Tag: data

Use of Infographics in Content Marketing

Posted on by SGA SGA

Every person takes in information and learns differently. Thus, you have to have different tactics to reach everyone in your audience.

At SGA, we know that some people remember what they read rather than what they hear; others learn when they see things in writing. Then there’s the 65 percent of us who are visual learners and process information based on what they see. That’s why infographics are so popular and a great addition to your content marketing.

What are they?

Infographics make use of a mix of text and a variety of visual images in order to tell a story and convey statics and other information. Such visuals include charts, diagrams, graphic designs, maps, drawings, and colors. A good infographic is visually engaging, fits into your content marketing strategy, and supports your marketing goals. Bad infographics distract, are confusing, and muddle the message.

Using them

Always keep your target audience in mind. Infographics can be an incredibly valuable tool if used correctly, but it must be compelling and relevant to your audience. If it is not, it becomes just a novelty. Remember, if your customer is not going to care your content, it will not matter what it looks like visually.

Keep it simple. The goal of an infographic is to create quick bites of information that can be quickly digested. As well as visually appealing, it must convey accurate information. If the graphics look great, but the content is correct, this will have negative effects on your brand.

Having too much accurate information all over the design weighs heavily on the overall visual appeal. Too much text makes it just as difficult for someone to digest as a lengthy written article.

Make them shareable

Most infographics are created for online publishing: websites, blogs, social media. When you decide to incorporate infographics into your content marketing strategy, make sure they are engaging and appealing enough that consumers will want to share them. Creating evergreen infographics allows for republishing of materials.

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4 Simple Ideas to Improve Outreach

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It’s difficult to imagine a time before randomized trials and data. But as an article in the December 12 issue of the Economist points out, before the 20th century, “The sick were wise to stay away from doctors. Medical treatments were often worthless and sometimes dangerous.”
Then in the 1920s, English statistician Ronald Fisher used randomized controlled experiments to test the effectiveness of fertilizer on farms, and quality and production escalated. The medical field soon picked up the method. More than any single discovery, controlled experimentation contributed to the 20th century’s miraculous increase in lifespan.

In the realm of public policy and outreach, this technique can be tricky. Changing behavior is often hard to observe and quantify. What’s more, local government programs don’t have the budgets for lengthy experimentation and controls.

But things are changing. Online media provides the ability to conduct small and inexpensive controlled experiments that allow us to determine if people are taking the initial steps towards behavior change. For example, we can test degree of awareness, intent to change, influence of social norms and more.

In 2015, SGA began testing out how online experiments can help build better, more reliable outreach programs. Here are four simple, but important, lessons we’ve learned:

  1. Reach beyond likes and unique visitors. The biggest problem using social media likes and website visits as a proxy for success is that you don’t know why people took the action. They could have been searching for your content and found it engaging. Or they might have randomly clicked on your website during a Google search and quickly jumped off, never to return again. You just don’t know. While building a strong foundation of fans is important, it’s just the beginning. To build a community, you need to test how engaged your fans are through controlled messaging experiments.
  1. Embrace A/B testing. If you really want to understand the value of your likes, you need to see if they are repeatable.  The key is to run two sets of posts—an A version and a B version. (You can also run multi-variant tests if you want to move more aggressively.) Then see how each performs with your community over time. You can set these up on social media, websites and e-newsletters. For e-newsletters, send the two variations to a random subset of your subscriber list a few days before you intend to send out the newsletter. Then send the one that does best to the rest of your list.
  1. Turn data into insights. Once you have some data to work with, you can look at the demographics of the people who engaged with your content as well as the content that got the best response. Facebook and Twitter insights and Google Analytics can tell you loads about your followers. Understanding the type of content that resonates with them will help you understand how to inspire them with behavior change messaging. This data allows you to paint a more robust picture of your audience, which you can incorporate into outreach both offline and online.
  1. Create a call to action. Find the route to engagement by asking your fans to do something. When determining your call to action, be sure it is something you can measure and start small. Ask fans to opt in to receive emails or post their own content showing actions they have taken. One of our projects for the Orange County Stormwater Program asked people to post photos of how they were saving water in their yards. By having residents show their actions, it verifies the behaviors taken and starts to build a social norm for the action—and engagement in general.

In 2016, we will see more and more emphasis on data as online marketing’s balance of art and science continues to demand more of the science. Business and commercial marketing has already shown this. With simple experiments, you can better understand your audience, their motivations and whether they’re buying your program’s message or merely window shopping.

A Surprising Obstacle to Recycling Paint

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The questions were simple:

  • Do you know you can recycle paint?
  • Do you do it?
  • Why or why not?

But when we asked Leo, a middle-aged man who had just finished painting his house, the answers were more complicated.

Leo had heard he could recycle paint. He wasn’t doing it, though, because he had also heard that he would need to show identification and pay a fee — two things in short supply. So he stacked all the paint in his garage and stopped thinking about it.

Recently our friends at PaintCare, a nonprofit dedicated to increasing paint recycling, asked us to conduct a survey to figure out what Latinos thought about properly disposing of their unused paint. We sent a team of surveyors out to Latino communities in Santa Ana, Los Angeles, Riverside, Ontario, Chino, Riverside, San Francisco, San Jose and Westminster in California as well as Denver and Thornton in Colorado.

What we found surprised us. A whopping 77% of Latinos surveyed kept their leftover paint in storage. An even larger 79% were unaware of the many locations that accept unused paint. (Check out PaintCare’s location finder and see for yourself.) And nearly every person surveyed was just like Leo. They believed that an ID and fee would be required to recycle paint. For the record, dropping off unused paint at one of the PaintCare locations is both free and anonymous.

Armed with data on the attitudes and beliefs of the Latino community, we’re ready for action. Our next step? To create a pilot program to educate and inspire Latinos to get that paint out of their garages. Stay tuned…

Naming our Data: Bringing Data to Life through Characterization

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It often began with the question, “Have you heard about IPM?”

You yourself may be wondering, What is IPM?

For the past year, we worked under a CalRecycle grant to promote Integrated Pest Management (IPM) to the City of Thousand Oaks and the neighboring cities of Camarillo and Moorpark. We got to work and surveyed a number of local residents to gauge their understanding of IPM, where they struggle in the IPM process, and to assess their willingness to try IPM practices.

***

A few months ago, we mentioned that data on its own doesn’t mean a whole lot. Often times, due to an overwhelming amount of data collected, not much is done with that data. We decided to take the extra step with our findings, and identified how our data might prove useful for the City of Thousand Oaks in improving its strategy.

Meet Diane, Wendy, Frank, and Oscar:

Don’t be fooled, these aren’t actually real people—they’re personas. Using our data, we constructed these personas to help us create an effective outreach strategy for Thousand Oaks.

Just as we did in the case of Downtown Long Beach, we segmented our collective of data and transformed our findings into an actionable strategy for IPM outreach. By transforming data into character profiles, we were able to see how it applied to different segments of the community’s population.

With Diane, Wendy, Frank, and Oscar as our guides, SGA and the City of Thousand Oaks were able to create strategies and decisions based upon which persona our audience was most comparable to:

For the Wendy Willings, we focused on simply asking them to try IPM.

For the Diane Do-Gooders, we created a way for them to share their positive experiences. We gave these Dianes the opportunity to be champions of IPM amongst their neighbors.

For the Franks On-the-Fence, we recruited the Wendy Willings and the Diane Do-Gooders to influence Frank to give IPM a try.

For the Oscar the Outsourcers, we made them aware that toxic pesticides can cause serious harm to the community’s water resources and health, and encouraged them to pursue less toxic pest control services.

Thanks to these characters, we were able to use our data to simplify our target community in a simple, concrete, and memorable way.

How We Turned Data to Narrative in Downtown Long Beach

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Did you know that between 1902 and 1969 the Pike in Downtown Long Beach was the most famous beachside entertainment area on the West Coast? So famous, in fact, that Midwesterners wanting to escape the brutal winters flocked to the warm seaside port city, helping to coin its moniker, “Iowa by the Sea.” Then, oil was discovered, aerospace companies moved in and the city became known for little else than the industries it hosted.

Today, Long Beach has emerged as a vibrant, ethnically diverse, pet-friendly and bike-friendly city. Often hailed as one of the best cities to live in the US, Long Beach is the next Oakland. Despite these modern-day accolades, Downtown Long Beach remains somewhat unknown to non-residents, and some say, overshadowed by the glitz and glamour of Los Angeles.

SGA partnered with Downtown Long Beach Associates (DLBA), a nonprofit dedicated to improving business activity in the area, to find an explanation for this discrepancy in perception. DLBA has been critical in transforming Downtown Long Beach into a place where locals thrive and people want to visit. “Creating a vibrant urban center isn’t achieved through creativity alone,” says Kraig Kojian, President and CEO of the Downtown Long Beach Associates (DLBA). “Data is essential so that we create grounded policies and make reasonable decisions.”

“SGA tackled difficult questions: What makes people visit DTLB? How we can harness our biggest fans to expand our base?” explains Kojian. “Finding the answers to these questions can ultimately foster an engagement that lifts up our most devout supporters while bringing those on the fence in.”

We started with a survey to gather hard data that would give us a sense of how Downtown Long Beach (DTLB) visitors “use” the area. We spoke to 323 visitors at 10 different downtown locations in fall 2014. We segmented them into residents, visitors, tourists and workers and asked about their frequency of visits, types of businesses they supported and how they felt about recommending DTLB to a friend or someone they know, among other things.

So we gathered the data. Now what? Data in and of itself don’t mean a whole lot. The trick with these types of research projects is to distill the metrics into narratives that tell a story.

In DTLB, we found that residents were the biggest promoters of and spenders in DTLB; visitors had the potential to bring in more revenue as they are large in numbers, come frequently and could potentially settle down in DTLB; and most importantly, residents and visitors liked DTLB for the authentic experience that gives the town its vibe as a hip enclave of young, creative professionals who love their community.

“Whittling down complex data into simple concepts is what is expected from data analysis,” Kojian says. “Data that can’t be shared across platforms and explained to different groups—from residents to board members to other organizations—is rendered pointless. SGA’s staff understood that the ability to share this information was key. We look forward to working with them for the next two years on upcoming surveys.”

We look forward to it, too. With big ticket retailers such as H&M and Nike planning on moving into the Pike and a new hip foodie restaurant popping up in DTLB every week, we expect visitors to become as invested in Long Beach as locals already are.

Bringing Sexy Back to Data

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Nate Silver has certainly given the mundane topic of data a spanking new makeover with his book, The Signal and The Noise. Silver, who correctly predicted the winner in 49 out of 50 states during the 2008 presidential elections, said he was able to make a dent in political forecasts only because other political pundits were so bad at it.  Then he pointed to other industries such as finance and weather forecasting where predictions fail. It’s not all hopeless, however.

Silver has made data fun and buzz-worthy. He has recently infused data into such topics as finding the best burrito in America. The process to determine the 64 burrito-selling establishments nationwide that would be in the bracket involved something called a VORB, or Value Over Replacement Burrito, score, according to his blog. The judging system was based on 20 possible points in five categories: tortilla, main protein, other ingredients, presentation and overall flavor profile. The results led to a flurry of reactions (not all positive) on social media.
Continue reading “Bringing Sexy Back to Data”

Mo’ Data, Mo’ Problems

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Is more data always better? Do we have a natural tendency to make up patterns and trends where there aren’t any? Are computers never wrong?

These are some of the questions posed by data nerd Nate Silver, author of our latest book club entry, The Signal and The Noise.

In his book, Silver uses examples in failed predictions ranging from the 2008 financial crisis to the Fukushima earthquake in Japan to illustrate the following three points: his humble roots as an accountant, poker player and then baseball stats number cruncher, Silver hit the big time in 2008 by correctly predicting the winner in 49 out of 50 states during the presidential elections. His blog featuring stories using data and statistics, fivethirtyeight.com, was first bought by the New York Times and more recently, ESPN. Let’s just say he brought sexy back to data. Continue reading “Mo’ Data, Mo’ Problems”