Data Monetization Workshop 2018: Key Themes & Takeaways

“Data Monetization is a hot topic because it has two words that everyone loves. We all love data, and who doesn’t want to monetize something?”

These were the words that kicked off the 2018 Data Monetization Workshop to a roomful of attendees and industry experts who had gathered to discuss the question that followed this observation: what does Data Monetization actually mean?

This question was discussed at length over the course of the half-day event and was the impetus for speaker topics related to using data for social good, how to account for data on a balance sheet, how AI will affect the future of Data Monetization, and more. Here are some of the most important themes and takeaways from the discussions of the day.

What Is Data Monetization?

• Data monetization is about data value, not data dollars. It’s not about selling customer lists, but about deriving value.

• Data Monetization encompasses business intelligence and takes a much broader perspective on what can be done with data. Analyzing what options exist outside the enterprise, what products and services can be created using data, and trying to get data into the hands of decision-makers are all components of Data Monetization.

Data for Good

• Most organizations aren’t trying to sell your personal data; they’re focused on using information to improve city performance, prevent mass shootings, and rescue people from sex trafficking.

• Nobody owns data. Companies and organizations have rights to data, but in order for progress to be made data must be shared and communicated.

The Dark Side of Data

• While data offers many beneficial opportunities, there also exists a dark side of data. What complications does something like what happened with Cambridge Analytica have on future opportunities for Data Monetization?

• Using certain data is not always a question of “Is this legal?” but rather “Is this ethical?” Sometimes data is available but not right to use, which can feel like a restraint at times but leads to being an organization being perceived as trustworthy. It is important to have a solid core philosophy on what data you do and don’t use before it becomes necessary to bring in lawyers and PR teams.

Education, Train, Explain - Data Literacy

• Poor data literacy is seen across the board. If you don’t read the fine print, you can sign your data rights away. Many problems with the use of personal data are often due to mismatched expectations.

• People don’t always understand how valuable data is and what an asset they hold. You have to teach people to think in technicolor. Some companies try to exclude information, but more information changes the landscape and provides more context.

• Creating data products with different derivations is one way to communicate data to different roles (e.g., an analyst versus a CEO). You have to meet people where they are.

• Being transparent with a product roadmap is a great way to demonstrate to people that data products will look different as time goes on. Users can know what features they can expect and when.

Doing Things Differently and Looking to the Future

• There are emerging technologies that can help make processes easier. Right now you just have to ask yourself, “How can I do things a little bit differently today?”

Doug Laney Is One Cool Dude

• Doug Laney was kind enough to join us remotely from his vacation to answer audience questions about his book Infonomics -- of which every audience member got a free copy!

Special thanks to all of the speakers, to MapR for sponsoring the post-workshop networking reception, and to everyone that attended! If you have questions or comments about the Data Monetization Workshop, feel free to reach out to info@juiceanalytics.com.

Related Reading:

• Lessons from a Data Monetization Workshop (2017)

• Three Keys to Data Monetization Success

• Data Product Resources

4 Steps to getting started with data products

Over the years, we’ve had the pleasure to work with many great individuals and companies and through our work have gained the ability to sympathize with their experiences of what we like to call “going from 0 to 100."

No, we’re not endorsing excessive speeding in your car. We’re talking about going from having nothing but hopes and dreams about delivering engaging analytics (0) to having an interactive data story that your users don’t want to put down (100).

Because we’ve focused our efforts on taking clients from 0 to 100, commonalities or trends for best practices in the data and design experience (read: everything between 1 and 99) have become increasingly clear. Use these four tips to make your introduction to data products a better, more frictionless experience.

1. Know your audience

• What do the end users you have in mind for the product look like? What questions will users ask of the data? What actions will they take with the answers to these questions? These are all things you should know before beginning to work on data products.

• Be specific about for whom you are creating a data product. If you try to provide insights for too many types of business roles you run the risk of making it too broad for any role to gather insights from the data.

2. Gather the right data

When putting together the data to be used in your product, it’s important to discern the difference between “more data” and “more records."

• More data: It’s not always in your best interest to gather the most “data” possible. By doing this, you run the risk of gathering data that you may not use and wasting money in the process.

• More Records: Gathering “more records” (read: rows of data) is a better strategy as you prepare for your data product. Doing so can alleviate the effects of outliers and unearth trends in the data.

3. If you’re new to the data, begin with an MVP (Minimum Viable Product) and let your users determine what features should be included

Building out all the bells and whistles you think you might need at the beginning the data product’s life can be expensive. Starting with an MVP that is put in the hands of actual end users will help determine what data is actually needed and what design aspects are best for your purposes.

• Helps with data: Starting with an MVP helps determine the shape and caveats that exist within your data, and allows your users to make decisions about what data is most important to them.

• Helps with design: By starting with an MVP, all of the questions that you and your users have for the data are answered by the design. Additional features can then be added from that point on in a more cost-effective manner.

4. Be open-minded about visualizations

• We won’t get into data visualization principles in this section because that warrants a totally separate article, but a simple point here: just because you saw similar data in a pie chart once doesn’t mean that is the only (or best) way to visualize your data.

• Because your users are the ultimate consumers of the data, let them be the judges of what visualizations will be most effective for them.

Easy peasy, right? We think so, but maybe that’s only because we’ve helped so many customers get from 0 to 100. If you're still not sure what your next steps should be, we’re here to help. Learn more about our 0 to 100 process by checking out the document below.

What's in a Juicebox: Connected Visuals

The ability of an excel novice (i.e. me) to use a pivot table is basically naught. My ability to manipulate data does not exist, and yet I work for one of the most forward-thinking data presentation companies! Nevermind why I was hired, I quickly learned how to use a Juicebox application because Juicebox is designed with the everyday end user in mind. We have tackled the problem of data delivery to both analytical and non-analytical groups. In this post, I want to chat about one of the features that make that possible: connected slices. What is a slice? A slice is a Juice term for a data visualization within a section of Juicebox application.

I have mentioned before that Narrative Flow is important to Juicebox. Our applications are web-based and users expect to move and navigate from top to bottom, like when interacting with a webpage. Part of that movement from top to bottom in Juicebox means that as the user is making selections within the application, those selections should not only carry down the page but that they should also inform the visuals that follow.

We strive to be the world's best platform for telling data stories and because of that connecting our visuals together is vital. When someone makes a selection in the topmost slice, it places a filter on the data and the selection they make. This filter helps the user narrow down their selection and drill into the data.

Much of the problems with static reports and dashboards is that they only give the user a top-level view of his or her data. Traditional solutions do not provide the ability to drill further to discover what factors could be driving the data. In essence, today's charts, dashboards, reports, and BI solutions give the user a snapshot and not the whole story. 

Curious to see what else is included in Juicebox? Check out some of these posts highlighting other unique features:

• What's in a Juicebox: Narrative Flow
• What's in a Juicebox: Discussions

Getting unstuck: Give your data a jumpstart

It’s a predicament that we’ve seen many times over: your data is stuck. You’ve tried some reporting through some Excel pivot tables, or you’ve messed around with a Tableau trial, but felt like there wasn’t enough engaging content to get your users excited. Rationalizing why you can’t get your data to be impactful for your business, you think things like, “maybe my users are talking about the data but I just don’t know about it” or “maybe the data isn’t structured in a way that allows for valuable insights to be extracted from it."

If you’re sitting there thinking that your mind is being read by our artificial intelligence, you’re wrong. It's because at Juice we have seen this scenario played out too many times and we’ve made it our mission to make these issues a thing of the past. What you need to do is give your data a jumpstart.

Here’s our suggested plan of action for getting your data unstuck and giving it the jumpstart it needs:

1. Get your data into a readable structure.

• The first row of your data should always represent the column’s title

• Columns should contain the same type of values, respectively

• Each row should represent a case or a single instance within the data and should contain a date of when that data was collected. This means that two different rows in the data can represent the same entity with data collected for it at different points in time.

• As a consequence of the rule above, the data should include a row identifier column that can be repeated to indicate that different rows of data are representing the same entities.

• Make yourself a metadata sheet (also commonly known as “data definitions”) that you and other users of the data can refer to.

Here are some simple example data & metadata using the principles above.  

2. Present your data in hierarchical manner catered to specific audiences.

• Give your audience a call-to-action, let them know why the data is important and why they should care.

• Begin with presenting high-level key metrics. Think about what the most important numbers are you to your intended audience(s).

• Give your audience the option to select a few different categories in which to segment and parse-out those important numbers. Doing this will allow your audience to drill-down in the data to get from a high-level to a granular level.

• Allow your audience to take the data they have drilled down to with them. This could be one row of data out of the thousands they started with at the high-level.  

Here’s an example of this data presentation flow.

3. Engaging your audience in data discussions

• This one is self-explanatory: talking about the data with others is the best way to squeeze the value from it.

Here’s an example of effective data discussions.

Sounds like a good plan of action, right? If you're still not sure what your next steps should be, we’re here to help.

We’ll work with you to get your data in a structure that makes it valuable, or even create data for you. We’ll build you a data story with that data that helps you and your users understand the data so that you can turn data insights into business actions. We’ll get your users engaged in data discussions and app design feedback so that you know they’re engaged with the data and you know how valuable they perceive the app to be. So drop us a line, we’re here to help.

6 Cool Companies Who Are Rethinking How We Work

It can be a challenging climb to reshape how people think about solving problems. We encounter this challenge daily as we work to build the best solution for communicating data the world has ever seen. We operate in an arena where good-enough solutions — Excel, PowerPoint, and other visual analytics tools — have left people with deeply-rooted habits and a blasé acceptance of the status quo. That’s not good enough for us, and it isn’t good enough for these six companies that are rethinking how business tools should work:

Slack

Slack is the current king-of-the-hill for shaking up the status quo. Sure, we had email, file sharing, and messaging apps before Slack, but we didn’t have single, elegant tool for team collaboration.

What’s cool about it?
Slack made integrations easy from the start. We use everything from ChatOps with our development team to HeyTaco for everyday appreciation of our colleagues. Slack's approach to 'channels' found the right balance for open communication by topic.

Flourish

I only recently stumbled across the excellent visualizations available through Flourish. There are many, many tools for putting data visualizations on a screen; few vendors are so obviously passionate about their craft. 

What’s cool about it?
Flourish is more than another charting library — they are making world-class visualizations accessible. I was particularly impressed by the clever use of animation in those visualizations. At Juice, we appreciate that new users won’t always be able to read a visualization without some guidance. Animation can help draw a user’s attention to the most important information right off the bat.

Kialo

Kialo is “a debate platform powered by reason.” It cuts through the noise of social and online media by removing the worst parts of debating online (trolls, fake statistics, unrelated cat gifs) while strengthening the best.

What’s cool about it?
Kialo creates a structured dialogue with visualization, voting, and commenting. Whether discussing politics or the merits of a new project, Kialo has focused on an overlooked need: a place other than the comments section to examine arguments and consider new viewpoints. 

Typeform

Typeform is "the versatile data collection tool for professionals." It's a thoroughly modern survey-building solution that I’ve enjoyed using for over a year.

What’s cool about it?
Typeform's survey-authoring interface is remarkably intuitive. Adding questions, structuring logical flows, and navigating your survey is silky smooth. Similarly, the end-user experience is beautifully designed with selectors and animations that make it (almost) fun to fill out a survey.

Beautiful AI

From the founder of SlideRocket, Beautiful AI is a next-generation solution for creating web-based presentations. They say all you have to do is "think of an idea, choose a template, and get to work."

What’s cool about it?
Beautiful AI has taken a giant leap past a tool like Google Slides. It comes with a collection of smart slide layout templates. Better yet, these slide layouts automatically update as you add more content. The tool also comes with an easy-to-use integration with third-party image libraries so you can incorporate pictures into your presentation.

Toucan Toco

A data storytelling solution to build data apps for your business. We may be a bit biased, but that sounds awesome.

What’s cool about it?
While I don’t have hands-on experience with this solution, I love their message. Like Juice, they see the need to:

• Communicate data to non-analysts with guided narratives ("Address the remaining 99% of your employees”)

• Create targeted applications that solve specific business problems (“A business need = an app”)

• Include simple, clear data visualizations ("The comfort of using consumer apps, finally in a business setting”)

Honorable mentions

• Quid: Quid puts the world’s information at your fingertips, drawing connections between big ideas.

• Skuid: Accelerate deployment of personalized applications that let your business people drive innovation, without the wait.

• Trifacta: Trifacta enables anyone to more efficiently explore and prepare the diverse data.

• Datawrapper: Datawrapper makes it easy to create beautiful charts.

Thinking about changing the way you work? Check out our app trial process. Download the info sheet below to learn more.

Data Fluency Dorks Unite

How we communicate data is broken.

There. I said it.

It may not be nice to hear, but deep down you know it's true. You can see it in the way that data gets delivered to audiences: email attachments no one wants to open, 50-page slide decks filled with never-ending complex charts, and scrolling pages of dashboards with no context around them. It's not only messy, it interrupts the ability to adequately share and communicate important information about data.

So what's the solution? How do we deliver data to audience where they can draw out conclusions and information that is going to be meaningful to them? The answer: data fluency.

Data fluency, or data literacy, is something that we at Juice have been talking about for years (we literally wrote the book on it). We recently sat down with Dalton Ruer, or as he's more familiarly known around the web, QlikDork, to discuss the details of data fluency and how to achieve it. Check out the video below to hear from Juice CEO Zach Gemignani and Global Head of Data Literacy at Qlik Jordan Morrow and learn what having data literate consumers means, how to get good at choosing visualizations and weaving them into engaging stories, what a data fluent culture looks like, and so much more.

Related reading:

• Our new book Data Fluency may not be for you
• 4 Components of the Data Fluency Framework
• Top Signs Your Audience Isn't Data Fluent

You're Invited: Data Monetization Workshop 2018

Juice is proud to announce that it will host the third annual Data Monetization Workshop on Thursday, March 29, 2018 at the Nashville Technology Council’s Tech Hill Commons. Created by local data expert Lydia Jones in 2016, the Data Monetization Workshop brings together some of the top data and analytics practitioners in the country to discuss how to deploy data monetization in a business setting.

This year’s workshop will feature speakers and panelists from companies such as BuildingFootprintUSA, Crystal Project Inc., Dawex, Digital Reasoning, and Uber. The topics covered will be: 

• The Now: What are the opportunities and business models you should consider to monetize your data? E.g. enhancing existing products, new data products, data marketplaces.

• The Future: How will emergent technologies such as IoT and AI unlock new opportunities and challenges for data monetization?

Prior to the workshop, attendees will have the option to attend a data storytelling seminar led by Juice Analytics employees. The seminar will showcase Juice’s unique method for quickly and easily creating data stories from a given data set. The workshop will conclude with an open bar networking event.

Attendees in the past have come from Florida, Texas, New York, Georgia, California, Canada, and Australia, and across industries such as healthcare, finance, retail, technology, and government. They are typically members of the C-Suite (including CEOs, CMOS, CFOs, CXOs, and CAOs) as well as data and analytics leaders, data scientists, investors, and data product development leaders, among others.

To learn more about this year's Data Monetization Workshop, visit the link below. Please be sure to register in advance as seating is limited. We hope to see you there!

What's in a Juicebox: Narrative Flow

Do you remember when Facebook first launched its News Feed? I do. I can recall complaining with friends that it was "too stalker-ish" (we were right) and that "no one was going to use it" (we were wrong).

Today it's hard to imagine Facebook without its signature News Feed, but for a long time I did not care for it at all. That's because once people get used to a certain way that things operate on the web, they don't like it when those practices are changed. Not only do they dislike change, but they come to expect certain design practices online. Take for example the horizontal navigation bar found across the tops of web pages: around 88% of websites have its main navigation panel there on every page. Nine times out of 10, that's the first place a user will look when attempting to navigate through a website.

Another piece of design experience that all users expect is vertical narrative flow. Web pages flow from top to bottom and as you want to learn more about a company, product, piece of news, etc. you scroll down.

Juicebox is not unique among BI solution to offer a design layout that flows from top to bottom. Infographics and web pages have taught us that people want to read data the way the same way that they read text. However, Juicebox has a special ability to seamlessly connect the narrative flow, dynamic textual content, and complex filters to give users an effortless experience while navigating data.

Narrative flow is essential to the experience of Juicebox and our user-centered design. As a user interacts with a Juicebox application, they are continually making decisions about what they would like to see in the data, what relationships are most important to them between segments and tables, and what details they need to make informed decisions. All of these complex interactions are done behind the scenes as Juicebox provides that infographic-type feel in a web-based format.

Can you think of a situation where you need to deliver data to an audience of users? Maybe it is customer reporting or a data model that needs a user interface for people who are not data savvy. In recent months we have made it even more easy for you to get started with Juicebox. Through our Guided Design Process you can see your data in Juicebox and give access to 10 users so that they can experience the ease of navigating through your data in a narrative flow. To learn more about Juice's Guided Design Process, check out our resources page.

You Don't Need a Slide Factory

You might be surprised to learn that one of our most popular blog posts of all time is Automated PowerPoint Generation, or Making a “Slide Factory.” Even though this post was published almost nine years ago, month after month we continue to see it rise to the top of our most visited pages. 

Whenever someone reaches out to us asking if we have a ‘Slide Factory’ solution, we tell them two things:

1. Sorry, we do not.

2. You don’t actually need a slide factory.

In fact, the need for automated presentation delivery is the genesis of our data storytelling solution, Juicebox. We are intimately familiar with the need to deliver data to customers, co-workers, stakeholders, etc., in a consistent, structured manner that communicates a message while providing each person with the data that is most relevant to him or her. Instead of attaching a 50-slide PowerPoint deck, Juicebox does that same job with an interactive reporting application. Users benefit from a guided analytical story, ability to capture insights, and features to collaborate with others.

Not only do your users benefit, but you no longer have to deal with report production and ad hoc headaches! Juicebox was designed with the data consumer in mind, meaning that the need to spoon feed your audience data and information through long-drawn-out PowerPoint slide decks is no more. 

In recent months, we have made it more affordable and simpler than ever to get started with Juicebox. Through our Guided Design Process, customers are seeing what their data looks like in a Juicebox application within days not months. We give you four weeks and ten user accounts to test Juicebox with your data, you have plenty of time to get user feedback and build a business case for using Juicebox. Pricing starts at only $6 per user (with a 50 user minimum). With tiered discounts for more than 500 users, Juicebox is a competitive option for any budget!

If you would like to test drive your data in Juicebox, fill out our Get Started form and we will be in touch ASAP.

Check out some of our Juicebox apps in action:

• Nashville Arts Grant

• Virginia Economic Development

Gift Ideas for Data and Visualization Lovers: 2017

It's that time of year again. Thanksgiving is over, and the mad dash to find the perfect gift for everyone on your holiday shopping list is on. If you're anything like us, you've got a number of data visualization enthusiasts on that list that you just know are going to be particularly difficult to buy for. Thankfully, we're back with our annual gift guide created specifically for people who love data and visualization. Read on to find out exactly what to buy for your data-loving friends and family.*

Books

Just like last year, we're kicking this gift guide off with a selection of books that we think any data lover would enjoy. While there are so many excellent books on data visualization to choose from, these are a few of our favorites that were released (or re-released) this past year, with a few old classics thrown in as well. 

The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave

Semiology of Graphics: Diagrams, Networks, Maps by Jacques Bertin

Visual Journalism: Infographics from the World's Best Newsrooms and Designers by Javier Errea

Infographics: Designing and Visualizing Data by Wang Shaoqiang

Presenting Data Effectively: Communicating Your Findings for Maximum Impact by Stephanie Evergreen

Storytelling with Data by Cole Nussbaumer Knaflic 

Beautiful Evidence by Edward Tufte

Data Fluency by Zach and Chris Gemignani

Art

A few years back, Juice gave each of its employees a piece of sound wave art and it was a huge hit. One employee actually loved his painting so much that it now hangs permanently in Juice's Atlanta office. These pieces are not only custom and unique, they're absolutely beautiful visualizations of something that everyone loves: music.

For Kids

It’s never too early to start introducing the children in your life to the wonderful world of data, visualization, and technology. Instead of wandering through toy stores frantically searching for Fingerlings, consider instead one of the cuter, cuddlier, and less noisy distribution plushies from Etsy seller NausicaaDistribution. These visual guides to Star Wars and comic books make for great introductions for kids and teens to the wonderful world of visualization. And if you want to start them really young, check out the Code-A-Pillar from Fisher Price. It's a seriously cool toy that involves planning a path for the robotic caterpillar and getting it to follow that path using coding.

For the Data Lover Who Has Everything

What do you get for your data loving friends that already have everything on this list? How about the most customized visualization possible - one of their DNA! Give someone the ultimate information with either a 23andMe or AncestryDNA report that details his or her ancestry, food intolerances, and so much more! It will definitely be unlike any other gift they've ever received before.

These are just a few ideas for gifts for your data-loving friends. For more ideas and inspiration, check out our gift guides from previous years. And of course, have a very happy holiday season!

Related reading:

• Gift Ideas for Data and Visualization Lovers: 2016 Edition
• Gift Ideas for Data and Visualization Lovers

*Or for yourself. We don't judge here.