Curated for content, computing, and digital experience professionals

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Gilbane Advisor 11-4-16 – mobile / desktop evolution, enterprise software, attribution

In the spirit of right-tool-for-the-job, our first two articles relate to the evolution of mobile and desktop platforms. There is a lot of, mostly rational, exuberance around the speed with which smartphones are taking over the world. But that is only possible because they are not limited to content in native apps and walled gardens. According to StatCounter, mobile is now responsible for more web page views than desktops. Its share will continue to grow because that is where most of the content will be. This is a metric that has been under-appreciated because of too much attention on usage time — access to all content is surely more valuable than limited content chosen by someone else, even if it is more engaging.

At some point we won’t need both desktops and mobile devices, but in the meantime they each have jobs they are much better at and will be the preferred tool for. Our second article looks at this in terms input devices, the new Macs, and Apple’s strategy.

Mobile leads in page views

… this doesn’t necessarily mean … that people are using their mobile devices more than their computers, it does for certain mean people are viewing more individual webpages on mobile browsers than they are on desktop versions. Read More

mobile / desktop evolution

Wherefore art thou Macintosh?

Horace Dediu explains how the new MacBooks fit into the mobile / desktop evolution and Apple’s strategy around it.

It cannot take on the role of being the future. That belongs to the touch screen devices. It will not morph into a touch device any more than a teen’s parent will become cool by putting on skinny jeans. What it will do is become better at what it is hired to do. … The key to the Mac therefore becomes that which the iPad/iPhone isn’t: an indirect input device. The keyboard and mouse/trackpad are what define the Mac. Read More

Enterprise Software: Death and Transfiguration – What’s The Future?

Once upon a time — and it was a time that lasted some thirty years — there was no better place for VCs to invest in the broad world of tech than enterprise software. This is no longer true, and the enterprise is missing out as a result. What’s an entrepreneur or VC to do? Read More

WeChat’s Next Step Toward a SuperApp

If you haven’t heard of Google “instant apps” you should look into it even though many think that they are a ways off. One reason is that WeChat is working on something similar for their 800 million users.

WeChat’s pitch to software developers is that instead of having to build one version of their app for Android phones and another for the 20% of Chinese who use iPhones, they can just build on WeChat to serve both sets of customers. And the use case will get strengthened as more users find it natural to stay within WeChat to open the easier-to-build mini-apps. That’s an especially attractive proposition as Chinese users are loading fewer and fewer apps. Read More

Analytics CEO makes a passionate case against marketing attribution

Sergio Maldonado has a guest post on Scott Brinkler’s blog and he is looking for debaters.

It all started with a beautiful idea. Cross-channel attribution (or “multi-touch attribution”) became a popular concept at the time when web analytics had just completed its journey from IT to the marketing department (circa 2008). Read More

Gilbane Digital Content Conference

Main conference: November 29 – 30 ● Workshops: December 1, 2016
Fairmont Copley Plaza, Boston

Register today!
and use code F16G for an extra discount

Also…

Soon, Google to divide index, giving mobile users better & fresher content than desktop.  Hmm… “better and fresher” but less content? via Search Engine Land

How the Web Became Unreadable Yes, and continued variability of displays will exacerbate. via Backchannel

“…an update to adjust to the ‘smartphone revolution'”… Google has quietly dropped ban on personally identifiable web tracking via ProPublica

Contrast with WeChat approach… Behind Facebook’s Messenger Missteps via The Information

Take that new Google translation tool! Microsoft researchers announce human parity in conversational speech recognition via Microsoft

 

The Gilbane Advisor curates content for our community of content, computing, and digital experience professionals. Subscribe to our newsletter, or our feed.

Building the analytics you need to monetize your innovation

Join us at the Gilbane Conference in Boston December 1-3 and learn how your peers are building superior digital experiences for customers and employees. If you haven’t reviewed your analytics for effectiveness in a while, or are wondering if you are collecting the right metrics to support your business objectives, this in-depth workshop is for you.

Great Ideas Need the Right Metrics to Flourish: Building the Analytics You Need to Monetize your Innovation

For digital innovators, Analytics and data-driven decision-making have become key determinants of success. “If you can measure it, you can manage it.” The right metrics often make the difference between monetizing innovation and under-performance.

Yet identifying these “metrics that matter” isn’t easy—the right metrics vary widely based on your business model—nor is it easy to build the required capabilities and collecting the necessary data. Fortunately there is a way to make it easier, and this presentation will share a better way to tackle the challenge.

In this workshop, author and analytics veteran Jaime Fitzgerald will share his battle-tested method that addresses this challenge. During two decades working with data, Mr. Fitzgerald created a new method that makes it easier to define the metrics you really need to monetize your innovative ideas, business models, and initiatives. In addition to defining the “metrics that matter,” Mr. Fitzgerald’s methodology defines the analytic methods and data sources you need to generate these key performance indicators, and how they will be used to enhance key business decisions, essential processes, and business model evolution.

Instructor: Jaime Fitzgerald, Founder & Managing Partner, Fitzgerald Analytics
Tuesday, December, 1: 1:00 p.m. – 4:00 p.m. • Fairmont Copley Plaza Hotel, Boston

This workshop is included in the ConferencePlus package. Save $200 on the ConferencePlus and Conference Only options. To get your Bluebill discount use priority code 200BB when registering online.

I would like my $200 registration discount – code 200BB

 

Gilbane pre-conference workshops announced

It’s only June but we’re already working hard on the 2015 conference program and want to share a bit of what you can look forward to.

We’ve got a great lineup of pre-conference workshops that will be held Tuesday, December 1, the day before the main conference, December 2 – 3.

Pre-conference workshops:

Developing a personalization strategy: one size doesn’t fit all
Instructor: John Berndt, CEO, The Berndt Group (TBG)

An anatomy of a digital audit
Instructor: Tim Bourgeois, Partner at East Coast Catalyst and Founder, ChiefDigitalOfficer.net

Insider’s guide to selecting the right WCM
Instructor: Tony Byrne, Founder, Real Story Group

Foundations for best-fit WCM service provider selections
Instructor: Cathy McKnight, Partner and Principal Analyst, Digital Clarity Group

Great ideas need the right metrics to flourish – building the analytics you need to monetize your innovation
Instructor: Jaime Fitzgerald, Founder and Managing Partner, Fitzgerald Analytics Inc.

Digital is global in nature, not by default: leveraging digital globalization to increase global customer experience
Instructor: Bruno Herrmann , Director of Globalization, Nielsen

Find out more and get detailed descriptions for these workshops.

Hotel now accepting reservations

The Fairmont Copley Plaza is the official conference hotel for Gilbane Conference 2015. Discounted room rates have been arranged for attendees and are available starting today. Find out more.

What big companies are doing with big data today

The Economist has been running a conference largely focused on Big Data for three years. I wasn’t able to make it this year, but the program looks like it is still an excellent event for executives to get their hands around the strategic value, and the reality, of existing big data initiatives from a trusted source. Last month’s conference, The Economist’s Ideas Economy: Information Forum 2013, included an 11 minute introduction to a panel on what large companies are currently doing and on how boardrooms are looking at big data today that is almost perfect for circulating to c-suites. The presenter is Paul Barth, managing partner at NewVantage Partners.

Thanks to Gil Press for pointing to the video on his What’s The Big Data? blog.

Big data and decision making: data vs intuition

There is certainly hype around ‘big data‘, as there always has been and always will be about many important technologies or ideas – remember the hype around the Web? Just as annoying is the backlash anti big data hype, typically built around straw men – does anyone actually claim that big data is useful without analysis?

One unfair characterization both sides indulge in involves the role of intuition, which is viewed either as the last lifeline for data-challenged and threatened managers, or as the way real men and women make the smart difficult decisions in the face of too many conflicting statistics.

Robert Carraway, a professor who teaches Quantitative Analysis at UVA’s Darden School of Business, has good news for both sides. In a post on big data and decision making in Forbes, “Meeting the Big Data challenge: Don’t be objective” he argues “that the existence of Big Data and more rational, analytical tools and frameworks places more—not less—weight on the role of intuition.”

Carraway first mentions Corporate Executive Board’s findings that of over 5000 managers 19% were “Visceral decision makers” relying “almost exclusively on intuition.” The rest were more or less evenly split between “Unquestioning empiricists” who rely entirely on analysis and “Informed skeptics … who find some way to balance intuition and analysis.” The assumption of the test and of Carraway was that Informed skeptics had the right approach.

A different study, “Frames, Biases, and Rational Decision-Making in the Human Brain“, at the Institute of Neurology at University College London tested for correlations between the influence of ‘framing bias’ (what it sounds like – making different decisions for the same problem depending on how the problem was framed) and degree of rationality. The study measured which areas of the brain were active using an fMRI and found the activity of the the most rational (least influenced by framing) took place in the prefrontal cortex, where reasoning takes place; the least rational (most influenced by framing / intuition) had activity in the amygdala (home of emotions); and the activity of those in between (“somewhat susceptible to framing, but at times able to overcome it”) in the cingulate cortex, where conflicts are addressed.

It is this last correlation that is suggestive to Carraway, and what he maps to being an informed skeptic. In real life, we have to make decisions without all or enough data, and a predilection for relying on either data or intuition can easily lead us astray. Our decision making benefits by our brain seeing a conflict that calls for skeptical analysis between what the data says and what our intuition is telling us. In other words, intuition is a partner in the dance, and the implication is that it is always in the dance — always has a role.

Big data and all the associated analytical tools provide more ways to find bogus patterns that fit what we are looking for. This makes it easier to find false support for a preconception. So just looking at the facts – just being “objective” – just being “rational” – is less likely to be sufficient.

The way to improve the odds is to introduce conflict – call in the cingulate cortex cavalry. If you have a pre-concieved belief, acknowledge it and and try and refute, rather than support it, with the data.

“the choice of how to analyze Big Data should almost never start with “pick a tool, and use it”. It should invariably start with: pick a belief, and then challenge it. The choice of appropriate analytical tool (and data) should be driven by: what could change my mind?…”

Of course conflict isn’t only possible between intuition and data. It can also be created between different data patterns. Carraway has an earlier related post, “Big Data, Small Bets“, that looks at creating multiple small experiments for big data sets designed to minimize identifying patterns that are either random or not significant.

Thanks to Professor Carraway for elevating the discussion. Read his full post.

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