We recently had a series of webinars in which we discussed a few simple ways to package your data like it's a thoughtful gift. Here is recording and slides from one of those webinars. It's just under 30 minutes, so if you missed the original it might be something interesting to watch while waiting in line to return that sweater or in between nibbles of stale gingerbread house.
Have a wonderful Christmas!
Oh yeah... and here are the slides for Treat your Data Like a Gift.
It felt like it was about time to share some of what we’ve been working on as well as review some of the Juice design principles and how they relate to sharing information. In light of the holiday season, we’ve packaged a webinar to share some of how we think you can gift wrap data for your clients. There are four sessions next week, so feel free to join us at a time most convenient for you. We'll keep these sessions to 30 minutes in length so you'll have a plenty of time to check on your other gifts.
Hope we see you there.
We're going to have a little pre-emptive thanks-giving around a meal by doing something called a Meal with a Mission, and you're invited. We'll be eating around this ridiculously earthy, awesome table at ROAM in Alpharetta, Ga.
When? Thursday, Nov. 21st, 12pm-1pm
What Makes This Meal Special? We're going to have fun and do some good together! Here's how it works:
There's $20 donation required to participate. Everyone will bring a nonprofit cause to share, an organization whose work you admire. After the meal, we'll take 3-4 minutes each to talk about our causes. We'll all vote, and the cause receiving the most votes wins the entire donation pool.
We'll be providing some 'ol fashioned homemade goodness from Cue Barbecue, an Atlanta favorite.
Sign-up here to donate and participate.
We can fit up to 16 folks around the table, but if more sneak in, we'll try to squeeze! If you're in Atlanta or passing through, we would love to see you.
Thanks! Can't wait to see you!
A few weeks ago, while visiting in Virginia for work, I ended up on M Street in D.C. with a couple of co-workers. One of us was going to a meet-up and the other two of us had time to kill. (One thing you should know about me before we proceed is that I am a big—and I mean BIG—cake/cupcake fan. Have you heard of DC cupcakes? I don't watch it regularly, but I am very aware of it. I'm also aware of a lot of other big cupcake joints, like Sprinkles Cupcakes. So...)
Once I realized where we'd ended up with time to kill, I was immediately on a mission to find DC cupcakes. In the process we discovered a bonus: Sprinkles Cupcakes was only a few blocks away. One of my favorite things to do is compare flavors of cake from different places and see which I like better. Clearly, I need CAA (Cupcake Addicts Anonymous).
I won't bore you with all the details of the cupcake tasting (though it was delicious fun) but we did find some great everyday visualizations to share. Given that we are visualization nerds, it's only natural that while taste comparing the cupcakes, we also compared their visual menus that you can take with you on their visualization merit.
Let's start with the Georgetown Cupcakes menu. It's pink - I dig that. But beyond girly color, it has some other great features. Though it's not really a "typical" visualization in that it doesn't replace text or anything with visual elements, but it does have kind of a visual layout. To outline a few things it does well:
1. The way it's broken up by day (columns) makes it easy to search for the day you are there and find the cupcakes available.
2. It's broken into three "rows" so to speak, with a "row" for everyday, special and advance flavors. This is helpful to quickly find the break between everyday flavors and the other flavors.
Things it could do better:
1. The everyday and advance order cupcake flavors are the same for every day. It seems you could focus more on playing up the special flavors, since that is where the variation lies. Plus, you could save space and ink.
2. Within the special flavors it can be tough to find which days a particular flavor falls on easily. In the everyday rows, the same flavor is always on the same row. Not the case in the special section so your eye does a lot of jumping around trying to search for the same flavor on different days.
Moving on to the Sprinkles Cupcakes menu. It's more of a visual menu than the other.
1. It's easy to find a flavor you want and figure out which day it's available.
2. It's slightly less easy but still not hard to find the day you are there and see which cupcakes are available. There's a little more eye movement involved since there are more flavors.
Things it could do better:
1. I don't know that it really adds anything really valuable to the visualization, but the colored dots do correspond to the dots on top of the actual cupcakes. If you were having trouble reading the signs in front of the cupcakes in the case, that could be helpful for cupcake identification I suppose. A way to make the dots more helpful would be to correspond their colors more closely to the flavor they represent. The colors are pretty though.
2. No seasonal flavors are listed.
Aside from the visual aspects of the menus, another thing I like about the Georgetown Cupcakes menu is that on the backside, they have great descriptions of each cupcake flavor. As a cupcake lover, I find that helpful. Just sayin'.
And if you love cupcakes like I do and are curious which cupcakes are actually the best, you might be disappointed. They are both delicious—preference between the two comes down to...well...preference.
If you want a little cake with your icing and believe a cupcake is not a cupcake without a great icing, Georgetown Cupcakes might be your pick. Their icings were off the chart awesome! Just give me a shot of the icing, hold the cake.
If you dig cake and could take or leave the icing, you definitely want Sprinkles Cupcakes. Not only do they put less icing on each cupcake, but the cake (and how moist it is) really stands out above the icing.
In a perfect world, I'd combine the two. I need both to feel truly cupcake satisfied. What can I say? I want it all. I guess you could say it's the same with the menus: combine the find-what's-available-today easiness of the Georgetown menu with the when-are-they-serving-my-fav icon layout of Sprinkles and it'd be a match made in heaven. Until then, I guess I'll have to keep searching. And tasting. It's tough work, but someone's gotta do it.
So there you have it! A breakdown of cupcake menus! Who knew cupcake hunting could be so visual?
“Data is the new oil.” -- everyone (first by Clive Humby)
"Treat data like money." -- Jim Davis (SAS CMO) in The Economist
Are you are sitting on a gold mine -- if only you could transform your unique data into a valuable, monetizable data product?
Over the years, we’ve worked with dozens of clients to create applications that refine data and package the results in a form users will love. We often talk with product managers early in the conception phase to help define the target market and end-user needs, even before designing interfaces for presenting and visualizing the data.
In the process, we've learned a few lessons and gather a bunch of useful resources. Download our Checklist for Product Managers of Data Solutions. It is divided into four sections:
1. Audience: Understand the people who need your data
2. Data: Define and enhance the data for your solution
3. Design: Craft an application that solves problems
4. Delivery: Transition from application to profitable product
Happy drilling.
JuiceChecklist-ProductManager
From time to time we call in some data muscle to help on a project or to brainstorm about a problem. Harold, Amanda and Sean at Five x Five have been awesome data resources, colleagues and valuable part of our little Atlanta Data Village.
Here is a link to their website as well as the meaning of Five x Five in case you don’t know. Great name for a data company. We finally convinced Amanda to write a blog and share some thoughts. Enjoy!
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We hear some version of this phrase, often with a heavy dose of exasperation, during preliminary meetings with nearly all of our clients.
The vast amount of data – be it transactional, customer-level, sku, property, etc. – available these days can be as much a source of stress on marketers as it can be valuable. “Big Data” is now practically a household term, but what do we DO with it? How do we make it manageable?
For us at FIVExFIVE, data is all about delivering meaningful insights through segmentation, prediction, and optimization. The reality is that before we can get to any “fun analytical stuff”, we spend about 80% of our time on exploration and cleansing – discovering the “smaller, manageable, and meaningful” Big Data
Here is a small flavor of the steps to get your data ready.
Data Validation
Pattern discovery
Data Cleansing
Data Analysis
Variable Reduction
Once your data has been cleansed and processed, you then try to answer some of the BIG questions. What will be actionable, interpretable, and relevant? Its only after you figure out the relevant questions can you then begin to narrow down the sometimes thousands of columns to determine what really drive business results, satisfaction or profitability.
Even after you’ve made sense of the data and developed an analytical solution, you’re not finished. You have to visualize/present the results in a way that the decision-makers value the analysis, make a decision, and want more. Keeping it simple, and saying as much as possible with as little clutter or extraneous displays of data is an art. Trust us. It isn’t easy for statisticians to admit this, but delivering beautiful, much appreciated visualizations is as much fun (and valuable) as the modeling terabytes of segmentation data.
Marrying all these disciplines and steps is what has to be done to turn your Big Data into the Best Data.
Have a perspective about “the process” that differs from ours? We’d love to hear your thoughts. Drop us a note at info@fivexfive.com.
If you haven't noticed via various posts and examples, like our Fantasy Football Leaderboard, we are big sports fans. Over the past year we've gotten to know Ryan McNeil (a former NFL defensive back) pretty well. Learning about the subtleties of college and professional football, as well as sports media, has been fascinating. As you will see below he is very excited about the new season and the opportunities for better use of data in the profession. Or it could be just that his Hurricanes are currently 3-0. Enjoy!
I love this time of year. The anticipation of the first week of NFL football always gets my “juices” (pun intended) flowing. I’ve been astonished by how much data has changed the game since my playing days.
While Sabermetrics, APBRmetricsMoneyball and sports analytics conferences are now well known, the use of data in sports is still in its infancy. The use of information is still exclusive to team leadership (owners, GMs and coaches) and their analytics team. The next wave of data in football and all sports is just starting and ironically I have the same feelings of anticipation as if a new season is just starting.
The next wave is the use of data across many new audiences including agents, players (professional, college and high school) and fans. This doesn’t mean that we’re going to turn them all into data scientists or that soccer moms will be sharing their R analyses with coaches, but it does mean that data becomes a much bigger part of the sports conversation.
The greatness of football (and sports in general) goes beyond the game experience itself; we also love the conversations, bonds, and memories that are created at every game. What I’ve learned over the past couple of years, particularly being so involved in the media business, is that enhancing these conversations among players, between players and coaches, between agents and teams, and between teams and their fans enhances the sports experience.
So, what has to happen for this next wave and these conversations to take place? First its not about just giving everyone a new playbook or raw data, but delivering data applications.
A data application is a focused solution that attempts to answer one question or explain a single idea. Questions like:
Data applications often benefit from being available on mobile devices and should be visually engaging, leveraging the latest data visualization techniques.
Visualization is the WOW factor. It can engage players to better understand coaches and agents. It can improve younger players learning curve. Have you ever seen the three ring binders we got to learn plays? For the fans, it can further draw them into the details of the game.
The season of data is only beginning and it’s very exciting. I’d love to hear what you think some of the data applications should be as well as what questions need to be answered to get players, agents and fans more engaged with data. Email me at rdmcneil@ot-network.com. I’m anxious to hear what you think. Now, are you ready for some football?
Ever feel like your great data communication documents don't quite live up to the standard of readability you've developed for your data visualizations? You're not alone. Somehow, most of us were never trained either in the education system or in our professional careers on how to properly format our text. As a result, it's oh so easy to just use whatever Word or Google Docs tells us to (you know you've done it: Courier New, anyone?)
That's why Juice created the Simple Font Framework. It's four simple steps to formatting headers, text body, notes... the works... so that it's clean, readable, and beautiful. Interested? Check out the video here:
Now, once you watch that video, you'll likely have your curiosity tweeked, so we're including a another video for more in-depth font-a-licious information on understanding the mysteries of fonts (like: what exactly does "sans serif" mean?)
Now, what are you waiting for? Go make your text look great with Juice's Simple Font Framework!
As you can imagine many of the clients and people with whom we interact on a daily basis are data analysts or some form of analyst in one way or another. I’m amazed how we are still learning about new tools and data “tricks” all the time from the folks we meet. These are all very smart and talented data savvy individuals, but is being an analyst enough?
It’s tempting to lock our minds and bodies into our comfortable air-conditioned cubicles and churn numbers and crunch data all day long, and then lob it over the cubicle or office walls for our boss or peers to review, without worrying about outcomes, or the possible interpretations.
Being on the front lines every day the Juice Team is witnessing an evolution of the modern-day data analyst. Producing static reports, hitting the email send button, and answering periodic questions doesn’t work anymore.
The really impressive “analysts” we speak with now do much more than analyze data and produce reports. So much more that we’ve taken to calling them "data presenters". There’s probably a much better name, but it seems to be the one that has stuck.
What are the attributes of a data presenter? Well, on top of being an Excel guru, pretty savvy with Tableau and not bad with SAS or R you probably have some combination of the following traits:
Another observation that may help is that data presenters generally are not created overnight. They tend to emerge over time. And over time we’ll be watching, because after all, we’re striving to be better data presenters, too.
We met Raleigh Gresham recently at Atlanta Product Camp and immediately found a data kinship. We especially loved one of his blog posts on To Do Lists and got permission to post it here on the Juice blog. You can check out his post below and other writings here.
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To do lists. The pinnacle translation of any data set. The final act of simplification for any analysis.
They are reports in their most primal state. They achieve the ultimate goal of any applied datum, answering the core question “what do we do now?”
For the rare data user hoping to generate utility from their analytical efforts, this simplest of reports is worth fighting and editing for. They demand data isolate the next actions. Ignoring the excuses of technology and governance that are liberally used by so many in their field, they relentlessly “sculpt” the data with analytics until the simplicity of checkboxes is all that’s left.
When this data dharma is finally achieved, they are done. They add nothing more. They make no apologies for the simplicity or the unfamiliar clarity of the result. A to do list leaves no room for the theory-making and hypothesis-spinning rendered by common reports. There is no buffer for interpretation. The comforts of second guessing dissolve. Someone becomes accountable for action.
To do lists are ruthlessly challenging to achieve. Most analysts do not have the stomach for them. To create to do lists, one must be willing to call action out — to recommend movement. Action is risky. Movement changes the status quo. It takes great resolve to settle for nothing less than a to do list.