Digital Root

The Mind-Language-Physiology Link

When I was a boy, I believed that people with blue eyes could perceive the color blue more acutely than people with brown eyes.

This research doesn't exactly prove that, but it does suggest there's a mind-language-perception link going on.

It was clearly the language system interfering with a task that was presumably purely visual: distinguishing between different colors. Categories in our thinking may go much deeper than we think.

While not conclusive, this research indicates that having a greater definition of a given color enables perception to a more granular degree.  Its conceivable that this language-physiology link permeates our ability to think and perceive well beyond colors.

Agile Is Dead

Agile methods for planning - from software to market research - have evolved to a buzz/hype laden, heavy, and bureaucratic burden. At least in many shops that have too many people bearing spreadsheets and too few creating unit tests.

In practice I've restricted Agile/RUP/XP/etc to the minimum applicable elements necessary to get the job done consistently and humanely. Typically this means a basic sizing/risk estimate for discrete stories (oops my 1990's XP training is showing), pushing the high risk elements into early prototyping, burn/build tracking and iterative assignments. 

Generally it gives our teams what they need - projects that have the features and functions it needs, clear visibility, ability to change scope and assurance of date/budget delivery.

Applied to planning (advertising / product or research) a recent book eschews the mythos and hype around agile and boils it down to simplified experimentation. I read a good review that simplified it even further:

It's about doing the minimum amount of work needed to get to, or inspire, an idea.  It's about cutting down the waste - things like deliberating adjective soup and brand vegetables for 3 months.

It's about generating hypotheses that can be tested, not sitting in an ivory tower with a damp towel on your head waiting for the answer to appear like divine inspiration.

It's about making stuff that can be tested in the real world, not running weeks of focus groups to hear people talk about how they think they think or might behave.

It's about making as few charts as possible to explain a strategy or idea - get to the work

It's about understanding that strategy has to evolve and morph over time (whilst being aware there's a danger that this could become an excuse for superficiality).

It's a bias to doing over thinking.  

It's about doing stuff to learn stuff.

It's more like experimentation than planning as we know it.

 

 

Bullet Time With Motion Video

Bullet time - the effect popularized in The Matrix - typically uses 24 still images stitched together to create a single from of video, or video-like dimensional motion. Working with the medium however, presents limitations when you want to tell a story using flowing motion and moving components.

A series of intelligent tools from Revisionfx introduces an amazingly simple, yet effective mechanism to achieve the effect of bullet time while still using video.

The particular tool, Twixtor intelligently combines sequence frames allow you to speed up or slow down the action to achieve the effect. These are two great examples of using lo-res video with Twixtor to generate cinematic effects with standard tools.

Experience Human Flight from Betty Wants In on Vimeo.

 

More Super Slow Motion [Water] - 550D from Rickard Bengtsson on Vimeo.

 

 

Simple But Brilliant: UX Mobile Stencils

When designing websites, the first place we often go is to the wipe board or a sketch pad to block out ideas. Mobile applications however don't translate as well because of the inherent size and unusual form in which widgets take shape.

Enter UI Stencils.  Sleek stencils and notepads designed to make it simple to quickly mock up mobile apps with pencil and paper. These will allow designers and creatives to put ideas into action collaboratively while keeping close to the final form it'll take in a graffle or wireframe.

Showing Numbers In Context

The Boston Globe demonstrates the value of showing numbers in context when building charts.  Often times, charts will casually depict numbers on different scales (e.g., Millions and Billions side by side) which obscures interpretation.

When creating visualizations, try to keep values on a relative scale whenever possible. If not, try to create a common measurement for context (as Shaq is below).  And when all else fails, try using a natural log version to illustrate the relative shape of the data.

 

When Good Design Happens To Bad Data

This infographic has been getting all kinds of love on Mashable. While it was created by a professionals I know and respect, it frosts me when wishes are presented as fact.

A portion of the underlying data originated from the ecumenical Addthis  of Clearspring Ad-network fame, but the comparative set is fit into models that are dubious at best.  Taking unlike metrics (e.g., Facebook's Monthly Active User, vs number of Gmail accounts) and using them for corollary or comparative models is risky if not deceptive form.

In the case of this infographic, the objective is to transfer the merits of well-known data (addthis tracking data) to unknown (pretty much everything else) and obscure the equivocation with slick design. 

It's doing exactly what most people expect advertising to do; Lie.

Mary Meeker is a Copy Cat

A week after I wrote about Mobile web trends pointing to a new form of data consumption,  Mary Meeker publishes a report supporting the same theory. 

Except she included a bunch of research baggage and such.

Internet Trends 2010 by Morgan Stanley Research

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The Future of Mobile Web

Prediction: by 2015, 60% of web traffic will come from Mobile devices

While the emergence of social media has captured the attention of every blogger, journalist and advertiser, another more fundamental trend is positioned to disrupt the computing experience; Mobile Web.

Earlier this year, Mobile data traffic surpassed voice traffic across the globe. A trend that researches believe will continue to grow over the next 5 years.

At the same time, the information rate is doubling at nearly the pace of Moores law.  IBM estimates that by 2015, information published digitally will double every 11 hours.  When taken in context of mobile data usage, the way we process information will be significantly altered.

As by-product of the mobile experience is UX efficiency. Designers don't have the real-estate or bandwidth of normal computers. Instead, they have to focus on targeting applications based upon location, usage, function and utility.  An unexpected result is that mobile data consumption is not only smaller, but more filtered than web based.  Advertisers take note: If you think the move to digital is difficult, get ready for communicating to 60% of your audience with 1k instead of 30k.

A few examples of how this is starting to take shape.  Yelp recently released a report about their iPhone and web originated traffic.  While mobile represents less than .5% of their visitors, they generate 27% of traffic.  Per visitor that's a nearly 10x rate over web-based visitors.

Facebook's iPhone application accounts for approx 25% of monthly visits but generates 40% more traffic than web users.  If m.facebook.com and other mobile access points are factored in the volume of mobile usage is even more significant.

As global mobile/web availability increases - particularly in the BRIC nations, where mobile usage has leapfrogged traditional voice/web - advertisers and application designers will have to adapt to a highly filtered, localized, utility-driven digital world.

To help stay ahead of this transition, pay close attention to emerging trends in the mobile space, and experiment on how to optimize marketing and advertising messages using Rich Media on Mobile,  HTML5, Geolocation, Mobile Search  and Sensor integration.

Amazing Pictures From the ISS Via Twitter

The Science of Computational Advertising

Yahoo! Chief Scientists overview the science of Computational Advertising to Stanford's Management of Science & Engineering department.

The series of lectures were made public by Stanford and is surprisingly cogent and approachable for those unfamiliar with predictive statistics or interested in the mechanics of digital advertising.

  

What is Computational Advertising?

www.stanford.edu/class/msande239/lectures/lecture-01.pdf

  

Bidding and Price Mechanics for Ad Networks

(Use of Nash's famous Equilibrium Theory - Not the Christian Bale Movie) 

www.stanford.edu/class/msande239/lectures/lecture-02.pdf

Paid Search Placement Mechanics

How do they know which ad to put above another in search ads? www.stanford.edu/class/msande239/lectures/lecture-03.pdf

Sponsered Search - Part I 

www.stanford.edu/class/msande239/lectures/lecture-04.pdf

Sponsored Search - Part II 

www.stanford.edu/class/msande239/lectures/lecture-05.pdf

What Happens After The Click

www.stanford.edu/class/msande239/lectures/lecture-06.pdf

Page Ranking Method Comparison

www.stanford.edu/class/msande239/lectures/guest-lecture-ag.pdf

Targeting And Display Ads

www.stanford.edu/class/msande239/lectures/lecture-08.pdf