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State of the USA Website Concepts and Strategy August 20, 2008


Mary Jo

Akron, OH

Mary Jo

Akron, OH


Today

Tomorrow

Mary Jo is a single parent living in suburban Akron, OH. She has an Associate’s degree and works as an office manager at a law firm that specializes in class action law suits. She earns a modest salary. Jason, her son, is dangerously overweight and was recently diagnosed with type 2 diabetes. Mary Jo is by no means an expert in medicine, but her son’s diagnosis has motivated her to learn how and why her son became sick. She knows there has been a lot of press about obesity and she just wants to find out what she can do to help her boy. She is highly motivated, but also very busy and distracted.

Mary Jo is a single parent living in suburban Akron, OH. She has an Associate’s degree and works as an office manager at a law firm that specializes in class action law suits. She earns a modest salary. Jason, her son, is dangerously overweight and was recently diagnosed with type 2 diabetes. Mary Jo is by no means an expert in medicine but her son’s diagnosis has motivated her to learn how and why her son became sick. She knows there has been a lot of press about obesity and she just wants to find out what she can do to help her boy. She is highly motivated, but also very busy and distracted.

Mary Jo is technically savvy and an avid Internet user. However, she is also skeptical, not trusting much of what she reads, especially on the Internet. Her work at the law firm has shown that, with the right resources, determined individuals can affect change. She seeks answers and the first place she looks is online. The only uninterrupted free time she has in the day is her 45 minute lunch break. She will use this time to perform her online research.

Mary Jo is technically savvy and an avid Internet user. However, she is also skeptical, not trusting much of what she reads, especially on the Internet. Her work at the law firm has shown that, with the right resources, determined individuals can affect change. She seeks answers and the first place she looks is online. The only uninterrupted free time she has in the day is her 45 minute lunch break. She will use this time to perform her online research.


“Jason is sick and I need to know why.”

“Jason is sick and I need to know why.”

She opens her web browser and uses Google to do some online searching. She

Mary Jo performs a Google search for keywords “overweight children data in America”

searches for the keywords “overweight children data in America” and discovers a

and discovers the State of the USA site (SUSA), in three of the top five results. The

variety of sponsored links that make her skeptical. The first result non-sponsored is the

first non-sponsored result listed is “Childhood Obesity in America—the State of the

CDC’s obesity and Overweight website, which provides a map listing the number of

USA.” Mary Jo clicks on the link and is delivered to the State of the USA page with an

obese Americans by state, but not by age. This doesn’t help.

interactive map that is clearly labeled: “Children ages 8 to 16 obesity rates in the 50

She downloads a PDF on the page. The document explains where the data comes from in two limited paragraphs that contain a broken link. The rest of the document is made up of simplistic tables and charts that have nothing do with her needs. Frustrated, she closes the PDF and trashes the file. She finds on the lower portion of the CDC page two links with the word “child” in them. The first takes her away from the CDC page and lands her on the Journal of the American Medical Association (JAMA). She does find information but it is written in statistical jargon that she doesn’t understand. The second link takes her to another part of the CDC website. There she finds an article about the prevelance of overweight children and adolescents, 2003 – 2004. There is a link to a table at the bottom of the page with three rows of data and columns that span the years 1963 to 2004.

U.S. states, 2008.” The map shows her that the problem is not localized—it is a national problem. She moves her cursor over the map and notices that the states are clickable. A panel appears when she hovers over Ohio displaying information specific to the state. She selects Ohio and the map zooms in on the state. She selects her town and sees that the children who live there, hers included, have an obesity rate of more than 20%, but the county, which includes Cleveland, is only 11%. She notices a module containing links to articles that cite this data and wants to click through it but doesn’t want to lose her map. As she is thinking about this she notices a “save this data” button.


Beneath the table there is a fact sheet which she clicks on…

pain points and concerns recommendations

• Search results do not yield relevant information. • Because the CDC is a government website that Mary Jo generally trusts, she gives it an honest try and dives deep, only to discover her search yields little information about her problem. She begins to get frustrated.

• SUSA should lay claim to the words “data,” “statistics,” “stats,” “graphs,” and “charts” in organic search results. • SUSA should provide intuitive and clear labels for all of the maps, graphs, and charts that it provides.

Mary Jo Akron, Ohio

12:00 pm Wednesday

Today

Mary Jo

Scenario

Akron, Ohio

12:00 pm Wednesday

Tomorrow Scenario


“This is going from unhelpful to just plain useless.”

…and finds multiple links to a variety of dates based on content type (e.g. news releases, fact sheets, and media advisories). The most recent news releases are from 2005. The most recent fact sheets are from 2008. She clicks on “2008 Fact Sheets and Media Advisories” and discovers four news releases that do not give her any more information. At this point she has HAD IT with the CDC and is losing faith in their ability to give her the information she needs. She closes her web browser in frustration.

“Hmmm ... May this will help.”

Curious and needing to save the map before she moves on to more research, Mary Jo clicks on the “Save this data” button, which displays in-page login fields and a “Register Now” button to save her work. This is her first time on the site so she clicks “Register Now.” A larger in-page box appears above the map (she has not left her data page) with fields requesting her e-mail address and a password. She provides the required information, which is accepted. Her that her new account has been created and the map is now saved. She closes the module and returns to the map. The map now has messaging showing her it is saved and she notices a few new elements on the page. She clicks on the article she was going to go to.


pain points and concerns

• She has now spent a total of 20 minutes, nearly half her allotted time, on the CDC Website and has turned up nothing. • She initially trusted the CDC, which is why she chose their site over sponsored links,

recommendations

but it has let her down and she no longer believes the site will deliver accurate and • SUSA should have related resources, such as articles, associated with the

current information. • Trust will be a key attribute of the SUSA site. To deliver that trust SUSA must provide accurate, updated, and easily accessible data that uses proven and understandable methodology. This means that SUSA must explain its data and sources in a way the

Akron, Ohio

maintain their position on the SUSA site. • SUSA should have a function to allow the user to store data he or she is browsing.

average user would understand.

Mary Jo

charts and graphs. • SUSA should make these items easily accessible but allow the user to

12:10 pm Wednesday

Today

Mary Jo

Scenario

Akron, Ohio

12:10 pm Wednesday

Tomorrow Scenario


“Why do I have to pay for this information?”

Mary Jo returns to her Google results. She scans the different sponsored links but realizes that most are either diets for sale or organizations unfamiliar to her. She now starts browsing the rest of the standard results. She finds a promising article at what seems to be a Nature.com subsidiary, the International Journal of Obesity. The abstract offers what seems to be a promising data set she might be able to understand. When she finds the link for the full text she is prompted to pay $32.00 for the full article or sign up for a subscription. Neither of these options are viable: why risk paying for something that might not provide her with what she needs? She is put off by this and again thinks that the government should do more to provide this type of data, free of charge.

“I can’t believe how easy this is.”

The link delivers her to an article that discusses schools in counties and states throughout the United States that are adopting policies to get kids trimmer and healthier. These include simple solutions such as cashless cafeterias, removing soda machines, and increasing and updating Physical Education programs. Mary Jo clicks on the “save this article” link and the page delivers messaging that the article is now bookmarked. Mary Jo returns to her map and zooms out to the United States again; she re-zooms into the states she remembers from the article that have been successful in reducing childhood obesity. She quickly discovers they have much lower numbers than her community. She now wants to see if the policies she read about can be attributed to the reduction. She goes to a date slider and moves it back five years, noticing the obesity rates were higher in the past. She deduces that the policies must have something to do with it. She converts the map to a bar graph using an easily found “displays” button on the map. In two clicks she has a bar graph displaying the county’s reduction of obesity rates over time. She saves the new graph and saves one other jurisdiction.


pain points and concerns

• Mary Jo is having trust issues with paid-for sponsor links on her Google results. She assumes that the results are going to try and sell her something when relevant data should be available for free. • Mary Jo reads the teaser article which gives her a sense of enthusiasm, but she is quickly disheartened when finds she has to pay for the rest.

Mary Jo Akron, Ohio

12:20 pm Wednesday

recommendations

• Not only data is shown but where the data has had an impact should be aggregated at the SUSA site to enhance the user experience. • Contextualized, easy-to-understand data should be aggregated at the SUSA site to enhance the user experience.

Today

Mary Jo

Scenario

Akron, Ohio

12:20 pm Wednesday

Tomorrow Scenario


“Isn’t there data for normal people?” Mary Jo browses to other publications on Nature.com and discovers another journal titled Obesity. She finds her way to the table of contents and scans for data sets and articles that could help her. She finds an article titled “Correlates of State Legislative Action to Prevent Childhood Obesity,” which she assumes will have something she can use. What she finds is a very dense and cerebral article with tables that she doesn’t quite understand. She is frustrated once more and closes her browser.

“People need to know what I have found.” Mary Jo is very excited about the data she finds but her skepticism kicks in and she questions where all this great data is coming from. She quickly scans the page and sees a button clearly labeled “About This Data.” She clicks on it and gets an in-page text screen explaining SUSA’s mission and methodology and the origin of the cited data. There are links to the organization’s website and a profile for the group. Mary Jo notices a list of users labeled “Other Users That Have Saved This Data.” She clicks on one of the user’s names and is given a page that shows all the graphs, articles, and charts this user has saved on the SUSA site. Leveraging this user’s research, she clicks through the various maps and articles and bookmarks those she finds relevant. She notices there is a “Contact This Person” button on the profile page and Mary Jo decides to reach out and share her story and ask for guidance and help.


pain points and concerns

recommendations

• The content and information is convoluted and hard to understand by a lay person.

• SUSA should be transparent about its processes and data sources and allow for us-

There is value in the content but unfortunately Mary Jo just can’t interpret it.

ers to connect with each other.

Mary Jo

12:30 pm

Today

Mary Jo

12:30 pm

Tomorrow

Akron, Ohio

Wednesday

Scenario

Akron, Ohio

Wednesday

Scenario


“What am I going to do?”

Mary Jo looks at the clock and realizes she has 5 minutes left before she has to get back to work. She has not touched her sandwich and she hasn’t found out anything that could help her make her case or explain her situation.

“I’m bringing this to the PTA!”

Mary Jo notices that her time is running out and she wants to capture all this great work so she can look at it more closely later tonight and hopefully use it at the next PTA meeting. Looking at her saved module she notices a button labeled “Download All Saved Research.” She clicks on it and an in-page box appears displaying her saved options. Armed with information from the SUSA site that was easy to download, print, and consolidate with her own online and offline knowledge-gathering and ideas, she plans to arm herself with a presentation to take to the PTA, the school board, and the city council. Thanks to SUSA she has an informed and believable story to help her son and her community.


pain points and concerns

• Mary Jo has a pile of work and feels the stress of not getting even the slightest bit of information that could help her understand her son’s situation. • She found the interfaces for the variety of applications she tried to use confusing and misleading, wasting much of her time. • When she did find data, she could not manipulate it, download it, and, in some cases, understand it. • It was hard to find methodology for the data she came across, making her question its validity and its usefulness for her cause. • The only recognizable data sources she came across were those of the federal government. She trusted the CDC and knew its offerings would be free or inexpensive but unfortunately found nothing of use. recommendations

• All downloadable SUSA data should be branded and contain a link back to the SUSA website.

Mary Jo

12:40 pm

Today

Mary Jo

12:40 pm

Tomorrow

Akron, Ohio

Wednesday

Scenario

Akron, Ohio

Wednesday

Scenario


Frank Scott

Washington, DC

Frank Scott

Washington, DC


Today

Tomorrow

Frank Scott lives in Washington, DC and runs a liberal politics blog. He knows all the government acronyms for executive agencies and can name most of the Senate Committee Chairs.

Frank Scott lives in Washington, DC and runs a liberal politics blog. He knows all the government acronyms for executive agencies and can name most of the Senate Committee Chairs.

His blog has a readership of around 120,000 unique monthly visitors and many of Frank’s readers are themselves bloggers who link back to his stories.

His blog has a readership of around 120,000 unique monthly visitors and many of Frank’s readers are themselves bloggers who link back to his stories.

He’s technically savvy; he maintains the blogging software on his server and he’s got over a dozen Google alerts on topics he’s interested in.

He’s technically savvy: he maintains the blogging software on his server and he’s got over a dozen Google alerts on topics he’s interested in.

There is an immigration reform bill before Congress and Frank wants to devote his morning post to the subject. This particular debate has focused on illegal immigration’s effect on the economy and unemployment rates. Frank would like to find some images to punch up his morning blog post on the subject and is looking for graphics related to state-level immigration rates and unemployment.

There is an immigration reform bill before Congress and Frank wants to devote his morning post to the subject. This particular debate has focused on illegal immigration’s effect on the economy and unemployment rates. Frank would like to find some images to punch up his morning blog post on the subject and is looking for graphics related to state-level immigration rates and unemployment.

In the past, Frank has tried and failed to find timely, attractive, and authoritative graphics representing federal information. Today he is going to try to acquire the data directly and create bar graphs using Excel. It’s 6 AM when Frank starts looking for this data. He figures it shouldn’t take him very long. He needs to get a story up before the morning rush at 9 AM.

It’s 6 AM when Frank starts looking for these graphics. He figures it shouldn’t take him very long. He needs to get a story up before the morning rush at 9 AM.


“Today we hit immigration.”

Frank wants to find Census data and visits census.gov. He goes to Data Tools and then the American FactFinder, an interactive application that suggests it has the latest data. The FactFinder contains a half dozen data sets. Frank chooses the Economic Census data set but returns to the FactFinder page when he sees the last Economic Census was completed in 2002. He chooses the American Community Survey data set, which has 2006 data and bills itself as a “fresh look at how [communities] are changing.” He’s not sure how accurate this Census data is but he’ll decide whether or not to use it after he gets his hands on some data. He selects the “Custom Table” option, which he thinks should allow him to drill down on the data he wants. Frank is in the FactFinder application. Frank knows he needs to choose which states to compare. He decides to get immigration rates for all 50 states, sort them by immigration rates and then focus on the states that are divergent. The FactFinder application allows him to select all 50 states as his geographic areas of interest. So far, so good. He clicks “Next.” The next page allows Frank to select the data elements he’d like to include in his custom table. He scrolls down looking for “immigration rates” but becomes flustered when he sees there are over 1,000 different data elements to choose from. He doesn’t want to look through all of them.

“Today we hit immigration.” Frank is a regular user of the State of the USA and he clicks on his bookmark. The homepage greets him with a listing of the most recently released data sets and blog posts from the State of the USA team. He knows what he’s looking for, so Frank does a search for “state immigration” and the State of the USA search results offer him a broad range of data sets, including breakdowns by year and by individual state. Frank clicks on the link “Immigrant Population as a Percentage of State Population, 2007,” which identifies itself as coming from the Census Bureau’s March 2007 Current Population Survey. This page shows a graph of the United States color-coded by immigrant population percentage. Frank isn’t sure if these figures include estimates of undocumented immigration, but the contextual explanation underneath the graph answers his question immediately. Frank is registered but not signed in so he goes to the top of the screen and clicks “Sign In.” He signs in with his email address and password. The page dynamically reloads and his MyStats collection shows up in the left sidebar. Frank clicks on the “save this data” button at the bottom right of the graph and adds this graph to his MyStats collection.


12:20 pm

12:20 pm

pain points and concerns

• The Census Website is geared toward the 2010 census. It’s not clear what data set is

recommendations

best suited to Frank’s particular need. • He’s lost in the array of different options. Is he expected to read over 1,000 different

• Search needs to be powerful and associative (e.g. immigration ~ immigrant) • Contextual descriptions should anticipate questions and seek to answer them rapidly

options?

so users don’t have to visit the original data source to hunt it down. • Each page should have a glossary section.

Frank

6:00 am

Today

Frank

6:00 am

Tomorrow

Washington, DC

Monday

Scenario

Washington, DC

Monday

Scenario


“Too many options and too little context.” Frank sees that there are options to sort the data elements by subject and keyword, so he chooses to select by keyword. He types in “immigration” and the application says it has “No results.” Ugh. Frank is annoyed—there are 1,000 data elements to choose from and none of them contain the word immigration? He decides to choose “citizenship” as his keyword and see if that works better. It does, returning only two dozen data elements. It’s more than he would like and some of the available elements are confusing: Does he want “B05001. Citizenship Status in the United States” or “C05001. Citizenship Status in the United States” or “Imputation of Citizenship Status?” He crosses his fingers and selects the first item. Frank gets a results table. Frank plans to look more closely at the data when he gets it into Excel. He tries to select the whole table with his mouse but certain parts of the table aren’t highlighted. It’s annoying. He uses the “Select All” command in his browser which does grab the entire table and the text of the page. He pastes it into Excel. The table doesn’t sort properly though—all of the data comes down in one row, not multiple columns.

“How did we do this before SUSA?” Frank does another search for “state unemployment.” He clicks on the result for “Unemployment by State, March 2007,” originating from the Bureau of Labor Statistics. Frank saves this graph to his MyState collection. He’d like to take the two graphs and make a widget for his blog. Frank clicks on “View and Manage My Collection” under MyStats and goes to his MyStats page. He sees a list of his recently saved data sets. He clicks on the “Create Folder” button and names his new folder “immigration & unemployment statistics.” He toggles the check boxes next to his two just added graphs and then clicks the “add to folder” button. He clicks on his “immigration & unemployment” folder which takes him to a new page with the two graphs.


recommendations

pain points and concerns

• Frank is a smart guy but he needs someone to hold his hand. If there is a multiplicity of data and data terms there needs to be context immediately available.

• SUSA should create organizing tools that allow users to group data sets together and manage them as a batch. For example, a user could download the data sources of four different indicators as one populated Excel spreadsheet.

Frank

6:20 am

Today

Frank

6:05 am

Tomorrow

Washington, DC

Monday

Scenario

Washington, DC

Monday

Scenario


“Why is the application fighting me?” Frank tries sorting the data manually but it’s a hassle and he returns to the FactFinder results page. He looks over the page more carefully and sees there is a small download link at the top of the page. He downloads the table as a zipped Excel file and opens it up. He starts deleting unnecessary rows and columns. He hesitates at the margin of error columns. He doesn’t know how to factor them in to his data compiling, so he deletes them. As the spreadsheet becomes smaller, it becomes more manageable and Frank sorts the table by estimates of non-US citizen state residency. He selects a pool of 10 states that he will compare. He worries that his sampling is unscientifically random. He goes back to the FactFinder custom table builder but it won’t give him the option of changing the Data Elements. Eventually, he finds a way to go back to the Data Elements selector and inputs “income” as a keyword and it returns dozens of options, many with duplicates. Frank chooses “Household Income” as his data set and gets a new custom table that he downloads and unzips. He tries to open it but Excel won’t let him open the file because he already has a file with the same name open. He renames the new file, opens it, and pastes the contents into his master document. Frank worries that this is going to be a pointless exercise.

“This is going to be slick.” Frank clicks on “Create Widget” which pops-up a layer which allows him to create views in a Flash widget. Frank adds the two maps to a widget and also creates alternate views using bar graphs for both immigrant population percentage and unemployment rates, sorted in descending order. He adds a description inside of the caption field, previews the widget, and grabs the embed code. He starts to work on his blog post.


pain points and concerns

recommendations

• The data application needs to be smarter. It would be better if there was a shopping

• SUSA should have a powerful widget creation tool that allows users to define and

cart approach. Frank could add data sets to his basket and then download them all at

present multiple data sets and graph styles to users.

once.

Frank

6:40 am

Today

Frank

6:10 am

Tomorrow

Washington, DC

Monday

Scenario

Washington, DC

Monday

Scenario


“I’m out of my league. My time could be better spent.” Frank does a Google search for “state tax revenues.” The first result is a Census page that has a different interface then before, but Frank is pretty certain he is on the right page and he sees that 2006 is an available year for data. Frank isn’t able to build a data set like in the FactFinder but there is an option to select by state. Rather than go through all of his ten states and download the data individually, Frank decides to get the “Flat Data File.” This page isn’t what Frank expected—it’s a comma separated data file with numbers but no row headings—and it isn’t any more sensible when he pastes it into Excel. Frank goes back and downloads the “Summary Table Spreadsheet [Excel].” After about 20 minutes of deleting, copying, and pasting, he lines everything up properly so he can compare the data in his master spreadsheet. Still, he’s finding the numbers hard to wrap his head around: Why does this data show Florida has no individual income tax revenue? Why do both New York and North Carolina show no property tax revenue? Frank looks at his watch. He doesn’t have time to figure this out. He decides to start writing his blog post immediately without an image. If he can find the time, he might continue this process and update his post with a graphic, but he doubts it.

“The conversation takes over.”

Frank finishes his blog post and embeds the SUSA widget near the end of it. He invites his readers to go in-depth on individual states and a robust conversation starts in the comments on how much illegal immigration affects state economies and unemployment rates. Many commenters post links to their own widgets on SUSA, incorporating more indicators and focusing on individual states. Throughout the day, Frank creates posts focusing on individual states using his readers’ widgets and their commentary.


recommendations

pain points and concerns

• Frank wishes that there was a newbie guide to DIY statistics from government sources.

• Visitors to Frank’s blog should be able to grab embed code from the widget and republish it in their own sites.

• It would also be good if he could crib from an authoritative source that has already crunched the numbers. Why should he have to reinvent the wheel?

Frank

7:20 am

Today

Frank

6:20 am

Tomorrow

Washington, DC

Monday

Scenario

Washington, DC

Monday

Scenario


Strategic Concepts and Considerations

Contents Introduction Strategy Discussions •

Brand Considerations and Challenges

Content Offering and Functional Considerations

Social Interaction and Peer-to-Peer Functionalities

Design Considerations and Samples

Additional Discovery Findings •

Objectives

Audience

Competition and Landscape


Introduction In discussions and materials received to date, we’ve come to understand a lot of what the State of the USA sees itself becoming. In this opening process, we’ve set out to digest and audit the received information quickly in a small collaborative group and offer insights into the site experience that will successfully capture the intended audiences and move the mission forward. As we proceeded, we found ourselves more and more often trying to separate the aspiration from a realistic and effective entry into the market. It became of increasing importance to distinguish the vision of SUSA Year Five from that of SUSA Day One. As we build for launch we need to establish a pragmatic concept and execution that puts us on the course with the most potential – recognizing the needs of a new site are very different from the enhancements you bring to an existing venture with an existing audience. You’ll find a collection of insights and questions to follow. As SUSA looks to turn the corner from demo to a full-functioning site, many of the open questions will need serious consideration and a critical eye. As each component is examined, prioritized, and designed, we need to look at it from the audience’s viewpoint and figure out what is a useful tool and what is an engaging toy? Google delivered value for years and built a loyal audience before releasing Google Earth. As the data visualizations are pushed forward, there will be plenty of room for enjoyment, sophistication and wonder in the functional set – and an appeal to curiosity is essential to drawing in our most important audiences. But we need to immediately deliver value with every step forward our users make; we need to deliver what they value in the tasks they face.

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Brand Considerations and Challenges Starting with materials provided to date and discussions with SUSA leadership and stakeholders, we further investigated challenges to building the desired brand and implications for initial and ongoing success. Here we discuss key brand attributes, as well as challenges to establishing equity in those attributes. Potential equity-building tactics are discussed here in part, but continue throughout this document. As the functional and editorial set of the initial release is defined and developed it should be continually audited against these brand aspirations and challenges – and non-contributors should be de-prioritized.

Aspirational brand attributes •

Credible

Trustworthy

Useful

Relevant

Consistent

Understandable

Unbiased

High in quality

Efficient

“Patriotic” in the classic sense of believing in the country and the possibility of a “better” future

Establishing credibility and trust Building equity credibility and trust will be perhaps the most difficult undertaking in the initial phases, and yet the most important. Consumer Reports has been often mentioned as a model for SUSA’s offering. But Consumer Reports has built its credibility not only through the easy-to-understand presentation of ideas, but also in its legacy of performing original research. How can SUSA build credibility without original research?

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How do we overcome a lack of confidence in the very third party data and research that serves as the foundations of our offering? How do we address the wide variations in trust our audiences have vis-à-vis our third party sources? •

Develop a Watch Dog component to the brand that audits the methodologies behind the original research and educates audiences to the strengths and weaknesses of these sets

Be critical of manipulation of this data – calling out misuse of the data in political rhetoric and punditry – showing that we aren’t blindly accepting what is fed to us by our government sources

Be responsive to the audience’s skepticism by engaging their questions and conducting an open dialog of doubts in any particular set of editorial choices – employ an ombudsman that is both diligent and public

Be transparent in our filtering of data – making it easy to grasp why a particular component of the data was removed from view and to access that removed data

Welcome outside auditing of our own methodologies by peers – and to garner their certification of our outputs; and

Garner endorsements from sources our audiences trust (e.g. established journalists and trusted thought leaders)

Becoming useful and relevant Tactical and editorial planning drives our ability to be relevant. What do our audiences actually need to better fulfill the mission of their own organization and their role within that? What is the true value they are looking for? At launch, it will be essential to have material our audiences find immediately useful in every section of our portfolio. •

We need to be timely in rolling out our value-added interpretation of data as it is released by third parties.

Is the staffing adequate for keeping up with the release of major data sets within the breadth of our portfolio? Does the portfolio need to be further focused?

It will be challenging to simultaneously elevate the most actionable material at the same time we grow the trust and credibility that is a prerequisite to using these

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actionable materials. Does this also point to a need to further focus the offering?

Being perceived as unbiased Can we rely on third party information and primarily act as an editor of that information and still be perceived as unbiased? Can any organization be perceived as unbiased in the current political climate? It will be more important that our information is seen as credible and useful rather than unbiased. Transparency into our editorial process will not only allow us to build a case for being unbiased, it will allow our audiences to create their own coherent picture of any biases they do perceive. Known biases make editorialized (in this case, expert-guided filtering) information as useful as purely factual information. As long as the user can develop a sense of the strengths and limitations of any provided data, that user can find use for it within their personal set of research tools and information sources.

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Content Offering & Functional Considerations The materials we’ve received and discussions we’ve had with stakeholders have highlighted functionalities that seek to be a research service or tool, a publisher of data and content, and a forum for discussion. Trying to serve all of these functions for an audience that doesn’t even know us will certainly result in something that is far too diffuse and provides so many avenues for our users that no critical mass and unified understanding of offering or organization forms. Where do we focus and what do we do with the rest? First we need to remove the idea of being a forum – at most, we’ll want to mature into this offering as audience accumulates and loyalty is built. Achieving our goals to foster discussion is picked up and discussed in the section of social interaction and peer-to-peer functionalities below. As we look at the landscape, and walk through relevant user scenarios – we find that again and again it isn’t that this data isn’t available, but that it isn’t provided in a reasonably accessible and useful way to any but the most dedicated and least time-starved audiences. To that end, focusing on being a research service to the ongoing investigations, content generation and discussion in the landscape would deliver the greater value. As a service provider we are promoting a better use of statistics, augmenting current content generation, and making information available for fact-based analysis where the lack of available data is causing circular, polarized debate. As a service provider, whatever the depth and offering of that service comes to be, it will need to be fully dedicated to meeting the needs of the user and deliver the highest quality to move SUSA’s mission forward. For our most important target audiences – as currently defined – timeliness will be a part of the quality that delivers to user needs. SUSA will have to turn around high-level analysis on new data quickly – even while we aim to be “best to market” rather than “first to market.”

Consistency in data and functionality breeds reliability Consistency is an essential feature of basic usability and reliability. In our first encounter with users we need to provide immediate utility, but on each subsequent encounter, we need to deliver the same or more in terms of quality, depth and functionality. The goal is to build a

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perception and expectation of what a visit to SUSA will provide. Our success is predicated on the user always thinking “SUSA will do it” when a specific need arises. At the most tactical level, if SUSA allows me to compare county-to-county statistics on infant mortality, it needs to do the same in obesity and life expectancy. And, if it allows me to build a specific kind of chart for one type of data, I need to be able to do the same with similar pieces of data. Given the inconsistency of data sources – especially as our portfolio crosses from one macrotopic to another (e.g. from health to economy) – this presents a significant challenge. We can address this challenge through restraint and messaging. Do we come out of the gate with consistently promoting national and state-level data – staying away from more granular city or county data? What level of data are our primary targets looking for most. Just because we can provide a certain granularity, it doesn’t mean we should. Or is it better to offer a more complete and granular set of comparisons – be it nation-to-nation or U.S. county-to-U.S. county, and instead pare down the subject matter we deliver on? Inconsistency will breed frustration and perceptions of unreliability. When a time-starved reporter or legislative assistance comes to SUSA for the same kind of state-level data they successfully acquired months before, we lose the trust we built and their subsequent return becomes highly unlikely. The casual browser has a little more tolerance for disappointment, but it is those time-starved audiences that have the greatest immediate impact on our mission.

Implications: •

Set an upper and lower threshold for data granularity.

Examine the ability to deliver consistent, timely data to our desired portfolio – does it need reduction?

Establish a threshold of functionality and provide it in every instance.

Clearly label one-off tools or unique depth of information as beta or otherwise special – providing these in explicit partnership with another organization can help to clearly delineate your core, reliable offering among these aberrations.

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The role of visibility vs. filtering in building trust The current thinking is to provide subsets of available data. This can prevent significant barriers to trust at release – as users wonder “what was left out.” We need to explore methods that allow us to present the filtered view up front with access to the full set of data – and in many cases, simply linking straight to the original data source will not accomplish that due to the poor usability our audiences will encounter upon arriving at a particular government site or research service.

Implications •

Is it possible to use “all the data” from a particular report – putting our summary first and a more complete view a click away? There are significant concerns about the resources for doing so, but it would provide a significantly different – and easier to trust – message of, “We’re introducing you first to what we feel is most important, as the entry into a larger data set”

Provide an understanding (likely text-based) of what has been filtered out and why – and support an open critical discussion of those decisions

Provide multiple, and sometimes opposing, expert opinions on what the most important stats in a large set may actually be

Making the data useful Utility needs to be the foremost driver in defining the types of content and functionality we will provide. We need to pay special attention to supporting the users’ capabilities in bringing the outputs and findings of our system to their own spaces and arenas – online and off. Current functional investigations by SUSA have talked at length about this need, but we wanted to add to this a particular focus on online-reusability aspects.

Implications: •

Allow users to pull “embeds” from configured data visualizations and all other visual presentations that will augment the users’ content-based destinations (e.g. blogs)

Invest in making online re-use as easy as possible with the kinds of usercustomization that has become commonplace (e.g. one-step publishing to popular blogging tools and social networking platforms, and offering a range of sizes and color customization)

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Enable sharing not only of a particular data set or visualization, but also to a user’s filtering and configuration of that data set (e.g. setting a particular date range or filter) – think of the ways users can link to very specific map views on Google Maps

Allow users to save galleries of their own “favorite” data sets – both as presented by SUSA and their particular configurations – that they can share and publish

One particularly useful value SUSA can provide is the ability to bring together diverse data – especially where the original research is happening at various organizations that aren’t related. Our breadth will allow users to bring indicators together across issues in our portfolio – economic change against health factors for instance. There are many complicating factors here and a noted hesitancy to take this on in the functional descriptions to date, but the opportunity merits additional consideration and problem solving.

Who owns the “complete picture”? There is an established desire to provide the “big picture.” But this stands at conflict with a desire to foster discussion – a complete picture can be an endpoint of discussion. Our initial audiences are looking to dive into particulars – they are already carrying their own complete picture or hypothesis, and are looking for corners of that picture to be illuminated and compared against their prevailing beliefs. Let the complete picture coalesce in the content and discussions we inform. Embed ourselves and our utility in that content and discussion, but don’t over-exert in creating, shaping or publishing it.

Implications: •

Focus on a particular utility in the course of building to the big picture.

How complete can our system of “national indicators” be at launch and what does this mean vis-à-vis the brand we are messaging at launch?

Do we push all analytical content off the site and only promote it within our experience? More on this below.

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The role of “editorial content” Editorial content needs to likewise focus on the needs of our audiences. Our editorial content should avoid providing the kinds of op-ed material provided in current news sources, blogs, and so forth. Instead – content should serve the same role as our visualizations, providing useful distillations and summary findings from data sets. The content should not seek to be an endpoint, but something that users will want to take away for an outside end use. In many cases, it will be this summary content that our users are looking to get even before the more complex data visualization function – not to mention the importance of this content to search engine optimization.

Implications: •

Provide high-level summaries and “data sound bites” of new reports upon their release along with the data visualizations as they are developed

Track current events to elevate visibility of data sets that may not be new, but are especially relevant to a hot debate, ongoing discussion, or even a particularly bold or attention-grabbing statement by a politician

Provide critical analysis of common statistics being used in the landscape to provide a richer understanding of how that information can be used (such as explaining the strengths and weaknesses of a specific unemployment stat)

Provide simple “stat shots” (similar to those you see in USA Today and common to magazine-style layouts) along with more involved data visualizations whenever possible

Provide ongoing “did you know?”-style content that surfaces an odd individual stat and uses sheer curiosity to draw users in – we have to appeal to their natural inclinations to investigate

Another editorial challenge pertains more to the outreach and marketing that will strive to capture the attention of our audiences – we need to provide a strong “so what?” with regards to our offering, toolset, and our data without becoming politicized or drifting too far from our central mission – how can we make an strong emotional appeal that will lead our audiences to make this a go-to “research” tool.

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Make it “educational” Part of building trust and credibility will be establishing the perceptions of our expertise – and by extension, making our users more qualified to be critical in their approach to data and its end uses.

Implications Provide contextual information to supplement the provided information and build trust such as: •

Explanation the information gathering and methodologies behind particular statistics – their strengths and weaknesses

“Stats 101” material on how one should read stats and where one should be critical – as well as basic guidelines to knowing a “good stat” from a “bad one”

Simplicity first Complex, interactive data visualizations are very attractive, but the majority of our audiences will want answers on a deadline. We need to foreground simple analysis and provide not only what our audiences will realistically have time to use – especially at launch when we are trying to build and retain audiences – but also what SUSA will have time to analyze and build on tight timelines to provide value while the original dataset is relatively fresh.

Implications: •

Provide simple stat shots and high-level text summaries (mentioned above in content) – remember, our time-starved audiences may need to build considerable loyalty before they begin to “play” with interactive data configurations

Begin with visualization systems users are most accustomed to – simple charts and graphs, “weather maps,” etc. – and let them self-select to complex interactions as we move forward

Follow the same models in navigation and search – for instance, building strong keyword search capabilities that can deliver to the user’s need without having to resort immediately to advanced search capabilities and filtering

Provide scannable, high-level lists, galleries, and result sets that users can quickly browse – including the provision of multiple well-titled configurations of particular data sets that anticipate common needs of our core audiences (e.g. being able navigate directly to a “by state” or “by Nation” view of a particular data set)

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Social Interaction and Peer-to-Peer Functionalities We can’t begin as the forum for discussion. And, in fact, we need to give a lot of thought as to whether we even want to try to become the host of the discussions our mission aims to create. Nike provides the means to be a stronger competitor – it doesn’t try to create its own basketball league. So where does this leave us on social functionalities in our initial release?

Integrate into established communities With delivering immediate utility to inform conversations being core to the release strategy and mission, those end uses provide a rich opportunity to promote social interaction and other peerto-peer connection. Starting from zero, as far as audience and peer-to-peer interaction within that audience, we will benefit more from beginning to draw upon and connecting to the conversations happening elsewhere within established communities – blogs, discussion forums, and social networking sites.

Implications •

Provide publishing integration to popular destinations, especially blogs – something you’ll see in many ASP models

Promote the end-uses within our site – sending users out to those other destinations to become engaged in those existing communities

Create explicit partnerships and content syndication with established bloggers, journalists, etc. to tap into their audiences and build trust and credibility

Actively engage in discussions at existing destinations – our content experts openly commenting, contributing columns or posts, etc.

Allow for commenting and conversation within our experience, but don’t let it overwhelm the primary purpose – that users should interact with our data to gain original insights they take and integrate into their current methodologies

Be more concerned with content and functionality that actively provides the right value at the right time rather than strict “traffic retention” – let the value and other discrete outreach methods like RSS feeds and tailored newsletters draw them back and extend their visits

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Start with on-site social interaction focused on end use Sites like Flickr focus the peer-to-peer functions around the core business. As we draw users into creating profiles, they would focus on things like tracking galleries of the unique data views and favorite data sets – and how the individual re-used them (links out to posts they made with it). The discussion itself would not only serve to connect users to one another and begin building community within SUSA, but also serve to teach users the best ways to utilize the site within their own work. An individual’s page at log-in would likewise promote the latest creations and uses of data outputs by users with similar interests or within a set of peer contacts.

Social interaction offerings should start shallow and broad – with close observation of usage It is important that SUSA not over-invest in any particular area. The true needs and reactions of the intended targets are unproven, and a new system can’t rely on what our focus groups tell us will be useful – instead we need to put pilots out there and observe real world results to guide our ongoing evolution. It is hard to know, at this point, if people will even want to have discussions here about the data and findings themselves devoid of the kinds of strongly prescriptive or opinionated context you receive in op-eds and blogs.

Implications •

Build rudimentary systems of personalization and profiles that meet a broad range of basic user expectations – e.g. a simple comment system, broad but simple RSS capabilities

Install sophisticated tracking and metrics systems to understand what user to user interactions are taking place – what and where data is shared, how profile pages are being used, etc.

Avoid “over-steering” any discussion that does ensue within the SUSA environment – using a light touch as far in curating comments

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Design Considerations and Samples The design of the SUSA experience will be driven by brand, strategic priorities and audience needs. As the open issues in each of these areas are resolved, initial thinking about design will need to be audited and adjusted. That said, there is a collection of best practices and high-level recommendations that we can tie to what we do know, thereby offering a significant step forward. Per explicit request, we’ll provide three relevant samples from our portfolio – the guidance they provide and the questions they raise.

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NPR Election Map http://www.npr.org/news/specials/election2008/2008-election-map.html

The NPR Election map uses simple information and intuitive drill-downs to present volumes of information in an easy-to-understand interface – a challenge SUSA will need to likewise tackle. While the map employs a variety of interactive components, the Election Map delivers immediate and useful information prior at the point of entry, before employing any of the additional elements. As SUSA serves its time-starved audiences, it is important to remember that we begin as just one research tool in a sea of available options. Until we build a history of success with individual users, we have to be sure that we are delivering value from moment one Threespot Media LLC, Proprietary and Confidential

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as users start searching and examining data. High-level findings, quick summaries, and fast facts all provide immediate, easy-to-use material our audiences can consume and move forward with. That immediate utility will encourage deeper use in the current visit – or should time not allow it will encourage return usage when needs again arise, building to deeper interactions over time. We must remember that our mission is to deliver information and value to the larger discussion – be it through the presentation of a simple statistic, or complex user-driven configurations. The NPR audience offers a diverse range of web savvy within among its user, while they are uniformly more educated and intellectually engaged than the average web user. To that end, the map interface, annotations and presented data all draw upon the styles election-interested audiences have encountered over the years in on-air and print graphics covering these issues. And when the user does begin to interact with the map – examining different data sets, chronologies, and drilling-down to related news – simple expected interactions, transitions, and strong titling keep the experience from becoming overwhelming or confusing. While SUSA’s target audiences are likely to be uniformly more advanced web users than NPR’s, it will be very important to understand their expectations and play to them – as well as not overestimate their tolerance for or interest in complexity. As we prioritize our audience targets we need to closely examine their existing online behaviors and play to them. If they frequent blogs, we need to play off the simple commenting functionalities and diverse RSS offering typical to those spaces. If they are bloggers themselves we need to understand the proliferation of widgets and embeds commonly used by these audiences and play to those habits. And at the same time, we need to be ready to support a diversity of users – while we aspire to certain priorities at launch, our target represents a far more diverse group with varying capabilities – and always offer a simple and clear usage up front, without entirely hiding more complex offerings. Finally, the map interface and execution was planned to grow through the phases of the election – from Primaries to Presidency, including House and Senate races – from day one and constructed to age and evolve. Repeated use by the audience allowed functionality to become denser and more complex as it evolved forward. Many of the data sets SUSA employs will be updated over time, or dovetail with other expected data sets. While none are likely to move through narrative arcs of the regular simplicity of an Threespot Media LLC, Proprietary and Confidential

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election, we should look for and incorporate narrative progressions in our planning wherever possible and use these to draw users in, encourage repeat visits, and graduate them to deeper engagement with individual data sets and SUSA in general.

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The International Rescue Committee http://www.theirc.org/

The International Rescue Committee has existed for more than 70 years but at the time of their recent re-branding had low awareness and recognition with its intended audiences in a very crowded international development marketplace. While the IRC and SUSA share little in terms of subject matter, they do share the need to quickly and succinctly tell users who they are and what can be accomplished through the web site. A mission statement is easily ignored or disbelieved, especially by users with something to accomplish. To that end, the IRC web site offers a very straightforward understanding of the organization and what they do through the use of bold and clear navigation that doubles as messaging. Similarly, SUSA will need to construct its site architecture and functionality to convey the brand and a clear understanding of what the organization offers – in a way that still intuitively leads Threespot Media LLC, Proprietary and Confidential

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users to desired functionalities and information. While SUSA’s end product is more technically complex, we should aspire to a clean and simple experience – like the IRC or like any of the many sites out there that serve as tools and services. From Google to Flickr, service-oriented sites enter the marketplace by making the core offering clear and useful, while building upon that value through incremental functionality. We need to begin with a focused understanding of what we add to the marketplace – and bend the entire launch offering to that purpose. We need to create a very simple and direct brand promise and deliver that promise in all we do. As the organization matures that promise can expand and evolve with a loyal audience. What is that promise, in its simplest and most conversational terms, at launch?

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The Brookings Institution http://www.brookings.edu/

The central challenge for a Brookings web experience is tied to one of its core differentiating strength – breadth of quality coverage. While Brookings covers hundreds of topics valid in the policy landscape at any time, audiences are coming to them and their web site for very specific information on a single world event, or piece of legislation, or field of study. To compensate Brookings offers a multiplicity of paths through the site to accommodate the variety of approaches users take, and relies more on content-based relational navigation than rigid catalog-like taxonomies – though those are surely available. While SUSA will enter the market with a smaller portfolio of topics, a best practices approach to providing a multiplicity of content paths to satisfy a diversity of user behaviors will be important in getting users to the most useful information efficiently.

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Strong search functionalities should be considered the primary navigational path for our most task-oriented users, like journalists and other “influencers.” But at the same time, we need to serve a strong browsing audience by providing clear information and a narrative thread that can take users from a home page or other entry point to deeper information, broader information, and other anticipated interests. And finally, catalog-style taxonomy needs be available, but has to be constructed in a way that keeps users from guessing – placing information wherever it makes sense. Too often it is easy to fall into seeing a single perspective in creating a tree structure and confuse significant portions of the audience. We can also learn from the rudimentary personalization and targeting seen on the Brookings site. In dealing with the fact that any individual user is interested in 5% of what Brookings covers, users are able to create shortcut lists of topics, experts and research projects – as well as subscribe for feeds for any one of these to ensure they are receiving the latest offered material even if they aren’t able to visit the site in a particular week. But when they do visit, the site generates a list of new content related to their stated topics, experts and research projects for perusal. SUSA will need to follow a similar mentality in presenting information – from clear presentation of related information along topical lines and intuitive next steps, to a variety of tailored outreach options that make it easier for the new user to quickly build a connection. And at the same time, we need to make sure to reserve secondary spaces to promote information on topics unrelated to the task at hand – promotions outside of the primary active space that introduce the breadth of coverage, highlight timely material, and so forth. Even as the site grows and comes to more fully realize the idea of providing a full set of national indicators – most individuals within our audience are not working with that full set, but rather deal with some subset in their daily practice.

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Additional Design Considerations As we discussed SUSA’s mission and challenges internally, a number of additional points were discussed that should be helpful to developing an aesthetic and editorial approach. •

Breathe credibility: The overall aesthetic presentation needs to focus on “the real” – avoiding stock photography and abstracted imagery and favor journalistic material that is both relevant and recognizable.

Make it human: Seek out the opportunities to inject humanity into the number crunching and data visualization. This obviously begins with creating usable, manageable interfaces, but also points to the tone of content surrounding the data sets.

Default to simplicity and let users self-select: Users who want complexity and sophistication in their experience will catch on to it through the simplest means. Illustratively, an RSS icon provides all the promotion knowing users need, without confusing the web novice. Seek the same kinds of simple functional signposts.

But again, moving forward decisively with design is contingent upon having a clear well-defined set of strategic principles concerning the audience, the brand, and tactical priorities – whether long-researched or intuited – that the organization can stand behind. Starting from an agreed foundation allows the organization to track success and evolve over time as the audiences evolve or the organization’s understanding of those audiences does. With an agreed and committed direction the collective team can be more adept at tracking the strengths and weaknesses of the strategy in practice and apply its efforts appropriately rather than progressing through a scattered series of enhancements or band-aid fixes.

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Additional Discovery Findings As planned – the following discovery findings were gathered in a rapid and improvisational process rather than aiming to do exhaustive research and definition. The information here came together through the internal process of understanding SUSA to the best of our ability within the given timeframe in order to deliver the best concepts and strategic insights for the core work. We understand that significant discovery has occurred around all of the included. The discovery findings here should serve as an outside perspective to identify potential additional research and define previously unrecognized assumptions within discovery and planning to date.

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Objectives To free (as in liberate) useful, statistical data to provide a fact-based assessment of the critical issues facing the United States and enable, feed, and facilitate discussion of such issues. More granularly -- the following objectives more granularly define and/or contribute to that mission: •

Be the Consumer Reports of the United States, “The Measure of America”

Raise the bar of access to data – both the ability to find and understand available data

Feed the discussion from the legislature to the dinner table

Provide a common platform for discussion

Reinvigorate and empower democracy

Diminish and remove friction in civic discourse

Aggregate and filter to an expert-defined subset of the most useful data – providing a streamlined path to a solid understanding

Provide a conduit to data

Provide a non-partisan and independent national indicator system

Filter and prioritize the data – but not provide conclusions on the “next steps” in associated policy

Completing the picture; and

Removing friction in civic discourse

Important tactical consideration for the early release phases will include: •

Building trust equity with key audiences

Becoming and stay relevant

Establishing a critical mass of participants for discussion and civic dialogue; and

Building sustainable resources and funding

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Audience Prioritizing Audience Targets The “Key Audiences…” presentation (6/6/08) identifies four key audience groups – Policy Shapers, Influential Intermediaries, The Engaged Public, and “Budding Scholars.” Considering the audience- and brand-building challenges faced, the limited time available for the majority of targets, and the crowded marketplace within which SUSA operates, it will be essential to focus on a small audience target in Phase 1 outreach efforts. Functionalities and content needs to be tailored to this smaller set (while not ignoring the needs of aspirational audience groups). In creating a more targeted initial audience, it would be useful to examine the components within these macro-level groups to identify the easiest to reach and those that will deliver the most impact on the organization’s mission. Briefly, we spent some time examining the “Influential Intermediaries” and came away with the following items in need of additional discussion and examination: •

When we look at the “journalist” target are we looking to reach elite “issue” journalists or the “rest”?

A potential goal could be to provide a generalist media member with the information to operate at the level of an “issue journalist” – would that be a good investment of time and resources?

Are junior reporters the low-hanging fruit? Do they have smaller roster of loyalties to competing sources? (Analogous to junior staffers within the legislature when we examine that target more closely?)

What are the audiences of our journalists – how much are they intended as an influencer vis-à-vis mission vs. a conduit / influencer in the realm of audience building?

Similar dives into understanding the components of our targets – even if as rudimentary as the above – can offer insight that help to clarify strategy and align efforts within the team – fleshing out the foundations for decision-making on everything from aesthetics, to content directions, to site functionalities.

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Auditing Customer Cycles Following audience prioritization, it will be important to clearly and formally identify the anticipated barriers and competition per audience group and how they match to each phase of the customer cycle: •

Building awareness

Establishing understanding

Delivering value and retaining participants; and

Conversion to loyalists and advocates / ambassadors.

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Competition and Landscape The materials we received at the outset of this engagement indicated that a good deal of competitive research has been conducted to date covering a number of key areas. Government statistical sites, international statistical sites, “indicator” projects and sites, data visualization experiences, and social data sites were all noted in the material we received. In response to that, and the timeline overall, we spent little time on formal competitive analysis as opposed to quick browsing and collaborative discussions that brought our collective experiences to the table. And even in that effort – we focused much more on landscape than competition as we wrapped our brains around the concepts that underlie SUSA’s efforts and how they’ve been effectively delivered across many industries. In all cases – the next steps will be to prioritize the areas of additional investigation required visà-vis branding and strategic decisions to be made, and the wealth of competitive research already conducted. In some cases you’ll find you want to do further, formal research into a particular site or group of sites, others will come to warrant fleshing out a more specific watchlist of sites and organizations, and yet others will provide useful insight merely in their mentioning and require nothing further.

Competition Traditional Competition The majority of sites examined in the materials we’ve seen to date can be thought of as “traditional competition” – organizations offer a similar product to a similar or the same audience, or specialize in something that is seen as an integral component in the site as planned to date (specifically, the data visualization and social data sites). To that end, we didn’t spend too much time trying to expand upon this list – but named a few as when concepting investigated a potentially “investigative” side of the SUSA brand. •

Annenberg Public Policy Center (factcheck.org)

NRDC

Watchdog NGOs

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The U.S. Census – While this one doesn’t fit with the others so much – it came up again and again in any “investigative” or “trust” related discussions as it was the least questioned / doubted set of government data.

Ideological Competition SUSA seeks to bring about a change in the national discourse. To that end, there are a host of organizations, individuals, and web sites that promote and/or enable the kind of politicized discourse whose influence we seek to diminish. To that end, we must dig into what makes these polarizing methodologies successful with our targets. In the long run, this is SUSA’s true competition as they work against our mission rather than for audience share. But this list is also an important list of potential allies – in that they don’t seek to necessarily provide the same thing – and can be as willing to use what SUSA provides in reaching their audiences as any other information. Rightfully, you’ll note a heavy overlap between many of those noted below and what we collectively consider our most important audiences. •

Pundits

“Cult of Fear”

Wedge Issues

Political Advertising

Ideologists

Like many of the sites mentioned in this document, it will be particularly important that these groups be examined in the aesthetic design process, art direction, and establishment of the ongoing editorial direction. What are they providing to their audiences that we’ll need to supplant? What are the psychological drivers behind their appeal? How will we tap into them or work around them?

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Landscape Outside of competition – there are many ways to look at the landscape of experiences that our audiences operate within to glean useful insights. This landscape helps us to understand our audience expectations so we can deliver to them – with the intent to over-deliver and a guide to understanding the technical and functional complexities (and simplicities) they are accustomed to. Further we can gain insights by examining successful organizations and experiences that deliver products and services that have metaphorical similarities to those we wish to provide.

“Aggregators” These sites bring together data to provide a “data service” of some kind to users, or otherwise federate and filter larger data sets from primary sources. The first important learning we pulled from this was that most of the successful sites provide value by pulling together information from multiple sources in response to a single query – be that an actual or a metaphoric one. In many ways the “sum becomes greater than the whole” through the aggregation. •

Rotten Tomatoes

Kayak (travel tickets aggregator)

MyYahoo

It would be useful to further fill out this list and formally investigate the specific qualities and functionalities that make these particularly successful and how these qualities can be made part of the SUSA experience.

“Filters” While most “filters” have some kind of aggregation within their process, their true value is to point their audience to the most useful or interesting items within a large field. It is useful to examine not only how the “results” of the filtering are presented but also the ways these brands and experiences build a perception of trust and value with their audiences in the very filtering. •

Pandora

Hype Machine

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Other music sites – the breadth or material available (the number of genres, the number of bands and songs within each genre, the speed with which new material is released) and the difficulty of “scanning” the medium (as opposed to the ease with which we scan text or image search results, or even video thumbnails) has made effective filtering an essential component to the success of music delivery from elbo.ws to the Apple iTunes store.

Digg, Reddit, Stumble Upon – The “social filtering” provided by these services has particular relevance to the strategies SUSA has discussed to date – not only will they be a great source for learnings, but likely an important conduit and outreach vehicle once the experience is operational.

Services Given the important of delivering immediate utility, we can look to the proliferation of services that have emerged to help users post their audio and video content to their own sites (blogs, MySpace, etc.). Those that aim to help users monetize their content are particularly helpful as their business models have put a greater emphasis on giving the user both flexibility in customizing and publishing the end product, as well as functionalities that enable outreach by their customers. •

Brightcove

Cruxy

YouTube (specifically the embed and share functionalities)

Your Minis

Additional Landscape Considerations Given the time constraints and prioritizations of our undertaking, there were a number of additional vectors that came up but weren’t explored but merit further consideration: •

Discussions and forums, generally: What is driving success and failure?

Discussions and forums, political subject matter: Where is the discussion we want to be part of actually happening?

Civic contributors and influences: How are they capturing the attention and loyalty of their audiences? Are they?

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High-level Usage Flow Screens: Introduction The following high-level wireframes were created in the course of exploring the user scenarios discussed earlier. They are not intended to show the exhaustive functional detail in each screen and component, nor present allinclusive flows. Instead they focus on core tasks users will be trying to complete and the major functionalities required. As definition and design moves forward, these rudimentary illustrations will serve as a starting point – in concert with all the definitional and user interface work SUSA has performed to date – for the creation of a more complete collection of functional wireframes, user flow definitions, and screen and component designs.


User Scenario: Mary Jo


Screen  - Mary Jo selects the drill down link from her Google results and comes to a clearly labeled data page that she immediately understands.


Screen  - Mary Jo begins to push her mouse around the map and notices panels turning on when she overs over states. Mary Jo hovers over her home state of Ohio.


Screen  - Mary Jo clicks on Ohio and the map zooms in on the state, revealing a similar map that is now divided by counties in Ohio.


Screen  - Panels similar to the ones she has already seen are shown as Mary Jo hovers over her own county of Cuyahogo.


Screen  - Mary Jo starts to save the map and is prompted to create a profile.


Screen  - Satisfied that her information is saved and she is done with registration Mary Jo closes the registration panel. Mary Jo notices that the page has added messaging. Mary Jo sees her e-mail address in the top left corner and she sees the data she just saved listed on the left-hand side of the screen. Mary Jo is now more then confident that her map is retrievable.


Screen  - Mary Jo selects New Jersey, a state she just read about in a related article she found.


Screen  - Mary Jo read about obesity policies implimented in 2002, and wants to look at their impact.


Screen  - Mary Jo sees that the map changes instantly and the date is now displaying 2002.


Screen 10 - Mary Jo would like to look at the data as a bar graph because she is not familar with New Jersey geography, but does know the names of the counties from the article. Mary Jo sees the button next to the save button that has a bar graph icon on it. She clicks on it and is given a bar graph that is broken down by county using the same color key.


Screen 11 - Mary Jo is a skeptical Internet user and before she continues on she would like to know more about this data she is going to use to make her case for change. Mary Jo clicks on this “about the data� link and is delivered a screen that gives her an overview of SUSA, how it works, and where this data has come from. This makes her feel even more confident about the information she has found.


Screen 12 - Mary Jo notices that other users have bookedmarked this data and decides to take a closer look. Mary Jo clicks on John Little’s link and is delivered a profile page for John. It turns out that John is a counselor in one of the counties in New Jersey that she read about in her article.


Screen 13 - Mary Jo decides to contact John to share her situation and see if he has any insights to offer.


Screen 14 - Mary Jo has a lot of great information that she wants to review later. Mary Jo clicks the “Download” link.


User Scenario: Frank


Screen  - Frank logs into the site so he can easily save and work with the data he is about to review.


Screen  - Frank does a search for “immigration“ and is returned results for data and articles.


Screen  - Frank clicks on the first link and is delivered a map that shows the percentages of immigrants per state.


Screen  - Frank clicks on the “manage my collection� link and is delivered to an aggregate page of his stored data.


Screen  - Frank creates a new folder and names it appropriately.


Screen  - Frank clicks on the “add/remove� button, and check boxes appear next to his saved items. Frank uses the check boxes to select his two new data sets and clicks save.


Screen  - Frank wants to see these individual data sets he has collected so he clicks on the link for the “immigration and umemployment� folders and is a delivered a screen showing visual representations of the two maps alone.


Screen  - Frank wants to combine his saved maps into one widget that he can embed on his blog. He chooses the “create widget� link under the title of his folder. Frank is given some options on what to include and how this data should look. After he makes his selections he can prevew what he is going to see or get the code that he will use in his blog.


Screen 10 - Frank places the widget into an appropriate position on his blog posting. The widget is linked back to the State of the USA page and is branded with the SUSA logo.


State-of-the-USA-document-August-20-2008