plug your data into a design program. You want them to help you create the most impactful narrative possible.  

3) Do they design data according to best practices?

Now here’s where a lot of agencies fall short. Yes, you can design a chart. Yes, you can add a pretty illustration. But this is not what true data visualization is.

The entire point of the art is to make data as comprehensible as possible, to present it in the most easy-to-digest format. There are subtle but very effective ways to do this. The way you label, order, or use color can help or hurt your data visualization. (You can find out more about best practices in the Data Visualization 101 e-book from our sister company, Visage.) Ask them about their data design philosophy to get a sense of how they approach it.

4) Do they work in different mediums?

There are many ways to present data visualizations, including infographics, interactive experiences, video, and more. The format you choose is informed by your data story, which is why it’s so important to work with someone well-versed in data storytelling. They should be able to design whatever the data requires.

5) Have they created similar work before?

If you have a specific idea in mind, you want to work with a data visualization agency that has the skills and experience to execute it for you. (You also want someone who can tell you if your idea doesn’t serve the data well.) Take a look at their portfolio to see if they’ve created similar work or have experience with similar clients or industries.

6) Do they have a good response when you ask them what their favorite type of chart is?

You want to work with people who are passionate about their craft. Asking this question will give you a sense of their knowledge and enthusiasm for data visualization. Trust us, any self-respecting data nerd will have an answer. (And if you want to hear some very strong opinions, you might also ask them which side of the pie chart debate they’re on.)

7) What recent piece of work are they particularly proud of, and why?

You can comb through their portfolio to get a sense of what they do, but if you aren’t the most data-literate person, it’s likely you’ll miss the nuance and craftsmanship that goes into a strong data visualization. Having them explain their thought process behind a design or what they did to help enhance comprehension will give you a sense of their creative process and problem-solving skills.

6) Do they have thorough and thoughtful processes?

There are a lot of moving parts in a major data visualization project. Content needs approval, brand guidelines needs to be communicated, data need to be double-checked. If these responsibilities are unclear, if they fall through the cracks, or are ignored completely, it can affect the quality—and credibility—of your data visualization. Make sure you are clear on how they work, and how they expect to work together with you.

7) Are they transparent with you?

You want a creative partner you can rely on to produce good-quality work. If they seem less than confident, if their pricing is murky, or if you get a general bad vibe, it’s best to move on. Again, a lot of agencies claim that they can do any data visualization, but it is a very specific skillset that requires true expertise.

8) Do they approach projects as collaborative?

You don’t want an antagonistic partner, but you don’t want a total yes-man either. A great piece of data visualization happens when the best ideas make it to the front—regardless of ego. If you have a great design suggestion, they should be open to it. If you’re heading in the wrong direction, you want them to tell you so. The goal is the best project possible. Work with a data visualization agency that puts that value above all else.

Ask these questions while you’re on the hunt and you should be able to find the right partner fairly painlessly. But remember: Finding your partner is only the beginning.

How to Work with Your Data Visualization Agency

If you want your brand to get the best work from your agency, it’s important to establish a good rapport from the jump. Here are a few tips to make the process a little smoother.

1. Communicate a clear goal. Your data visualization agency is made up of expert designers and data storytellers who are adept at creating visualizations to communicate a specific purpose. They need to know not only what the goal is for this particular project but how it plays into your larger communication goals. Is it meant to engage people on social? Will it be used at a tradeshow? This info will influence their decisions at every stage, from the language they use to the format they use to present the data. Start off on the right foot with a detailed creative brief to clue them in. Here’s how to write one if you haven’t done it before.
2. Educate yourself about data storytelling. It always helps to share a basic understanding of what data storytelling really is. To understand the value of data visualization, find out why data-driven storytelling helps brands, and learn about why our brains love data visualization.
3. Don’t just dump your data on them. It’s exciting to have a partner who can dive into your data, but that doesn’t mean they’re your personal assistant. Far too often a client will get so excited they’ll send over every single piece of data they have, giving us a veritable ocean of data to wade through. This wastes precious time for the data visualization agency and, ultimately, your organization—the longer they take, the longer you wait. When you deliver data, it should be organized, complete, and a decent amount of data. (Sometimes people come to us with three stats and ask us to turn it into a data story. Other times, it’s an insane database of randomness.
4.  Let them extract the most meaningful insights. You may already have a story in mind—and you may have the data to support it—but there may be a more interesting angle in that data. (Sidenote: We hate to see people try to retrofit data just because they have a “great” idea. Not only does this result in a weaker story but you risk misrepresenting data, which can hurt your credibility.) You should have filled your data visualization agency in on the project’s goal, so let them help extract the most valuable insights to achieve that goal.
5. Collaborate on the story. Once the most interesting insights are uncovered, it’s vital to shape a narrative that will communicate them with the most impact. This is a highly collaborative process. You know who you’re trying to reach—how they think, what problems they face, the language they use—so you should help guide your data visualization agency. We believe the best story wins, no matter who it came from. 

Follow these tips and you should be able to form a productive and creative partnership together. Of course, we’d be happy to build that partnership with you. If you’re looking for someone to turn your spreadsheets into a compelling data story, reach out.

Find out why data visualization helps your brand, how you can find great data stories, and more.

Find out how to design the most common charts and graphs to make the most impact with your data visualizations.

Data visualization design is both an art and a science, which is why it can be challenging for noobs to master. But if you want to master data storytelling—and make a strong impact through content—it’s a crucial skill.

The Power of Data Visualization

Your brain is prewired to process visual content much quicker than text, which is why data design is so effective. By “seeing” the data, it is easier for your brain to intake, synthesize, and retain the information presented.

To see the power of data visualization at work, watch this quick video. 

Unfortunately, a lot of people think that slapping a few charts together means you’re doing data visualization design well. Not only are you not doing it well; you might actually be hurting your brand. Subpar data design comes in many forms—a confusing visualization, mislabeled data, 3D charts that skew perception, etc. In these cases, your credibility may be on the line, and nobody wants that.

Even if you’re not misrepresenting data, if you aren’t presenting it in its most optimized form, you’re doing a disservice to your reader. Luckily, there are many simple things you can do to ensure your data stories make the impact they should.

So, if you’re ready kick your data visualization design game up a notch, we’ve compiled our team’s best tips to help you fix common data design mistakes and enhance your existing data visualizations, one chart at a time. We even arranged this list by category in case you need a quick reference. We hope they help.

25 Tips for Data Visualization Design

To start, let’s cover a few general things to keep in mind. Remember that every data visualization design choice you make should enhance your reader’s experience—not yours. (Sorry, but it’s not about showing off your sweet line-art skills.) Follow these tips to do your data justice.

1) Choose the chart that tells the story. There may be more than one way to visualize the data accurately. In this case, consider what you’re trying to achieve, the message you’re communicating, who you’re trying to reach, etc.

2) Remove anything that doesn’t support the story. No, that doesn’t mean you kill half your data points. But be mindful of things like chart junk, extra copy, unnecessary illustrations, drop shadows, ornamentations, etc. The great thing about data visualization is that design can help do the heavy lifting to enhance and communicate the story. Let it do its job. (But don’t use 3D charts. As previously mentioned, they can skew perception of the visualization.)

3) Design for comprehension. Once you have your visualization created, take a step back and consider what simple elements might be added, tweaked, or removed to make the data easier for the reader to understand. You might add a trend line to a line chart, or you might realize you have too many slices in your pie chart (use 6 max). These subtle tweaks make a huge difference.

Comparison

Data visualization makes comparison a lot easier, letting you actually “see” how two different data sets stack up to each other. But just putting two charts side by side doesn’t necessarily accomplish that. In fact, it can make it more confusing. (Ever tried to compare 32 different pie charts? Yeah, didn’t think so.)

4) Include a zero baseline if possible. Although a line chart does not have to start at a zero baseline, it should be included if it gives more context for comparison. If relatively small fluctuations in data are meaningful (e.g., in stock market data), you may truncate the scale to showcase these variances.

5) Always choose the most efficient visualization. You want visual consistency so that the reader can compare at a glance. This might mean you use stacked bar charts, a grouped bar chart, or a line chart. Whatever you choose, don’t overwhelm by making the reader work to compare too many things.

6) Watch your placement. You may have two nice stacked bar charts that are meant to let your reader compare points, but if they’re placed too far apart to “get” the comparison, you’ve already lost.

7) Tell the whole story. Maybe you had a 30% sales increase in Q4. Exciting! But what’s more exciting? Showing that you’ve actually had a 100% sales increase since Q1.

Copy

Data is about numbers, certainly, but it is generally used in conjunction with copy to help provide context for the point at hand. That said, in many data visualizations, infographics, and e-books, we see data visualization and copy working against each other instead of together.

8) Don’t over explain. If the copy already mentions a fact, the subhead, callout, and chart header don’t have to reiterate it.

9) Keep chart and graph headers simple and to the point. There’s no need to get clever, verbose, or pun-tastic. Keep any descriptive text above the chart brief and directly related to the chart underneath. Remember: Focus on the quickest path to comprehension.

10) Use callouts wisely. Callouts are not there to fill space. They should be used intentionally to highlight relevant information or provide additional context.

11) Don’t use distracting fonts or elements. Sometimes you do need to emphasize a point. If so, only use bold or italic text to emphasize a point—and don’t use them both at the same time.

Color 

Color is a great tool when used well. When used poorly, it can not just distract but misdirect the reader. Use it wisely in your data visualization design.

12) Use a single color to represent the same type of data. If you are depicting sales month by month on a bar chart, use a single color. But if you are comparing last year’s sales to this year’s sales in a grouped chart, you should use a different color for each year. You can also use an accent color to highlight a significant data point.

13) Watch out for positive and negative numbers. Don’t use red for positive numbers or green for negative numbers. Those color associations are so strong it will automatically flip the meaning in the viewer’s mind.

14) Make sure there is sufficient contrast between colors. If colors are too similar (light gray vs. light, light gray), it can be hard to tell the difference. Conversely, don’t use high-contrast color combinations such as red/green or blue/yellow.

15) Avoid patterns. Stripes and polka dots sound fun, but they can be incredibly distracting. If you are trying to differentiate, say, on a map, use different saturations of the same color. On that note, only use solid-colored lines (not dashes).

16) Select colors appropriately. Some colors stand out more than others, giving unnecessary weight to that data. Instead, use a single color with varying shade or a spectrum between two analogous colors to show intensity. Remember to intuitively code color intensity according to values as well.

17) Don’t use more than 6 colors in a single layout. Enough said.

Labeling

Labeling can be a minefield. Readers rely on labels to interpret data, but too many or too few can interfere.

18) Double check that everything is labeled. Make sure everything that needs a label has one—and that there are no doubles or typos.

19) Make sure labels are visible. All labels should be unobstructed and easily identified with the corresponding data point.

20) Label the lines directly. If possible, include data labels with your data points. This lets readers quickly identify lines and corresponding labels so they don’t have to go hunting for a legend or similar point.

21) Don’t over label. If the precise value of a data point is important to tell your story, then include data labels to enhance comprehension. If the precise values are not important to tell your story, leave the data labels out.

22) Don’t set your type at an angle. If your axis labels are too crowded, consider removing every other label on an axis to allow the text to fit comfortably.

Ordering

Data visualization is meant to help make sense. Random patterns that are difficult to interpret are frustrating and detrimental to what you’re trying to communicate.

23) Order data intuitively. There should be a logical hierarchy. Order categories alphabetically, sequentially, or by value.

24) Order consistently. The ordering of items in your legend should mimic the order of your chart.

25) Order evenly. Use natural increments on your axes (0, 5, 10, 15, 20) instead of awkward or uneven increments (0, 3, 5, 16, 50).

How to Master Data Visualization & Storytelling

Of course, if you really want to stay on top of your game, make sure you’re up-to-date on best practices for data storytelling at every stage of the process.

• Use the right sources. Great stories come from great data. While you can find a larger variety of external data, internal data is a particularly effective source of unique and interesting stories. To find external data, check out these 100+ sources of free and credible data. For internal data, here are 9 places to look. You can also follow our tips to source that data correctly in your content.
• Craft a strong story. The true power of data storytelling relies on your ability to extract and shape a cohesive narrative. Start with this step-by-step guide to find stories in your data and craft an effective data narrative. You can also download our free e-book, The Content Marketer’s Guide to Data Storytelling, for more tips on bringing your data to life.
• Choose the right format. To make sure your data has the strongest impact, you need to present it in the right package. Whether you’re creating an e-book, infographic, or motion graphic, pick the right format for your data visualization story.
• Apply design fundamentals. Good design matters. Remember, too, that differentiating yourself through design is crucial to stand out. Start with our guide to designing the most common charts and graphs, find out how to keep your content on brand, consider experimenting with different visual styles, and get inspired by more examples of technology infographics, B2B infographics, and interactive infographics.
• Make the most of your content. Get more mileage by repurposing your data visualizations, or turning your old content into infographics, e-books, animated infographics, reports, microcontent, etc.
• Promote the right way. Don’t let good data stories get buried. Find out how to promote your content like a content agency, and optimize your blog for SEO.

If you still need a little help with your data storytelling, don’t be afraid to seek outside help. Here are a few tips to find the right data visualization agency, as well as tips to work together once you do. We’re also happy to talk through any of your data design challenges—seriously, we’re data geeks.

Good data storytelling can do wonders. It helps you find interesting insights. It helps you tell unique stories that people want to hear. And with beautiful data visualization, you can deliver that story, no matter how complex, in an easy-to-digest package. This is why data visualization is such a useful tool—and why it’s become so popular. But like many things, the more people do it, the more mistakes get made. This is a disservice not only to the practice but to the very people these data visualizations are for.

At the very least, bad data visualization is a nuisance. At worst, it can seriously hurt your readers’ trust in you, and, ultimately, your relationship. We are on a mission to rid the world of BS visualization, so we’re breaking down 6 ways to avoid the bad data visualization epidemic. Keep these in mind for your next project.

1) Use Really Good Data

Good data storytelling starts with good data. But in an “alternative facts” world, not all data is good data—and because people want to jump on the data train, they’re churning out infographics right and left with subpar sources. That is some major BS. So how do you know what counts as “good” data?

• It comes from a solid source: Data can be tricky because it can be easily misrepresented or inaccurately collected by organizations with an agenda. Source your data from trusted, credible sources. Even better, use your own internal data. Here are a few more tips on how to properly source data, as well as some great places to find data if you’re stuck.
• It’s clean and complete: Missing or incomplete data can affect your interpretation and throw things off. Before you dive in, clean and sort data so you know you’re working with the right stuff.
• It has a story: Just because you inject a few stats into a blog post doesn’t mean you’re really doing data storytelling. A great story lies in the interesting insights you extract from a data set. Follow our primer to find out how to find a story in your data. (It also has tips on cleaning your data, too.)  

2) Tell the Full Story

It’s tempting to hone in on a single data point that supports a pre-conceived narrative, but if it doesn’t really fall in line with what the data is telling you, don’t present it as such. For example, let’s say your team saw a 50% increase in sales in Q1. Showing that increase alone makes it look like you’re killing it. But if you include the full set, including numbers from the previous quarter that show a 75% decrease in sales, it’s a very different story. Data helps you establish trust and build a relationship by showing readers information. Withholding or misrepresenting erodes that trust in a second.

Example: We used data from the Clarity‘s Global Entrepreneurship Monitor Report to craft an interesting infographic about the ages that entrepreneurs are most likely to pursue their business. With that data, the reader was able to see the larger picture and identify where they land on the age spectrum.

 

3) Choose the Right Chart

We admire any designer who attempts data visualization—so long as they take the time to learn how to properly do it. (To start, check out our guide to designing the most common charts and graphs.) Choosing the right visualization is crucial not just to the aesthetic of your piece but also to your readers’ understanding. Did you know 3D charts can visually skew data? That patterns distract from the data? That negative numbers should never be represented with the color green? These may seem like pesky rules, but they do affect the way a chart is interpreted.

4) Don’t Make Your Reader Do More Work

Data visualization is all about making things easier to understand and interpret. But oftentimes little things can interrupt the experience, like when…

• A reader has to hunt for a chart legend
• The legend is so far away from the chart they have to keep looking back and forth to try to make sense of what they’re seeing
• Data that is meant to be compared is presented in two separate, difficult-to-compare charts (e.g., five pie charts side by side vs. two stacked bar charts together)

The beauty of data visualization is that you use the best of both worlds—design and text—to enhance. So let design do the heavy lifting where needed. After you design anything, give it a pass to see if anything may be added, removed, or condensed to improve comprehension. For more on this, see the 8 design mistakes you should avoid in your visual communication.

Example: We partnered with the NFL to produce print reports featuring data and analytics for each team’s web performance. Each report contained detailed information, presented in an appropriate visualization. 

5) Ditch BS Chart Junk

Design can do a lot to enhance your data visualization. But too many designers care more about the design than the data. This results in a lot of unnecessary chart junk. These cluttered charts, filled with icons, illustrated characters, or outrageous creative “treatments,” make us cringe—definitely not the reaction you want.

6) Double Check E-V-E-R-Y-T-H-I-N-G

Obviously, you’re not willfully trying to sabotage your data visualization. But regular old carelessness is usually the cause of the biggest mistakes we see. (Remember the Fox News pie chart that totaled 193%?) Something always happens when data travels from spreadsheet to fully designed layout. That stray label, transposed number, or missing data point can throw everything out of whack. Things to keep an eye on:

• Labels: Are they all there, and do they match the data?  
• Numbers: Do they match the original text?
• Visualizations: Do the bar charts match the data? Are bubbles sized proportionately? Is each segment on your pie chart accurate?
• Copy: Are chart labels, legends, etc. typo-free? Is anything cutoff or misplaced?

Always give it a final pass before you send it into the world.

Above all, if you really want to keep the BS out of your data visualization, always challenge yourself to improve your skills. To get started, here are a few more resources to keep you on your toes:

• Find out how to craft an effective data narrative.
• Learn how to pick the right visualization for your data.
• Follow design best practices for data visualization.
• Try Visage, our easy data design platform.  

If you still need a little help with your data storytelling, we’d love to work together.

Although the infographic Renaissance has triggered its resurgence, data visualization is nothing new. For hundreds of years, data designers have brought numbers to life to give us better insight into the world around us—and their data storytelling lessons are as relevant as ever.

To take a little walk down memory lane, we’re showcasing historic data visualizations that demonstrate great data storytelling. From data labeling to proper comparison, here are 7 things you can apply to your own data visualizations.

1) Keep the Focus on the Data

Charles Minard’s 1858 “Les Émigrants du Globe” map was a simple depiction of immigration patterns. Simple is the keyword here. There are no over-illustrated continents that distract from the immigration routes. There is no unnecessary labeling (beyond the simple continent name), and the key is simply colored. Everything is easy to track and discern. It’s simplicity at its best.

2) Label for Comprehension

While it feels like there’s a lot going on in this 1865 chart depicting British coal production from 1850-1864, Minard helped make the data more accessible through useful labeling. We see the X and Y axis labeled in increments for context, along with grid lines and directly labeled sections, color-coded for distinction. (Note that he didn’t also include a colored key, which would have been redundant.) Well-labeled charts reduce interpretation time, helping increase comprehension.

3) Choose the Most Effective Data Visualization

There are many ways to display data, but the goal is always to tell the strongest story. That’s what Florence Nightingale was determined to do when she and William Farr analyzed death rates during the Crimean War and realized that most soldiers had not died in combat; it was actually “preventable diseases” that claimed the most lives.

To convince Queen Victoria and Parliament to invest in better sanitary conditions, she needed to present the data in its most impactful way—as she said, “to affect thro’ the Eyes what we fail to convey to the public through their word-proof ears.” In 1858, she created the “Diagram of the causes of mortality in the army in the East,” which featured the entirely new polar area chart, a variation of the pie chart. The visualization shows death by month, color-coded by cause of death. The chart showed the story impactfully, and she successfully argued her case for better sanitary conditions.

4) Tell a Comprehensive Story

The beauty of data visualization is that you can communicate far more information in a more digestible package than you can with text alone. While that doesn’t mean you have to use every piece of data at your disposal, you can tell a rich story in a single visualization. Charles Minard’s 1869 map of Napoleon’s Russian campaign shows this well.

As data visualization expert Edward Tufte notes, “Minard’s graphic tells a rich, coherent story with its multivariate data, far more enlightening than just a single number bouncing along over time. Six variables are plotted: the size of the army, its location on a two-dimensional surface, direction of the army’s movement, and temperature on various dates during the retreat from Moscow. It may well be the best statistical graphic ever drawn.”

5) Order data for comprehension

True data visualization artists know that data visualization is about more than displaying data; it’s about displaying data so the reader understands that information quickly and completely. Simple details like ordering do a lot to enhance the experience of viewing a data visualization.

This is demonstrated with William Playfair’s “The Commercial and Political Atlas” from 1786, depicting Scottish exports and imports throughout the year. Playfair depicted the data in ascending order so the viewer could quickly identify the most active regions. To order effectively, arrange data numerically, alphabetically, or sequentially.

6) Compare for Context

One of the biggest benefits of data visualization is the ability to not just “see” but be able to compare data points. Playfair’s 1805 “Chart of Universal Commercial History” plots the ebb and flow of regions throughout history, allowing us to see the individual story compared to the larger view. These types of micro/macrocosm looks help provide context and color to a data story.  

7) Make it Beautiful

While data visualization best practices have changed, the art remains just that—an art. This specimen from the Rand McNally World Atlas was published in 1890. The subject is certainly less than thrilling (“National Debts of Foreign Countries and the U.S. in 1890”), but it is so damn pretty you’d want to hang it in your office today.  

Although we can always learn from history, data visualization is an ever-evolving practice. To make sure you stay on top of best practices, here are a few posts that can help:

• Learn more about why data storytelling is so powerful.
• Find out how to pick the right format for your data.
• Check out these 9 sources for great data.
• Try these 25 tips to enhance your data visualizations.
• Dive deeper into data storytelling with our book Infographics: The Power of Visual Storytelling.  

If you need a little help with your data storytelling, we’d love to work together.

Great data storytelling languishing in blogs, a beautiful chart hiding on a designer’s desktop, a great graph shared once in an infographic—these are some of our biggest pet peeves, because a great data visualization should never go to waste. It takes a lot of time and skill to produce beautiful data visualizations, and we think you should get the most mileage out of anything you put that much energy into.

10 Ways to Reuse a Data Visualization

That’s why we encourage you to republish, repurpose, remix, and reuse your data visualizations as much as possible. (We actually call this a divisible content strategy, which you can read more about here.) We know that it’s easy to wrap up a project and move on, but you should really look at all content you create through two lenses:

1. How you’ll use it in its first iteration
2. How to use it to extend the shelf-life of the content or support other collateral you’re creating

For data visualizations in particular, there are a lot of things you can do to extend their reach. Here are some of our favorites.

1) Infographics

Now, for many people, the whole reason you end up with a slick data visualization is because of an infographic. But if you’re starting with a visualization from, say, your annual report, you may be able to find a new home—and even a new story—in an infographic. Additionally, you may have a series of infographics on similar subjects. As long as it’s relevant, save your designers some work and repurpose the visualizations you have.

Example: We helped Highfive turn data from a company report into a visual, shareable infographic. 

If you want to make an effective infographic, check out our best tips from creating more than 4,000 of them.

2) E-books and White Papers

No matter what you make, visuals will always enhance it. (To see the power of visualization in action, check out this video.) And when you have a great data visualization, it’s because you have great data (well, we hope). For things like e-books and white papers, data is a great way to tell your story and break up the information with engaging visuals.

Example: We worked with HP to create their highly visual Enterprise 2020 e-book, featuring plenty of data visualizations. 

For more tips on how to make better content marketing, check out our e-book archive.

3) Reports

Whether it’s a client report, company report, or annual report, a great data visualization makes it a lot easier to “see” the significance of numbers. When you need to communicate or support your argument, data visualization is very useful. (Also, who wouldn’t prefer a well-designed piece in their inbox over a droll spreadsheet?)

Example: We partnered with the NFL to produce print reports featuring data and analytics for each team’s web performance. Each report contained detailed information, presented in a visually engaging way for easy reference. 

And check out how we turned the Krochet Kids intl. annual report into an interactive data visualization.

4) Presentations and Tradeshows

When you are publicly presenting information, you need it to be visually impactful. Whether you’re trying to engage an audience at a talk or grab the attention of someone passing by your booth at a tradeshow, a beautiful visual always helps. This is especially true for any environment where audio may be ineffective, like on a loud and busy tradeshow floor.

Example: We partnered with the Gates Foundation to design a highly visual presentation, using data visualizations to make the information easier to synthesize.

If you want to add a data visualization to your presentation, make sure to follow our 10 tips for presentation design.

5) Interactive Infographics

Interactive content is a great way to bring people into a story, to immerse and engage them. If you really want your data visualizations to come to life, interactives can do it. You may decide to incorporate a data visualization into an interactive slideshow or make the actual visualization interactive. There are plenty of options, depending on what you need.

Example: We worked with Microsoft to create their Anatomy of a Breach interactive website, which includes animated data visualizations that show how prevalent the crime is. (Go behind-the-scenes of the project here.) 

For more inspiration, check out 101 awesome examples of interactive infographics.

6) GIFS AND ANIMATED VISUALIZATIONS

Animated data visualizations differ from interactive infographics because they don’t actually require interaction; they can move on their own. Because they’re visually stimulating and stand out, they are an awesome way to catch someone’s eye in a social feed or spruce up an old blog post.  

Example: We partnered with Takepart to create a set of GIFS that highlights facts important statistics about veterans to address mental health support for veterans. Though simple, the animated data visualizations make a powerful statement. 

Learn more about why motion content is so effective.

7) Motion Graphics and Videos

If you haven’t noticed, we’re big proponents of motion in all its forms, both in animation and interactivity. Video is a natural extension of that. It may be an animated motion graphic or a live-action video, but both also provide opportunities to infuse your story with data.  

Example: We partnered with Foodbeast and Totino’s to help tell a data story about Americans’ binge-watching habits. Using the actual Totino’s product as a visual challenged us to come up with creative data visualization.

Video is only becoming more popular. Learn more about the differences between motion graphics and video.

8) Microcontent

Microcontent is a huge part of a divisible content strategy. What is it? It’s basically all the little visual stuff you use to promote things: the blog teasers, social content, one-off graphics. Data visualizations make perfect microcontent, especially on social. Say you have an infographic featuring 5 different charts. Extract each chart, post it as a visual tweet, and you have 5 different posts promoting a piece of content—each from a different angle. This is one of our favorite ways to both promote and extend the shelflife of pieces of content.  

Example: We collaborated with the Golden State Warriors Warriors to create a piece of data visualization microcontent to celebrate Stephen Curry’s MVP award.

For more about how to use microcontent effectively, check out our e-book.

9) Press Releases

Gone are the days of the old-school page-long press release. Journalists, publications, and the public want to know the core message as quickly as possible. This is especially true for journalists who are looking for interesting content to cover. A visual press release that features compelling data—along with a beautiful visualization—is much more likely to get you noticed (and published!).

Example: A single panel extracted from our modularly designed infographic for Jive Software is a great visual to entice a publisher to follow a story or envision the content on their site. 

Find out more about how to get publishers to fall in love with your content.

10) Misc. Collateral

Every organization has different communication needs that vary department by department. There are many types of collateral that can get a nice upgrade with data visualization. Think of the regular collateral you have (or stuff you’d love to have) that could benefit, including sales brochures, employee materials, etc.

Example: Google asked us to help bring their Trust/SMB Whitepaper to life. So we created a data-rich, print-ready brochure used to promote Google Apps.

No matter what you choose to create, make sure you avoid these 8 design mistakes in visual content.

Of course, remember that before you can create a great data visualization, you need a great data story. Here are 9 sources of data to check out, plus 5 ways to find a great story in whatever you find. Oh, and make sure you always follow data visualization best practices. Check out this guide to designing the most common charts and graphs, and try these 25 tips to upgrade your data visualizations.

Still need help? We’d be happy to talk it out.

We’ve created many data visualizations with many different partners, so we know first-hand what makes these projects succeed and what turns them into a total disaster. To make sure you get the best work from your data visualization agency, we’ve put together a few insider tips on how to communicate and collaborate the right way.

8 Tips to Do Great Work with a Data Visualization Agency

It’s not easy to find the right data visualization agency for your project. (If you’re still on the hunt, check out our tips for how to vet them.) And once you find the right partner, the work doesn’t end there. You don’t want a gun for hire; you want a collaborative partner who will help bring your data to life. But working together means you each have a responsibility to do your part. To get the best work from your data visualization agency—and the best project possible—here are a few tips to make the process a little smoother.

1) Communicate a Clear Goal

Your data visualization agency is made up of expert designers and data storytellers who are adept at creating visualizations to communicate a specific purpose. They need to know not only what the goal is for this particular project but how it plays into your larger communication goals. Is it meant to engage people on social? Will it be used at a tradeshow? This info will influence their decisions at every stage, from the language they use to the format they use to present the data. Start off on the right foot with a detailed creative brief to clue them in. Here’s how to write one if you haven’t done it before.

2) Don’t Just Dump Your Data on Them

It’s exciting to have a partner who can dive into your data, but that doesn’t mean they’re your personal assistant. Far too often a client will get so excited they’ll send over every single piece of data they have, giving us a veritable ocean of data to wade through. This wastes precious time for the data visualization agency and, ultimately, your organization—the longer they take, the longer you wait. When you deliver data, it should be:

• Decently organized: Make it easier for your data visualization agency to “see” what they’re looking at.
• Complete: We can’t tell you how inconvenient it is to go back and forth in search of a few missing numbers. Clean and sort your data to avoid this.
• A reasonable amount: Sometimes people come to us with three stats and ask us to turn it into a data story. Other times, as we mentioned, it’s an insane database of randomness. Provide a solid data set that gives your data visualization agency enough to work with.

3) Let Them Extract the Most Meaningful Insights

You may already have a story in mind—and you may have the data to support it—but there may be a more interesting angle in that data. (Sidenote: We hate to see people try to retrofit data just because they have a “great” idea. Not only does this result in a weaker story but you risk misrepresenting data, which can hurt your credibility.) You should have filled your data visualization agency in on the project’s goal, so let them help extract the most valuable insights to achieve that goal.  

4) Know Your Terms

There’s a reason you’re using a data visualization agency, and it’s likely because you are not a data scientist or designer yourself. That’s OK, and you’re doing the right thing. But when it comes to collaborating on a data project, it’s important to know the basic lingo. This helps clear up miscommunication and ensures you’ll all stay on the same page. If you need a little help:

• Check out our guide to the most common charts and graphs: It’ll help you learn the difference between a pie chart and a donut chart so you don’t have to call it “that circle thing.”
• Learn about different visualization formats: Here’s a great rundown of the differences between data visualization, infographics, animated infographics, interactive infographics, motion graphics, and video.

5) Collaborate on the Story

Once the most interesting insights are uncovered, it’s vital to shape a narrative that will communicate them with the most impact. This is a highly collaborative process. You know who you’re trying to reach—how they think, what problems they face, the language they use—so you should help guide your data visualization agency. We believe the best story wins, no matter who it came from.  

6) Share Brand Guidelines

We can’t tell you how frustrating it is for a data visualization agency to put their heart and soul into a beautiful visualization only to be told—after the fact—that it doesn’t align with brand style. Make sure you share this information from the start. Conversely, if your brand guidelines don’t include directions for data visualization, this is the perfect opportunity to create some rules.

7) Identify Your Editors

Careless mistakes are the quickest way to ruin your data visualization’s integrity. Sometimes it’s a transposed number. Sometimes an entire chart is missing. With so much back and forth, these things can fall through the cracks. Make sure you have designated “editors” on both teams that will be accountable for reviewing and ensuring accuracy. (Note: This doesn’t have to be a proper “editor.” It may be a project manager or producer.)

8) Be a Good Creative Partner

There are many moving parts in a data project, and issues can come up at every stage. To help keep everything running smoothly, follow general rules to be a good collaborater:

• Designate a point person: This should be the contact to interface with your data visualization agency whenever they have a question or problem to solve.
• Get sign-off at every stage: Make sure all stakeholders have reviewed and approved content at each stage, from copy to design.
• Be responsive: Be respectful of your partner’s time. Don’t leave them hanging on questions or delay sending over important documents.
• Offer constructive feedback: Consolidate your feedback from stakeholders, and frame it in terms of what works and what doesn’t, instead of what you did and didn’t like.

Follow these tips, and we guarantee your project will be a lot smoother. The only argument you’ll have is about where to get a beer together after your awesome project goes live.

To learn more about the value of data visualization, find out why data-driven storytelling helps brands, check out these 9 great sources of data that are right in front of you, and learn about why our brains love data visualization. Still need some help with your data? We can hook you up.

If you want to tell a powerful story, data is the way to go. Whether it’s proprietary data, industry research, or public data, there are compelling stories all around. But even the best data story can lose impact if it isn’t presented the right way. That’s why it’s so important to choose the right data visualization format for your data.

We find that there is a lot of misinformation or misunderstanding around this topic. Many people think that throwing a few charts and graphs into an article is all they need to tell a good data story. Or they think they can stuff a trillion data points into an infographic and call it a day. While the intention might be right, the execution is so wrong.

We want you to tell the best data stories you can, so we’re breaking down the different types of storytelling formats to help you choose the best for your data. (Note: This isn’t entirely prescriptive, but it should send you in the right direction.)

Data Visualization Formats/Tools

Before we dive in, let’s clear up a few terms to specify what we’re talking about. When it comes to data storytelling, people tend to use certain terms interchangeably (or misuse them entirely), but there are very different types of data mediums and data visualization formats. For the purposes of this post, here’s how we break it down.

Data visualization: In the strictest sense, this refers to the actual visual representation of data. This may mean basic charts and graphs or larger, more complicated visuals. But it is about the visual specifically.

Information design: Information design is the visual representation of information—with no data at all (think of an organizational flow chart). We won’t be talking about info design here, but we think it’s important to understand the distinction.

Infographic: An infographic is a graphic that includes data, copy, and visuals. These elements work symbiotically to tell the story. (That means your infographic may include data visualizations.)

Animated infographic: These are infographics that include motion or animation. These are not interactive (see below), because the viewer doesn’t control the motion or animation.

Interactive infographic: An interactive infographic is any web-based content that lets you interact with the data on the screen. You may scroll over, click, expand, or otherwise manipulate the on-screen data.

Motion graphic: These are animated graphics that tell a story. Motion stories can be told through kinetic text, animated visuals, or both.

Video: This is live-action film, which may also incorporate text, graphics, etc.

Luckily, you have more options than ever to tell your story. But this can also make it tricky to choose which is best.

Before You Choose a Data Visualization Format

There are many elements that influence how you might best present your story. Before you decide on a format, think of the bigger picture. Each of these may affect the route you take.

Goal: Before you create anything or even come up with an idea, you should always know what your goal is. This is just as important to data storytelling as anything else. Are you trying to increase brand awareness? Establish your expertise? Engage your social followers? Some formats can help you achieve these goals more than others.

Story: An effective data story isn’t just a smattering of stats. If you’ve done your job well and teased out the insights, you can craft a narrative to reveal that story. That said, the story you’re trying to tell will very much dictate the data visualization format you choose. Is there a clear message? Are people meant to uncover or assign their own meaning to the story? Are you creating a useful resource? Are you trying to guide them to a next action? Keep this in mind.

Volume of data: This is one of the biggest issues we see over and over. People can go data-crazy sometimes and extract a mountain of data to turn into a story. That’s nice, but you must consider how much data is really required to tell the story. Sometimes you have millions of data points, and that’s OK. Just don’t stuff those into the world’s longest infographic.

Audience: Who are you trying to reach with your data story? Who will be interested in it? What level of knowledge or understanding do they have? What data visualization formats are they accustomed to interacting with? If you are targeting older boomers, for example, a fancy interactive might not be the way to go.

Distribution: Where will your data story live? On your blog? On social? Published on an industry site? How will you drive traffic to the piece? Know this from the get-go. If you are trying to engage people on social, the format you choose sure as hell better be optimized for social. (We once designed a beautiful animated infographic only to find out the publisher’s platform didn’t support the format. Then we cried.)

Choosing Your Data Visualization Format

Each data story is unique, so there isn’t a single rule or formula for choosing the best presentation. However, some are better suited than others to help you achieve your goals.

Data visualization

A strong data visualization can be used alone or as part of a larger piece. The power of strict data visualization lies in, of course, the visualization. A stunning visual is not only aesthetically appealing but lets the viewer “see” the story. Sometimes, a simple data visualization can be even more powerful than a detailed story with additional copy or context.

Good for: Data visualizations are often used as one part of a larger story in an infographic, white paper, e-book, on social, etc. (Simple visualizations are especially useful for situations in which time or attention is limited and you need to tell the story “at first sight,” such as a visual at a tradeshow booth.) 

Example: This simple data visualization is a convenient guide to grilling meat. The data is depicted in chart form, making it easy for readers to get the info they need at a glance. 

To make sure your data visualizations are effective, design them according to best practices. Find out how to do that with our Data Visualization 101 guide.

Infographics

Infographics are particularly useful to communicate in a simple, clear, and easy-to-understand way. They are aesthetically engaging and easy to share, making them a great tool for brand awareness. Publishers have become increasingly interested in infographics, as they visually enhance stories. Additionally, panels or slices from infographics can be repurposed as microcontent, helping to further promote the piece of content and give you more bang for your buck.

Good for: Social, content marketing, visual aids, editorial publishing, etc.

Example: This Jobvite infographic on paid parental leave tackles a relevant subject for their target audience and presents data in an easy-to-understand manner. 

Learn more about how to craft an effective infographic narrative and get publishers to fall in love with your infographics.

Animated infographics

Animated infographics have all the same benefits of infographics, but the addition of motion makes them more attention-grabbing. They are a good option if you want to mix up your content and experiment with motion without creating a full-on interactive or motion graphic. Like infographics, motion elements can also be repurposed in other areas.

Good for: Social, advertorial, or editorial, specifically situations where you need to grab attention to attract people to the content.

Example: We helped Newscred visualize the results of their content marketing survey by creating an animated infographic. The modular design allowed panels to be used individually or together.

Learn more about the power of motion in visual content.

Interactive Infographics

Interactive infographics are ideal for instances in which you have an enormous amount of data that needs to be easily navigable. You may present that as an exploratory interactive, in which users can dive into the data to extract their own meaning, or as a narrative interactive, in which you guide them through the interactive. Interactives require the viewer to actively engage by physically inputting information or manipulating data. It also encourages the viewer to spend more time with the content.

Good for: Engagement, deep data exploration, and immersive storytelling.

Example: We turned 10 million cells of data from a Northwestern University Qatar survey into a clean, colorful, easy-to-navigate piece. The interactive allows for exploratory storytelling, where the user can decide what data they are most interested in.

Learn more about the benefits of interactive stories.

Motion Graphics

Motion graphics are particularly useful when you have an abstract concept or a story that needs more context to connect the dots. It is a contained storytelling format, which makes it easier to deliver a succinct story or direct message. It is also passive, allowing the viewer to sit back and absorb.

Good for: Telling a succinct story in a short amount of time.

Example: We collaborated with NBC Universal to create a motion graphic encouraging Americans to reduce food waste, using data from the Natural Resources Defense Council.

Check out 6 awesome examples of storytelling through motion graphics.

Video

Video has become an increasingly popular medium, largely thanks to social platforms. Like motion, video can also incorporate text, graphics, and data visualization and offers an opportunity to demonstrate creativity. However, perhaps its strongest selling point is its ability to put a “human” spin on data stories by putting actors front and center.

Good for: Telling a succinct story in a short amount of time, especially when you are trying to create an emotional connection with the content.

Example: We partnered with Foodbeast and Totino’s to help tell a data story about Americans’ binge-watching habits. Using the actual Totino’s product as a visual challenged us to come up with creative data visualization.

Learn more about why humans are so attracted to video.

Remember: Story First

No matter what data visualization format you choose, remember the basics that will make it succeed: Strong data and a strong story. If you need a little help in that area, here are some things that might help:

• Learn more about why data storytelling is so powerful.
• Find out how audience personas make sure your data stories will capture people’s interest.
• Check out these 9 sources for great data.
• Dive deeper into data storytelling with our book Infographics: The Power of Visual Storytelling.  

If you need a little help with your data storytelling, we’d love to work together.

The Value of Data Visualization was created for presentation at the Richmond Federal Reserve’s “Unleashing the Power of Local Data” conference.

People have less time (and patience) to consume information, so they need brands to communicate as efficiently as possible. Enter the explainer video. Whether you’re introducing a product or service, demonstrating how to do something, or welcoming someone to your site, an explainer video lets you quickly and easily explain who you are, what you do, and why people should choose you. They’re also something that any brand can create, no matter the industry, product, or service. In the right hands, an explainer video can transform into much more than an informational video. It can become a compelling piece of brand storytelling. Need proof? We have 50 explainer video examples that demonstrate exactly that.

50 Great Explainer Video Examples

Whether you go with a simple motion graphic or a high-production live-action video, there are many ways to create interesting explainers. Here, we’ve rounded up dozens of explainer video examples that showcase how versatile this medium can be. From food and finance to tech and personal care, we hope these videos inspire you to create a fresh and unique explainer video of your own.

1. “Why Mozilla” by Mozilla

2. “AI Translations Your Business Can Trust” by Unbabel

3. “NextGlass” by breadnbeyond

4. “Super Sync Sports” by No Mint

5. “Instagram Direct” by Delve

6. “Unwanted Tracking Is Not Cool” by BLACKMATH

7. “British Gas” by CHI & Partners

8. “Our Blades Are F***ing Great” by DollarShaveClub.com

9. “Stampsy Launch Video” by Twistedpoly // Nejc Polovsak

10. “Don’t Be A Pitch” by Vireo Films

11. “Dumb Ways To Die” by Passion Paris

12. “Shark Wrap” by Video Brewery

13. “Hummingbird” by Hummingbird

14. “Lettuce App” by Brandon Wall

15. “Introducing Whistle” by Manifold

16. “Poo-Pourri Second Hand Stink” by A76 Production

17. “LivePlan Explainer” by Palo Alto Software, Inc.

18. “One Is One…Or Is It?” by TED-Ed

19. “Affordable Health Care Act Explained” by TurboTax

20. “Skype for Business: Simplifying Communication in the Cloud” by Office Videos

21. “STFU” by Unbabel

22. “Web Standards for the Future” by W3C

23.” Text Me Up App” by Thinkmojo

24. “Visa Purchase Alerts” by Column Five

25. “The Happy Home Company” by Doug Ludlow

26. “Get Rewarded for Not Texting While Driving” by XL Team

27. “Just The Cream” by BriefMe

28. “Blackbaud: Essential by Impact” by Blackbaud

29. “Create Your Own Business” by Squarespace

30. “Meet Zendesk Chat” by Zendesk

31. “What is Ellevest?” by Ellevest

32. “The Value of Data Visualization” by Column Five

33. “Helping Blind See” by Be My Eyes

34. “Smart Mailbox” by Epipheo

35. “Salesforce Desk.com” by Oddfellows

36. “Visa Fingerprint Scanner Technology” by Column Five

37. “hey guy, we are hims. it’s easy.” by Hims

38. “Wondering how Thinx work?” by Thinx

39. “Intralogistics” by UPS

40. “Collect by WeTransfer” by WeTransfer

41. “Digit” by Giant Ant

42. “Meet the new Dropbox” by Dropbox

43. “How to Create an Animated GIF in Photoshop” by Adobe Creative Cloud

44. “The Explainer: The Case for More Silent Meetings” by Harvard Business Review

45. “BYOB Lumberjack Party” by Motion Authors

46. “Gusto: Payroll, Benefits & HR for the Modern, Busy Workplace” by Gusto

47. “Logitech Monitor Cloud Awareness” by Logitech

48. Invoice with Google Calendar by Column Five

49. “How Warby Parker Glasses Are Made” by Warby Parker 

50. “How It Works” by Olio

How to Create Your Own Explainer Video

If you’re feeling inspired to bring your own explainer video to life, make sure to follow best practices at every stage of the process. Here are some resources you might find helpful.

• Learn about the keys to a strong explainer video. From visuals to voiceover, here are the 10 things your video will need.
• Make sure an explainer video is what you actually need. Here’s how to find out.
• Write a strong script. Use our guide to tell a strong story in your script.
• Choose your design style. Whether you do live-action video, motion graphics, or a mix of both, follow the best practices in the Content Marketers Guide to Brand Video.
• Make sure it’s the right length. Here’s how to figure out how long your explainer should be.

But if you don’t have the resources or time to tackle your next explainer video, bring in extra support. Check out our tips to choose the right video agency for you, or chat with us. We’re always happy to talk about any ideas you might have.

We’ve been in the marketing game for over a decade, and we’ve seen it all: the trends that come and go, the startups meant to be the next big thing, and a couple of economic downturns. But one thing has stayed the same: the best way to get real results that you can measure—and brag about—is to approach marketing with a clear strategy and a deep understanding of your market and audience. How do we know? Because we’ve helped our clients win in big ways with this philosophy, no matter their industry or challenge. But we don’t gatekeep successful strategies for our clients only. We want to see more good marketing in the world, so today we’re breaking down some of our best content marketing case studies, sharing our approach, and offering helpful takeaways you can use to win too.

5 Content Marketing Case Studies You Can Learn From

How do you navigate problem-solving? Market competition? Stagnancy? Here’s how we helped five brands face their challenges head-on—and get great results. 

Case Study 1: Bloomreach’s Paid Media Strategy Beats Goals by 30%

The challenge: Bloomreach is a platform that personalizes the e-commerce experience. To scale, they needed to grow both brand awareness and brand equity among new audiences, so they approached us to create their first-ever brand campaign around a single idea: “Be Limitless.”

What we did: To start, we built out a multi-channel paid media strategy to engage the right audiences on the right platforms. Our goal was to deliver the “Be Limitless” messaging across as many channels as possible while maximizing spend and increasing ROI. 

To do this, we focused on specificity. By using geofencing, historical data, and targeted job titles to segment the exact audiences Bloomreach wanted to reach, we could concentrate our efforts and tailor our approach to each channel/audience. 

We partnered with specialized vendors to deploy the campaign across a multi-channel buy, including digital channels, connected TV, programmatic channels, podcasts, and more. But we didn’t set it and forget it (a common mistake we see marketers make). To maximize spend, we used a test-and-learn approach, continuously testing and iterating campaign content to improve results in real-time.

With this approach, the campaign was a measurable success. 

• 10% of target account list moved from ‘unaware’ to ‘aware’
• 13 million impressions (beating campaign goal)
• $10 average CPM
• 429,000 completed audio listens at an average cost of $0.03 (vs. national average $.02 – $.05)

The takeaway: If you want to connect with your audience, segmentation is key. (See our guide to identifying your audience if you’re not exactly sure who your audience is or what they want.) Once you have a clear understanding of their drivers, you can identify the best distribution channels and test messaging

Case Study 2: VideoAmp’s Site Rebrand Increases MQLs 850% in One Month

The challenge: VideoAmp is a software and data startup. After raising Series C funding, they needed to position their brand for growth. However, their site did not tell a compelling brand story to engage visitors.  

What we did: To change the narrative, we created a UX-optimized website to communicate their refreshed brand story and make their brand stand out in a competitive market.

However, before we drafted any website wireframes, we needed to dive into the core of their story, so we revisited VideoAmp’s brand strategy to clarify goals, understand their brand heart, and craft fresh messaging. 

To bring the brand to life on the site, we crafted a clean and sophisticated aesthetic with a black-and-white color palette punctuated by intentional uses of color. We also incorporated animated visualizations to add movement and excitement, emphasizing VideoAmp’s focus on data-based solutions. 

With a streamlined story brought to life through a cohesive visual identity, VideoAmp made it easier for site visitors to understand what the brand does and why it’s different. Once launched, it was clear the fresh website delivered the desired results, helping VideoAmp garner:

• 850% monthly MQL increase (goal was 200%)
• $1.4 billion funding (raised since the web relaunch)
• 2 awards (Awwwards Honorable Mention and a Mobile Design Excellence Award)

Although most people consider a website redesign to be a purely aesthetic endeavor, VideoAmp’s case study showcases the importance of distilling a brand story and bringing it to life through every tool: words, design, and UX.

The takeaway: Your brand heart is the foundation of your entire brand story, so it’s crucial to have clarity and alignment about who you are and what you do. See our guide to find your brand heart (including purpose, vision, mission, and values), then look for ways to turn your heart into content that communicates your core story. 

Case Study 3: Dropbox’s Talent Campaign Increases Market Perception by 7%

The challenge: Dropbox is a reliable, private, and secure file-storing service that lets millions of people store their most important content. They are constantly creating new and exciting products to expand the brand, but they need an ever-growing team of employees to help them scale. Unfortunately, in the competitive tech landscape, attracting top talent is harder and harder. 

What we did: If you want to attract the best and brightest in your field, you need to tell the story of your employer brand: What are the benefits of working for you? What is your culture like? Why is working for you different than working for your competitor? To uncover this information about Dropbox, we embarked on an extensive research journey to understand employer brand perception from both inside and outside the company. This included an audit of their current perception, as well as surveys of current and even former employees to understand what differentiated the brand (according to the people who work there). 

This helped us uncover a key narrative: “We believe the world can work better.” With this foundational idea, we built out five key messaging pillars to build content around. Through multiple channels, we deployed a campaign to highlight Dropbox’s mission-driven culture of autonomy, flexibility, and diversity.

This revamped employer brand story proved to be a massive success, helping Dropbox plant its flag as one of the best brands to work for, as demonstrated by:

• 7% increase in market perception
• Named #1 Best Place to Work Remote (according to CBS News)
• 4.5 Glassdoor rating (up from 3.7)
• 2:32 min Average Session Duration on the jobs site

The takeaway: Understanding and leveraging your unique strengths and values is the secret to attracting the right people. But to effectively articulate this, you need to build out a strong Employer Value Proposition. See our guides to distill your EVP and translate it into unique content across channels. (For more details about this particular case study, find out what you can learn from Dropbox’s campaign.)

Case Study 4: Teach For America’s Paid Media Campaign Surpasses Goals by 124%

The challenge: Teach for America is an organization that finds outstanding leaders to teach in low-income schools, but they have struggled to recruit more teachers—falling short of their goals for seven years. To turn things around, they asked us to help enhance their paid media outreach strategy. 

What we did: TFA had a sizeable budget of $1.2 million. But in any paid media strategy, it’s not about the budget; it’s about optimizing that budget to reach the right people. 

We started with a research phase to review previous campaign results, audience analysis based on past performance, media vendor information, and TFA historical application data. This information helped us make more informed decisions about budget allocation and—most importantly—influenced an aggressive test-and-learn campaign. 

Like TFA, we know the value of education, so we ran tailored experiments to test, learn, and revise campaigns based on insights. By continuously testing and reallocating resources to the most effective channels, we maximized ROI and gained valuable insights for future campaigns, ultimately outperforming their recruiting goals by 124%. 

The takeaway: If you want to win, you need to adopt a data-driven and flexible approach. Set up short-term experiments to gather data, A/B test, and continue to iterate. AI tools can be a huge benefit here, as they can help you A/B test messaging to optimize your impact, build lookalike audiences, and more. If you haven’t experimented with AI, start with our ultimate guide to AI and download 75 free prompts to build an AI-driven content strategy.

Case Study 5: Course Hero Becomes an Industry Expert by Creating 600 Infographics

The challenge: Course Hero is an online learning platform that helps students access course-specific study resources contributed by a community of students and educators. To establish themselves as a trusted resource for students, they wanted to create a series of infographic study guides that distilled popular novels into single infographics. The problem? They wanted to create hundreds of them. 

What we did: All content takes effort to produce, but visual content at that scale can be a tremendous lift. Fortunately, having actually written a book on infographics, we knew how to scale production without sacrificing quality. 

To start, we developed a visual language and style guide to ensure quality and consistency for every infographic produced. We also established a core team and structured review process to maintain cadence, creating a well-oiled machine that would not be bogged down by unnecessary issues. 

Ultimately, this approach allowed us to create 600 infographic study guides for famous novels over the course of three years, driving healthy traffic to Course Hero’s site and earning thousands of shares and followers on social media (including nearly 40,000 followers on Pinterest).

Best of all, by creating this epic library of study guides, Course Hero was able to follow through on their brand promise in a tangible way by helping support students in their educational journey. 

The takeaway: In content marketing, consistency is the key to creating a relationship with your audience. You need to show up for them regularly to become a trusted resource. To do this, you need an optimized production process that ensures you can create a steady volume of quality content. We’ve made or witnessed just about every mistake in content creation, so we know exactly what pitfalls to avoid. See our guide to master content creation for our best tips to work quickly and effectively, 

How to Get Better Results from Your Own Content

We hope these takeaways have been helpful as you continue to pursue your content marketing efforts. Just remember: No matter how big your budget or team, you can only be truly successful with a measured, intentional approach.

• Start with your content strategy. You need a documented content strategy to guide your efforts. (We’re always surprised by how many brands do not have a documented strategy.) To make sure your goals and team are aligned, use our free content strategy toolkit.
• Stay flexible. No strategy is set in stone. Although it’s important to have a documented plan, that plan may change. Review your strategy quarterly (at least) and update as you gain more insights from test-and-learn campaigns. 
• Use the right tools to work smarter. AI cannot replace marketers, but it can help you do your job more effectively. Learn about the many ways you can implement AI and explore the tools that may serve you. 

That said, don’t get discouraged if you continue to hit roadblocks. As industries change and markets shift, sometimes you need a little extra support to navigate challenges. If you’re looking for a partner, use our tips to find an agency with the right expertise (or find out what it’s like to work with us). Whether you need help or not, remember that the most important trait you can cultivate is curiosity and a willingness to experiment. The more you try, the more you learn, and the more you’ll grow.