Babelfish Articles Jan-Sep 2016 12-09-16 final

Babelfish Articles July 2015-Dec 2015 10-12-15
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Articles #14
Jan- Sep 2016
Brian Crotty
Babelfish.Brazil@gmail.com

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Summary
60 teenagers reveal what they think is cool — and what isn't — in 2016..........7
AI will dictate the future of strategy ........................................24
The Missing Link of Artificial Intelligence ...................................25
Selfies will soon be passwords for mobile banking ............................. 27
Mastering Data and Analytics: 'Table Stakes' for Digital Business..............28
Setting effective marketing metrics ...........................................34
Ashley Friedlein’s 10 digital marketing & ecommerce trends for 2016............34
How neuroscience can spark creativity .........................................45
How neuroscience can make segmentation and understanding purchase behaviour
easier .......................................................................49
Digital isn’t merely an add-on; it’s a way to think differently about business
models, customer journeys, and organizational agility. ........................ 52
Mums relate to diverse identities .............................................57
Unilever’s Sarah Mansfield: 'More data is at the heart of everything'..........58
How Agencies Are Putting Themselves Out Of Business And What We Should Do About
It ...........................................................................59
Just What Is the 'Agency of the Future' and Has Omnicom Built It?..............61
Ad-Tech in 2020 (part 1) #agencypublisher .....................................66
Ad-Tech in 2020 (part 2)......................................................72
Ad-Tech in 2020 (part 3, final) ...............................................76
The Smartphone Is Eating the Television, Nielsen Admits .......................81
Desktop joins print in ad decline .............................................83
Check Out the 26 Boldly Inventive Campaigns That Won This Year's Project Isaac
Awards .......................................................................84
The collaboration curse.......................................................99
Five ways Artificial Intelligence can help marketers enhance the customer
experience .................................................................. 101
R3 report shows growth and performance of ad tech ............................ 104
26 Disruptive Tech Trends for the Rest of the Decade ......................... 107
Yuval Noah Harari on big data, Google and the end of free will................ 112
Digital Innovation is Kind of a Big Deal Right Now ........................... 117
The creative CIO agenda: Six big bets for digital transformation.............. 120
How to Use Neuroscience to Improve Your Content Marketing Strategy............ 122
Neuroscience offers targeting insights ....................................... 123
3 Trends That Will Completely Change the World by 2020 ....................... 123
WordsEye Transforms Thoughts into 3D Images .................................. 127
Os fatos de Mídia de 2015 (Brasil) ........................................... 128
Why Companies Can’t Turn Customer Insights into Growth ....................... 133
Survey Says: Yes, U.S. Consumers Will Buy Cars From Apple And Google.......... 139
Unilever's 'macro' and 'micro' marketing ..................................... 141
A Voice Drives The Future Of Travel .......................................... 141

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Apple Lags Behind Google and Facebook on AI .................................. 143
Search Giant Says What Took Hours to Complete Now Takes Minutes............... 144
Agência cria primeiro post de realidade aumentada do Facebook................. 146
A complete guide to emoji marketing .......................................... 147
Mobile Myth-Busting: 'Feed' vs. 'Read' ....................................... 158
The Productivity Paradox..................................................... 160
Extracting Insights from Vast Stores of Data ................................. 162
Strategists miss the big picture ............................................. 163
How Advanced Analytics Are Shaking Up TV Ad Buying ........................... 164
Foxtel announces new no-contract and equipment-free packages to rival Netflix . 165
The importance of emotional connection ....................................... 166
An Emotional Connection Matters More than Customer Satisfaction............... 167
Highway To The Danish Zone – 9 Startups From Denmark To Watch................. 169
Your Guide To Generation Z: The Frugal, Brand-Wary, Determined Anti-Millennials
............................................................................ 173
Is Amazon's 30-Hour Workweek Program Good For Workers? ....................... 178
That's It, Creatives! Programmatic Is Taking Your Job ........................ 180
Amazon’s Fire TV Gets Expanded Universal Search, Better Voice Control......... 180
Innovation Is Only Skin Deep................................................. 182
Removing Barriers from Digital ROI Measurement ............................... 183
Most active #IoT #investors in the last 5 years .............................. 184
Programmatic TV Ad Buying Will Never Work .................................... 184
Internet Of Things Summit: Sensors, Switches Rule In The Smart Home Of The Future
............................................................................ 188
FTC Urged To Investigate Celebrity Endorsements On Instagram.................. 189
IBM's global head of Watson IoT, Harriet Green, gave a keynote speech at IFA in
Berlin ...................................................................... 190
Beyond Siri, The Next-Generation AI Assistants Are Smarter Specialists........ 191
Big Data Lessons From Netflix ................................................ 193
JCDecaux Primed To Enhance Advertiser Offerings Via Data Republic Partnership . 196
From Microsoft to Self-Driving Cars, Invention Springs From Data.............. 196
Segmenting and refining images with SharpMask ................................ 198
Facebook's mobile update embraces vertical video ............................. 204
Data fuels change at American Apparel ........................................ 204
EEG-Based Measures versus Panel Ratings: Predicting Social-Media Based Behavioral
Responses to Super Bowl Ads.................................................. 205
Neuromarketing updates Super Bowl ad metrics ................................. 216
Zuckerberg Accused Of Abusing Power As “World’s Most Powerful Editor”......... 217
The Final Existential Threat To Adland: Remuneration ......................... 222
Study: More Aussies Now Have SVOD Than Foxtel ................................ 224
What’s Next for Entertainment: Three Predictions From Google Australia’s Head of
Marketing ................................................................... 226

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The future of strategy: Account planning's legacy ............................ 228
Brand entrepreneurship is the future of strategy ............................. 230
Strategy and technology: Why planners will move from a subjective approach to a
more empirical, objective role ............................................... 238
Big Data é essencial na estratégia corporativa ............................... 242
Netflix reduces ad viewing by kids ........................................... 243
The AI Revolution and Implications for Brands ................................ 243
Coles to cut product range by 15 per cent .................................... 245
Contactless cards reach new record ........................................... 246
Facebook is building its own Steam-style desktop gaming platform with Unity ... 247
Google Ramps Up VR Push Ahead of Hybrid Store, Software Service Daydream's Debut
............................................................................ 250
Snapchat wants more TV-like content for Discover ............................. 251
How agencies are using search to take advantage of moments that matter........ 252
True breakthroughs come from product insights ................................ 254
5 Strategies to Increase Sales’ Adoption of Your Content #1 .................. 255
5 Strategies to Increase Sales’ Adoption of Your Content #2 .................. 257
Absolut explores VR monetisation ............................................. 259
Dopamine fuels social sharing ................................................ 260
Segmentation a priority for AT&T ............................................. 261
Relevancy beats personalisation .............................................. 261
Starcom's Paul Wilson on scaling innovation .................................. 262
Social media celebs warned over ads .......................................... 264
Premium context lifts brand metrics .......................................... 264
Why P&G Decided Facebook Ad Targeting Often Isn't Worth the Money - There's Still
Something to Be Said for Mass Reach .......................................... 265
Clients value Cannes and find it inspirational ............................... 266
The enterprise technologies to watch in 2016 ................................. 267
Confessions Of A Cannes Media Lions Judge: Part Deux ......................... 273
How Netflix develops its original content .................................... 274
The Really Guilty Party In The ANA Debate? Advertisers! ...................... 278
Five conversations your boss doesn’t want to have with you ................... 279
Talent just wants to have fun ................................................ 283
NEC develops biometrics technology that uses sound to distinguish individually
unique ear cavity shape...................................................... 285
A Brief History Of Twitter's 140-Character Limit ............................. 287
Is An LTE-Connected Apple Watch Coming This Fall? I'm Betting Yes............. 289
The Tyranny of Choice, As Seen On TV ......................................... 291
Time Pressure: Behavioral Science Considerations for Mobile Marketing......... 292
The Car-Buying Process: One Consumer's 900+ Digital Interactions.............. 294
Marketers, Take Note of These New Google Products ............................ 295

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Instagram’s analytics will offer audience demographics, post impressions, reach &
more ........................................................................ 298
30 things you should remove from your résumé immediately ..................... 303
Data-driven storytelling: the intersection of numbers and narrative........... 317
Federal Government says ‘open data’ can power apps to make life easier in major
cities ...................................................................... 320
Why mobile is critical to Coca-Cola: talking QR codes and SmartLabels with Coca-
Cola’s Tom Daly.............................................................. 322
The Digital Download: New algorithms, ad formats and appointments............. 326
For virtual reality creators, motion sickness a real issue ................... 327
What Every Tech-Savvy Marketer Should Know About the Future of Programmatic
Advertising ................................................................. 329
How to tackle the awkward but crucial salary expectation question in job
interviews .................................................................. 330
PTV Standardization Progresses Amid More Big-Player Announcements............. 333
Media-Agency Kickbacks. Yes, They're Real. ................................... 335
Amazon Unveils Two New Voice-Control Devices: Amazon Tap And Echo Dot......... 337
The Rise of Programmatic Creates a Breeding Ground for Fuzzy Pricing.......... 339
Five Ways Agencies Goose Their Media Business ................................ 340
Marketers Growing In-House Media Buying Capabilities Amid Transparency Concerns
............................................................................ 341
The Laziness In The Internet Of Things ....................................... 341
Google Is Doing Away With Ads Along the Right Rail for Desktop................ 342
An Alliance of Content, Distribution and Consumers ........................... 343
TV Networks Recast the Role of Commercials ................................... 345
2015 Television Upfronts: TV Networks Borrow Page From Digital Rivals to Attract
Advertisers ................................................................. 345
Programmatic: It’s More Than Technology ...................................... 348
IPG Media Lab’s Kara Manatt: What Drives Content? ............................ 349
A Harvard psychologist says people judge you based on 2 criteria when they first
meet you .................................................................... 351
Gartner Says Power Shift in Business Intelligence and Analytics Will Fuel
Disruption .................................................................. 352
CMOs Want To Know: Which Naked Disney Princess Are You? ...................... 354
Agencies are using emotional reactions to gauge ad effectiveness.............. 355
Google wants you to use its delivery service to buy your fruits and veggies ... 356
Citi Innovation Lab Spotlight: Singapore ..................................... 357
OMD tops the list again in Gunn Report for Media 2015 ........................ 358
Philippe Krakowsky Takes on Mediabrands Chairman Role ........................ 362
A morte dos shoppings, o fim do Facebook e o futuro criado pelos Millennials .. 363
Why IBM Is Buying a Digital Marketing Agency ................................. 368
Hulu's one big advantage over Netflix is on the chopping block................ 370

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Ad effectiveness: It's time to move on from obsessing over CPMs and focus on the
human equation............................................................... 371
Mobile Predictions for 2016.................................................. 372
A Former CMO Gives Tips on How to Create a Better Brief ...................... 375
Ten ways your job is killing you ............................................. 376
Best Practices: How to Keep Users Engaged With Your Mobile App................ 379
How a side gig can be your key to career satisfaction ........................ 380
Could this one-passenger autonomous drone change transportation forever?...... 382
What's Important When Buying Programmatically? ............................... 385
A New Brand-Agency Model Emerges In The Age of Programmatic .................. 387
OMG P&G! .................................................................... 388
P&G's Pritchard on What Drove the Big Media Decision ......................... 389
Programmatic TV: DSPs TubeMogul, Videology, and The Trade Desk top Forrester
report ...................................................................... 390
Data savings from ad blockers might not translate into actual savings......... 392
TV Programmatic -- A Big Game of Hot Potato .................................. 394
How Mondelēz plans to increase its e-commerce sales tenfold by 2020........... 397
P&G Bypasses Mediacom to Kickstart Move Towards Addressable TV in Germany..... 398
What Video Ad Length Is Best on Facebook? .................................... 399
Top 3 Content Marketing Trends in Beauty ..................................... 400
Other Stuff ................................................................. 403

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60 teenagers reveal what they think is cool —
and what isn't — in 2016
Maya Kosoff Jan. 28, 2016, 1:25 PM
oss Gilmore / AP Images
Too often when writing about what teenagers like, we neglect to talk to the most important group of
all: teens. So we decided to put together a State of the Union on the American teenager. To learn
what American teenagers in 2016 really like, and what they don't, we polled about 60 of them from
across the US. We spoke with teens ages 13 to 19, in middle school, high school, and college.
We asked them about their digital lives and habits, the apps they use and the games they play, pop
culture, and politics. Their answers offer a glimpse into what it's like being a teenager in 2016. We've
drawn out the highlights below, along with some data from other sources, so keep scrolling for our
guide to teenagers in 2016.
View As: One Page Slides
Who did we talk to?
Flickr / chiesADIbeinasco
For our survey on American teenagers, we talked to a group of about 60 teenagers from across the
US, of various socioeconomic classes, grades, and ages. We didn't want to focus on one particular
geographic area, so we talked to teenagers from across the country, including California, Colorado,
Mississippi, and Pennsylvania.
Every teen we spoke with owned a smartphone, and most owned or regularly used a variety of
devices, like gaming consoles, tablets, and desktop computers.

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Teens get their first smartphone when they're 11.
Cole Bennetts/Getty Images
On average, the teens we spoke with received smartphones from their parents when they were11
years old. At their youngest, they received phones when they were 8; at the other end, one teen's
parents made her wait until she was 16 before she got a phone.
Teens are shy to talk about how much time they spend on their phones, but it's a lot.
Flickr/Daniel Oines
We got lots of "too many" and "I'm embarrassed to say" responses, but the numbers we were able to
get suggested teens spend about six hours a day on their phones. (This is both in and out of school.)
And they're spending lots of time in front of other screens, too.

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Peter Macdiarmid/Getty Images
Besides owning smartphones, most teens we talked to spent time in front of television sets and
gaming consoles (PlayStation 4 and Wii were popular answers) as well. Some also used desktop
computers.
On average, they said they spent 11 hours in front of screens every day — answers ranged from two
hours to 18 hours, which sounds as if it would be literally every waking moment (and maybe it is).
Teens aren't only spending a ton of time online — they're shopping online too.
BI Intelligence
Clothing has been relatively immune to the rise of e-commerce because people still like to try things
on before buying.
But when it comes to teenage shoppers, the option of being able to try on clothing before buying is
becoming less important, according to a survey conducted by Piper Jaffray in 2015.
Only 61% of US teens say they prefer to shop for clothing online from retailers that also operate their
own brick-and-mortar stores. That's a significant drop from the 81% of teens last spring who said they
preferred to shop at omnichannel fashion (or cross-channel) retailers.
What are teens' favorite apps? Here are a few of the most popular answers:

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Getty Images/Clemens Bilan
The most popular by a landslide: Snapchat.
Kevork Djansezian / Getty Images
It's no surprise that teenagers love Snapchat. Here's what they had to say about it:
• "It's how I communicate with most of my friends and it's fun." — 15-year-old
• "Snapchat because it's pretty much just texting, but with pictures of my beautiful face " — 16-
year-old
• "Snapchat, because it is fun to send your friends what you're doing, and where you are in a
fast and easy way. I also like being able to make stories, for all of my friends to see, and I also enjoy
seeing stories of my friends on it and see what they're up to." — 17-year-old
Spotify was almost universally heralded as the best music app, and it was also listed as a favorite app
by a lot of respondents.

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Nick Pickles/Getty
Teenagers almost universally named Spotify as their preferred music-streaming service — and some
teenagers said it was the best app on their phone overall:
• "I use it to share music, to see what my friends are listening to, and to find new music." — 14-
year-old
Instagram was another favorite.
Denys Prykhodov/Shuttershock
Instagram is a standby favorite of teens, who swear by its filters and direct-message feature. Here's
what they said:
• "I use Instagram to message my friends funny pictures I see on Instagram." — 15-year-old
• "Snapchat and Instagram, I love sharing photos all of the things I do and places I go. I also like
seeing what others are up to." — 15-year-old
The dark horse: Twitter.

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Anthony Quintano/Flickr
You might not expect Twitter to be among teens' favorite apps. After all, the company is having a hard
time attracting new users. But a lot of teenagers we talked to really liked the platform. Here what they
had to say:
• "Twitter because I can update everyone all the time quickly and it's not annoying like
Facebook." — 17-year-old
• Twitter because "you can voice your opinion on anything you want to and you can somewhat
interact with celebrities." — 18-year-old
• "My favorite app is Twitter because I am the kind of person who needs to get out my thoughts,
and Twitter may be like shouting into the void but at least I am heard and often validated by my
peers." — 19-year-old
Absent from the list: Facebook.
REUTERS/Dado Ruvic
The teens we talked to said they and their friends were still using Facebook — but it wasn't their
favorite app. Here's why:
• "I use Facebook, but I feel like I can't be myself on it because my parents and my friends'
parents are my Facebook friends." — 16-year-old
• "It's mostly outdated." — 14-year-old
• "Facebook is good for group events and things but it's definitely not my favorite app." — 15-
year-old
We also asked which apps were just flat-out uncool.

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Bloomberg / Getty Images
• Google+. "I don't even really know a time where Google+ was a thing." — 16-year-old
• Whisper. "People just don't use it anymore." — 17-year-old
• Vine. "I watch Vine videos, but me and my friends don't have accounts or make our own
videos, same with YouTube." — 16-year-old
This pretty much lines up with what teens across the board are saying.
BI Intelligence

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Instagram leads as the "most important" social network among US teens, according to the 2015
edition of Piper Jaffray's teen survey, as reported by BI Intelligence.
Most of the teens we talked to wouldn't acknowledge having fake Instagram ("finsta") accounts.
REUTERS/Brian Snyder
For the uninitiated, a finsta is a portmanteau of the words "fake" and "Instagram." You use it for
posting embarrassing or less aesthetically pleasing pictures you wouldn't want to share with all of
your friends.
Eighty percent of the teens we talked to had no idea what a finsta was, and 92% said they didn't have
one.
"I did have a finsta with a friend, but we don't use it anymore because it got too confusing to know
which account you were on, to make sure we were posting on the right one, and not posting on the
wrong one by accident," one 16-year-old told us.
"A lot of my friends still have them and use them. A finsta is a fake Instagram account people use to
post funny pictures they wouldn't normally post for everyone to see. Usually on a finsta you only have
your closer friends follow, so you can post embarrassing pictures of yourself without having everyone
you've ever talked to see them."
Facebook may be dead to teens, but a surprising number of them are texting their friends through
Facebook Messenger.
Facebook

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The most common form of messaging among teenagers in our survey was iMessage or SMS
messaging (100% of the teens we talked to used one or both of those). But Facebook Messenger
was mentioned almost as frequently — 80% of teenagers we spoke with said they used Facebook
Messenger as a primary or secondary form of communicating with friends. Less popular were
WhatsApp, Kik, and Snapchat text.
Overwhelmingly, three phones are most popular with the teenagers we talked to: the iPhone 5S, the
iPhone 6, and the Samsung Galaxy S5.
Flickr/Morid1n
Eighty percent of the teenagers we talked to had one of these three phones.
Teenagers are watching both cable and streaming services like Netflix — but there's one clear
winner.
Shutterstock
And that's Netflix. Hulu and Amazon were also listed by a lot of the teens we spoke with, but Netflix
had the lion's share.
Here's why, in the words of a couple of the teenagers we spoke with:
• "My family has cable and Netflix and Hulu, but for me all I watch is Netflix. I know my parents
will watch the news and sometimes a show on cable, but they also mostly use Netflix or Hulu to watch
shows and movies. I use Netflix more then Hulu because there aren't commercials on Netflix. I only
use Hulu when I miss an episode of a show because it will be on there fast." — 17-year-old
• "Netflix is life." — 16-year-old
Here's what teens are watching on TV (it's mostly Netflix and Netflix-like services).

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BI Intelligence
Over one-half of US children and teenagers ages 8 to 18 in a PwC survey preferred streaming
television to all other types of media.
We asked teens to identify the coolest app, website, or thing on the internet that adults probably didn't
know about.
iStock
We got a fair number of responses from teens who thought Twitter, Tumblr, and Snapchat were cool
(and they are!) and that adults didn't know about them (but they do!).
But we found a few responses genuinely surprising.
After School.

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iTunes
Several teens brought this app to our attention. We first wrote about After School, a social network
created specifically for high-school students, when it launched and started gaining traction in late
2014.
If you're nervous thinking about the kinds of stuff teenagers would post anonymously on a social
network, you're not alone. Millions of teens are using it to post their "deepest anxieties, secret
crushes, vulgar assessments of their classmates, and even violent threats," according to The
Washington Post.
Musical.ly.
Screenshot
You've probably never heard of Musical.ly, but it has already cracked the top 20 in Apple's App Store.
The app has quietly grown to its popular status without any press. Musical.ly lets you make music
videos of yourself or of other people. It may not seem like a particularly compelling value proposition,
but 10 of the 60 teens we spoke with listed Musical.ly as the app they were most excited about and
doubted adults would know about.
Color Therapy.

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Screenshot
Remember when you were a kid and you colored in coloring books? Color Therapy is a stress-
relieving, digital coloring book for adults, and the teens we talked to swore by it.
Wishbone.
Wishbone
Launched by the Los Angeles venture-capital firm Science's mobile studio, Wishbone shows you two
options and lets you vote on which one you like more — a spin on the popular "Would you rather?"
hypothetical question.
Wishbone became somewhat of a viral teen phenomenon, and as of September, just months after it
launched, Wishbone had been downloaded 3 million times.
"Neko Atsume."

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Screenshot
You have probably never heard of the Japanese game "Neko Atsume," but numerous teens we
talked to were obsessed with it. The game's name literally translates to "cat collecting," and that's
exactly what you do in the adorable game.
"Color Switch."
Screenshot/YouTube
Speaking of games, a bunch of teens also mentioned "Color Switch." In this game, you must follow
each color pattern you're shown on each obstacle to progress.
We asked teens to name the coolest celebrities.
Neilson Barnard/Getty

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Some of the more popular names included Taylor Swift, Justin Timberlake, Jimmy Fallon, 5 Seconds
of Summer, Kanye West, DJ Khaled, Justin Bieber, Kendall Jenner, Ruby Rose, One Direction,
"Hamilton" creator and star Lin-Manuel Miranda, Drake, and Nicki Minaj.
Yes, the star of the Broadway musical "Hamilton" was named in the same breath as Drake and One
Direction. That's him in this picture.
But teens consider YouTube and Vine stars celebrities too.
Kevin Mazur/Fox/WireImage
And most we talked to named a bunch they liked. Interestingly, a lot of the teens we spoke with — the
majority, 75% — told us they didn't have or use YouTube or Vine accounts, but they use both
services voyeuristically just to watch the videos.
There tends to be a lot of overlap between YouTube and Vine stars. Favorites include: Brendon Urie,
Shawn Mendes, Connor Franta, Troye Sivan, Tyler Oakley, Miranda Sings, Shane Dawson, Logan
Paul, Lele Pons, Josh Peck, Jenna Marbles, Manny MUA, Ethan and Grayson Dolan, Alx James,
Grace Helbig, Mamrie Hart, Hannah Hart, and Rosanna Pansino.
There was just one media company teens said they were obsessed with.
Lara O'Reilly/Business Insider
We didn't flat-out ask what media teens are consuming, but in their answers about their favorite
Viners and what they did online, 30% of teens we spoke with mentioned BuzzFeed, BuzzFeed Video,
Tasty (the BuzzFeed food video Facebook page), and BuzzFeed's quizzes.
But as far as slang goes, "Anything is very uncool as soon as BuzzFeed gets it."

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Flickr/jewdini
That's what one teen told us when we asked about what slang teens were using. The teen we were
talking to was specifically referring words like "bae" (the term of endearment meaning "before anyone
else") and phrases like "on fleek."
"Nobody has a better bull---t detector than a teenager does," Taylor Trudon, an editor at MTV News
and a bona fide teen expert, told us. Trudon is launching a new platform for MTV News called Voices,
a for-teens-and-by-teens community, so she knows a thing or two about teenagers. "They can tell
when you're not being authentic."
So what slang *is* cool, by teens' standards?
Summer Skyes 11 / Flickr
Well, here's what they told us. Most of these are no-brainers if you have kids or even just sit around
on the internet for any length of time.
• "I use YASSSSSSSS a lot when I get really excited and don't really realize it. I also likeslay,
even though I know that's kind of stupid."
• "Regularly use: hype (as in 'I'm so hype for this'), mad, dope, low key/high key, lit. Uncool: on
fleek, bae, fire, etc."
• "Goals. You might look at a beautiful celebrity or your favorite couple and say they are goals."
• "Me and my friends use Gucci and squad and #goals a lot but in a joking manner. The ones
that are uncool are on fleek and holla @ me."
• "I regularly say v instead of very (ex: 'She's v aesthetic') and 'it's lit.'"
• "'Throw shade/spill tea' — talk negatively about someone or gossip. 'Read' — make a
judgment."
• "I normally use flames or lit to sound cool. We need to stop saying bae and on fleek."

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Then, just for fun, we asked a couple of other questions. First up: What do you think about the
Kardashians?
Isaac Brekken/Getty Images
Before you abandon all hope for humanity, read their rather rational responses.
• "I don't really pay attention to them because there's always something negative going on with
them. Except for Kendall — she stays out of it and I like her for that, even though she's not a
Kardashian."
• "I dislike how prominent they are."
• "I dislike the Kardashians. They are currently taking over our generation."
• "I think they are a bunch of spoiled rich people who are cocky and don't deserve much, but
they are face and body goals."
• "I don't know much about them, but I feel like society shames them for all of the wrong
reasons."
Next: Whom would you vote for in the 2016 election, if you could pick any candidate?
REUTERS/Mark Kauzlarich
Sen. Bernie Sanders of Vermont won by a landslide (55% of respondents said they'd vote for him).
Also popular: Donald Trump, Hillary Clinton, Ted Cruz.
Finally, we asked teens to send us their homescreens so we could take a look at what their phones
looked like. Scroll through to see what apps are on teens' phones.

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Page 24
AI will dictate the future of strategy
5 September 2016
LONDON: Technological developments will dramatically change the role of agency strategists as they
move from a free-associating, subjective approach to a more empirical, objective and advisory role, a
leading industry figure has said.
Writing in the current issue of Admap, Mark Holden, Worldwide Strategy and Planning Director at
PHD, outlines the future direction of strategythat will start to emerge once attribution modelling and
demand-side platforms come together.
Currently, users log in to the former to pull out insights and then log in to the latter to execute their
strategies.
"When they are finally joined up, this will create the first closed system our industry has ever
experienced," Holden says, "with this the basis into which we can drop a reinforcement learning
algorithm."
The point about reinforcement learning – an emerging area of artificial intelligence – is that it requires
a closed system, where action and outcome are inextricably linked, in order to further develop.
Within five years, Holden expects that such algorithms will become self-optimising systems, capable
of making hundreds of thousands of incremental improvements every second.
And when other forms of advanced marketing technology are plugged into this closed system,
marketing activity can become self-implementing as well, creating what will feel like a marketing
central nervous system.

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"We will be witnessing media strategies, creativity and CRM initiatives being created before our very
eyes: strategies and ads will be an epiphenomenon of the system – as in, they will emerge from it,"
says Holden.
Strategists should not necessarily be alarmed by this prospect, however, which simply marks the
latest stage in the evolution of the discipline, as they become, in Holden's metaphor, gardeners.
Just as a gardener designs the layout of the garden, plants it and tends it, so the strategist "will
design the marketing technology stack, plugging in/out new technologies as they develop, feeding in
new data sources gained through strategic second-party data deals, and so on".
These strategists will need to know about data and marketing technology, and its interoperability, as
much as, today, they know about media.
But not everything can be plugged into the central nervous system: brand-building activity, for
example, will still require human judgement, and strategists operating in this field will utilise another
area of artificial intelligence – deep learning – to inform their decisions.
"They will construct their recommendations with reference to meta-studies that have teased out law-
like relationships on how the physics of marketing actually works," says Holden.
So while future strategists will come in two different forms, both will be working in what Holden
expects will be a "more solid, empirical, tangible and business-centric discipline".
Data sourced from Admap
The Missing Link of Artificial Intelligence
We don’t know how to make software that learns without explicit instruction—but we need to if
dreams of humanlike AI are to come true.
by Tom Simonite February 18, 2016
In 2012 the world learned of a surprising research project inside Google’s secretive X lab. A giant
simulation of three million neurons learned to recognize cats and people in pictures, without human
help, just by looking at images taken from YouTube.
The people behind the project founded a new research group known as Google Brain inside the
company’s search division. They and researchers elsewhere soon proved to the world that artificial
neural networks, a decades-old invention, could understand images and speech with unprecedented
accuracy (see “Google Puts Its Virtual Brain to Work”). The success of deep learning, as the
technique is also known, prompted Google and others to invest heavily in artificial intelligence and
has even led some experts to claim we should prepare for software that’s smarter than humans (see
“What Will It Take to Build a Virtuous AI?”).
Yet Google’s cat detector was in some ways a dead end. The recent successes of deep learning are
built on software that needs human help to learn—something that limits how far artificial intelligence
can go.
Google’s experiment used an approach known as unsupervised learning, in which software is fed raw
data and must figure things out for itself without human help. But although it learned to recognize
cats, faces, and other objects, it wasn’t accurate enough to be useful. The boom in research into
deep learning and products built on it rests on supervised learning, where the software is provided
with data labeled by humans—for example, images tagged with the names of the objects they depict
(see “Teaching Machines to Understand Us”).

Page 26
That has proved incredibly effective for many problems, such as identifying objects in images, filtering
spam e-mail, and even suggesting short replies to your messages, a feature introduced by Google
last year. But unsupervised learning is probably needed if software is to keep getting better at
understanding the world, says Jeff Dean, who leads the Google Brain group today and also worked
on the cat detector project inside Google X.
“I’m pretty sure we need it,” says Dean. “Supervised learning works so well when you have the right
data set, but ultimately unsupervised learning is going to be a really important component in building
really intelligent systems—if you look at how humans learn, it’s almost entirely unsupervised.”
One example of that is the way we learn as infants, establishing the foundations of adult intelligence.
For example, we figure out that objects still exist while out of sight and fall if unsupported, and we
learn these things just by observing the world, without explicit instruction. That kind of common sense
is needed if robots are to navigate the world as well as animals do. It also underpins seemingly more
abstract tasks, such as understanding language.
Figuring out how software can do what comes so easily to human babies is crucial if grander
ambitions for artificial intelligence are to be fulfilled, says Yann LeCun, director of Facebook’s Artificial
Intelligence Research Group. “We all know that unsupervised learning is the ultimate answer,” he
says. “Solving unsupervised learning will take us to the next level.”
Although they don’t have that ultimate answer yet, researchers at companies such as Facebook and
Google, and in academia, are experimenting with limited forms of unsupervised learning.
One strand of research aims to create artificial neural networks that ingest video and images and then
generate new imagery using the knowledge they have gained about the world—indicating that they
have formed some internal representation of how it works. Making accurate predictions about the
world is an important fundamental feature of human intelligence.
The "optimal" human face, according to a network of three million simulated neurons that Google fed
images from YouTube.
Facebook’s researchers have made software called EyeScream that can generate recognizable
images given prompts such as “church” or “airplane,” and they are working on creating software that
predicts what will happen in a video. Researchers at Google’s DeepMind subsidiary have made
software that looks at a photo with some parts blacked out and tries to fill them in with realistic
imagery.

Page 27
DeepMind is also testing an alternative to fully unsupervised learning called reinforcement learning, in
which software is trained by receiving automatic feedback on its performance—for example, from the
scoring system of a computer game (see “Google’s Intelligence Designer”). And researchers not
using deep learning have demonstrated software that can learn how to recognize a handwritten
character on the basis of a single example (see “This AI Algorithm Learns Tasks as Fast as We Do”).
Yet none of these explorations have so far revealed a path that seems guaranteed to lead to
unsupervised learning at close to the human level, or software that can learn complex things about
the real world just by experiencing or experimenting with it. “Right now we seem to be missing a key
idea,” says Adam Coates, director of the Chinese search engine Baidu’s Silicon Valley AI Lab.
Supervised learning still has a lot to offer while the search goes on, says Coates: Internet companies
have access to a wealth of data on the things people do and care about, feedstock that can be used
to build things like voice interfaces and personal assistants much more capable than those we have
today. “In the near term there’s a lot you can do with labeled data,” he says. Large companies spend
millions on getting contractors to label data to feed into their machine-learning systems.
LeCun of Facebook believes that researchers won’t be forced to subsist on labeled data forever. But
he declines to guess how much longer the engine of human intelligence will remain out of reach to
software. “We kind of know the ingredients; we just don’t know the recipe,” he says. “It might take a
while.”
Google Injects Machine Learning Into Analytics App
Selfies will soon be passwords for mobile
banking
FEBRUARY 24, 20161:07AM
Selfie check ... Raghav Malik, Senior Analyst in Enterprise Security Solutions, demonstrates the
Identity Check feature at the MasterCard stand at the Mobile World Congress. Picture: Carlos
Alonso/AP Images for MasterCard
James Covert and staff writersNew York Post
WHAT’S worse than too many selfies? Too many passwords.

Page 28
MasterCard says it’s rolling out a new feature this year in some countries that will accept selfie photos
as an alternative to passwords for verifying mobile payments,The New York Post reports.
MasterCard says users of selfie pay will be asked to blink into their phone cameras to verify they
aren’t simply holding up a photo.
Owners of the latest iPhone 6 and 6s also will be able to use a fingerprint as an alternative form of
verification.
“Consumers hate passwords,” said Ajay Bhalla, chief of Mastercard’s safety and security division. He
added that “the most commonly used password is 123456, so they are not secure.”
To make matters worse, people often use the same password for multiple sites, further widening the
exposure to hackers, Bhalla noted.
With the new selfie tech, MasterCard is looking to reduce rejections of legitimate transactions, which
cost the credit-card giant an estimated $US118 billion each year — 13 times more than the cost of
actual fraud.
Software trials were carried out in the US and Netherlands last year, BBC reports, adding that the
rollout this year would involve the UK, US, Canada, Netherlands, Belgium, Spain, Italy, France,
Germany, Switzerland, Norway, Sweden, Finland and Denmark.
MasterCard, which made its announcement on Monday at the Mobile World Congress in Barcelona,
joins other big firms including Chinese e-commerce giant Alibaba in experimenting with facial
recognition technology.
Last week, HSBC announced it will soon begin using voice-recognition and fingerprint technology to
help its banking customers access their money.
Chief ... Richard Haythornthwaite, Chairman of MasterCard, left, views a product demonstration in the
MasterCard stand at the Mobile World Congress. Picture: Carlos Alonso/AP Images for
MasterCardSource:AP
This story originally appeared in The New York Post.
Mastering Data and Analytics: 'Table Stakes'
for Digital Business
10 June 2016 | ID:G00302418 Jamie Popkin, Valerie A. Logan
This research examines the need for data and analytics to be seen as a core capability for digital
business. It argues for applying data and analytics for intelligent business processes and decision
design, and urges CDOs and CAOs to address these issues systemically, not incrementally.
Overview
Key Challenges
Chief data officers (CDOs), chief analytics officers (CAOs), and other data and analytics leaders:
• Are on a difficult change management journey to build and fulfill a strategy for using data and
analytics capabilities as a key component in the transition to digital business.
• Need to shift the organizational mindset from regarding data and analytics as a set of disparate
applications and datasets to viewing it as a deliberate, strategic layer of digital business.
• Need to prepare the organization for exploiting pervasive business instrumentation, rigorous
information management, and expansive analytics for business value; in other words, prepare the
organization to compete in digital business.
Recommendations
• Approach data and analytics as a core strategic capability within a larger digital business
strategy, not simply as a set of related initiatives.
• Leverage data and analytics for intelligent business processes, which identify and enable
digital business moments.

Page 29
• Start small and build momentum by alleviating operational pain and deriving business value.
• Build an agile, repeatable methodology, positioning data and analytics capabilities as
embedded within the infrastructure of digital business.
Introduction
The transition to digital business requires CDOs, CAOs and other data and analytics leaders to make
a leap toward a new view of data and analytics. They need to move past the old mindset of siloed
data, business applications and analytics applications being grounded in data warehousing and
business intelligence (BI) systems, primarily for enterprise reporting and basic analytical purposes. In
the digital business era, data and analytics needs to be thought of as an enterprise layer of the digital
business fabric that will power intelligent business processes.
During a time of rapid change, it feels safe to focus on incremental changes to avoid any disastrous
commitment in the wrong direction. But the idea of embedding data and analytics in the digital
business infrastructure demands a break from incrementalism and requires bolder thinking. The
transformation to digital business is not incremental. It requires a recasting of the entire business
model and will touch all areas of operations. Data and analytics will be embedded in successful digital
business models and business processes as opposed to being an "after the fact" addition to business
application data capture and processing. An incremental improvement program will be left behind by
those driving the digital business transformation because they need data and analytics to be an
integral foundation of digital business. Generally, IT leaders need to relinquish some of the
technology architecture control they have historically held and collaborate with digital business
architects in a new way.
Our discussions with clients indicate that most organizations face this transformation issue in one of
two ways:
• In the first instance, business management has understood this challenge from a data and
analytics perspective and has created a CDO position. The person who fills this role is tasked with
immediately creating a "data and analytics strategy." Organizations that have adopted this approach
are currently in the minority.
• In the second type of situation, the digital business model transformation is underway and the
importance of data and analytics becomes a very clear component of the overall strategy, with or
without a CDO being named. Enterprises not working to develop digital business models and
supporting infrastructure today will find themselves functionally behind within three years.
In either situation, getting the strategy right depends greatly on the mindset that prevails during the
preparation phase. The strategy preparation phase establishes the narrative for understanding and
validating the required investments and process changes required to use data and analytics
effectively in digital business model operations. This phase of strategy development requires a vision
(see "The Chief Analytics Officer's Vision Sets the Narrative for the Business Analytics Strategy" )
and needs to respect the four types of data and analytics strategy (see "A Good Information
Management Strategy Starts With Vision and Values" ).
CDOs and other data and analytics leaders are on a journey to build and fulfill a strategy for using
data and analytics as a key component in the transition to digital business. Moving to digital business
is not an incremental change; it is dramatic and all-encompassing. Incremental approaches tend to
reflect compromises that will not break down silos fast enough, or will leave functional gaps that
perpetuate kludges rather than resolve them (see "Digital Business KPIs: Defining and Measuring
Success" ). Data and analytics capabilities will be embedded in the new digital business models that
have begun to emerge and will continue to mature during the next three to five years. New digital
business models mean that the underlying business processes are, likewise, undergoing digital
business transformation. The goal is not necessarily to eliminate siloed applications and datasets.
The goal is to build a digital business that may require the elimination of some large siloed
applications and datasets to achieve the transformation.

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Are you ready for a leap away from siloed applications, in-fighting over who owns the datasets and
rigid business processes that, in many cases, were built for 20th-century business models? Are you
ready for the leap into the emerging world of digital business? The following best practices will
prepare you for the leap into the emerging world of digital business by emphasizing the need to place
data and analytics at the core of your business strategies.
Analysis
CDOs, CAOs and other data and analytics leaders should position data and analytics as an inherent
component of digital business.
Approach Data and Analytics as a Core Strategic Capability
The idea of data and analytics as one of the platforms of digital business has three components:
1. Business instrumentation comprising:
o New connections — the physical and/or virtual means of communicating or sensing through
capturing data from physical infrastructure, information signals and business processes; and
computing applications (e.g., IoT devices, consumer wearables, ecosystem-based partners)
o Data/information exchanges — representations of events and activities that have meaning
within the business infrastructure and are about data structure and format, as well as raw information
2. Business administration (for nontransactional-centric work):
o Business intelligence and traditional analytics used for performance management, reporting
o Business processes related to business planning and budgeting
o Data and applications to model formal but low-variable-based outcomes, core to business
administration
3. Intelligent business processes (for transactional-centric work):
o Decision management and analytics technologies are used to derive, capture and convey
operational context across one or more interactions executing in a process instance
o The decision option selected by the decision model is acted on by a human or system to
dynamically alter the course of a process instance as it executes
o Data and applications for more complex and high-variability-based outcomes and decisions
Figure 1. Data and Analytics Platform for Digital Business
BI = business intelligence
Source: Gartner (June 2016)

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The big shift in thinking is that data and analytics is not simply a set of related disciplines, but instead
has become a multidisciplinary field within a larger digital business strategy.
The current siloed infrastructure is problematic in two ways. First, when applications are siloed and
analytics and data are perceived as artifacts or byproducts of applications, then there will always be
the potential for rapidly escalating data integration expense and data quality risk exposure. The
second and more insidious problem is that an application-centric view of data and analytics is a
flawed but deeply ingrained, common approach.
There is a great deal of institutional inertia in continuing to manage and integrate silos. Look around
your enterprise and you can see the institutional inertia manifested in job roles, titles, decision-making
protocols, information-sharing protocols and business process operations. It is the key challenge to
CDOs and other data and analytics leaders to lead the enterprise into a new understanding of how
data and analytics can be managed differently within digital business.
Data and analytics is a key component of digital business; but to what end? By adopting the strategic
approach of viewing data and analytics as part of the fabric of digital business, an enterprise will be
well-positioned to support digital business through the development of intelligent business processes
(see"Make Business Operations More Agile With Intelligent Business Processes That Reshape
Themselves as They Run" ).
Focus on Intelligent Business Processes
Business transformation and process leaders have historically treated business processes as if each
were a train. They've laid track (standardized processes) so that passengers (specific work items)
efficiently arrive at a finite set of predefined destinations on time and at reasonable cost. Some
processes, however, are metaphorically ill-suited to journey by train (see "Make Business Operations
More Agile With Intelligent Business Processes That Reshape Themselves as They Run" ). Business
processes that involve reinventing knowledge work, transforming customer experience, and distilling
and acting on insights from IoT, analytics and decisions are different. They must get to ambiguous
destinations and pave new and volatile paths. Intelligent business processes are a more appropriate
mode of transportation for these business processes, but few organizations can marshal the right
data management, analytics, decision management and business process management (BPM)
capabilities to derive the operational context needed to reinvent business processes as they execute.
Intelligent business processes use decision management and analytics technologies to derive,
capture and convey operational context across one or more machine-to-machine or people-to-
machine interactions executing in a process instance. In other words, building a digital business
requires a rethink of the use of data, analytics, process and applications. Specifically, intelligent
business processes rely on real- or near-real-time access to properly structured data and accessible
unstructured data (descriptive and diagnostic analytics), and use predictive and prescriptive analytics
to dynamically execute a business process that is modified by the context of the transaction (see
"Make Business Operations More Agile with Intelligent Business Processes that Reshape
Themselves as They Run" ).
Business transformation leaders, process leaders and data and analytics leaders all struggle to
identify the degree and types of intelligence their processes need to get to strategic business
outcomes.
Digital business is challenging long-held beliefs about process and is driving radical transformation of
business processes and business models in most industries (see "Rethink Hammer's BPM Principles
for the Digital Age" ). Consequently, smart or intelligent business processes are among the most
important modern technology areas in which CEOs plan to invest over the next five years (see "Eight
Dimensions of Process IQ Determine How Smart Your Process Needs to Be" ).
You could equally apply the same capabilities of intelligent business processes to the non-
transaction-based work related to business administration. However, the outcomes and work
supporting them do not, as a rule, provide the level of advantage of disruption commonly found in a
digital transformation. So at this point it is far better to focus your innovation efforts on intelligent

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business operations. As your skills and capabilities mature, some benefits will bleed over to the
business administration. For example, a "data catalog" that might benefit a discovery process for
some customer-facing insight might eventually help streamline a budgeting process for customer
service resource planning.
Start Small and Build Momentum
Gartner clients often ask: "Where should data and analytics be applied?" The answer is that data and
analytics gets applied everywhere it can make a difference . Any data that can be defined can be
captured. Almost any analysis that can be conceived of can be calculated.
One of the interesting implications of data and analytics as part of digital business is that everything is
a target. Organizations should start small but also start anywhere there is operational pain and an
opportunity to get traction and deliver business value. Every element of the business infrastructure
has attributes, functions and yields outcomes. Data and analytics can be used to both report on the
operation of each business infrastructure element, as well as be used to operate the element.
Take business administration as an example. Business administration uses BI and performance
management (descriptive and diagnostic analytics) to report on operating results. At the same time,
an intelligent business process that monitors actual versus budget results can automatically alert
business managers to take an action, or can dynamically modify spending approvals for a project
(predictive and prescriptive analytics). This business instrumentation yields benefits to business
administration and intelligent business operations.
The goal of this phase of strategy preparation is to discuss the use of data and analytics in the
context of digital business. There is no better context than operational pain in the form of inefficient
operations, high costs, risk exposure and poor customer service. The best way to establish belief in
the strategic approach is to quickly show the potential to resolve the pain and mitigate risk.
Initial proofs of concept or pilots should target areas where there is an obvious problem with
instrumentation, data access and the value of existing analytics. Look for willing partners and bring
them along on the journey to document the opportunities for improvement. For example, is there a
use case or business process that requires a single view of the customer? A common issue is that
there is significant and costly human effort required to create a single view of the customer in use
cases like consolidating invoices, creating single views of customer activity and identifying candidates
for upsell/cross-sell. The single view of the customer initiative is usually well understood by the
business, but today is solved through manual data integration and human operational and tactical
decision making. CDOs and CAOs can propose an alternative approach to conventional solutions
that incorporates data and analytics as a component of digital business.
Make It Matter: Build an Agile, Repeatable Approach
The strategic positioning of data and analytics as a platform for digital business requires the
development of a methodology for diagnosing problems, identifying opportunities, communicating the
diagnosis and developing alternative solutions. This section outlines the components of the
methodology as a starting point.
Diagnose
With the target initiative identified (a specific process, decision, report or analysis, for example), and
in cooperation with the business owner, conduct the following business diagnosis process:
• Identify and inventory the instrumentation methods. The purpose of this step is to highlight any
clear deficiencies in instrumentation. Focus on answering questions such as, "What data would we
like to get but are unable to because our instrumentation does not provide that level of access,
granularity, etc.?" and "What are the alternative instrumentation options available to us?" This will
provide a baseline for future instrumentation updates and investments.
• Identify and inventory the dataset/stream characteristics coming from the existing
instrumentation. Focus on answering questions like, "Are we getting this data in the format and at the
pace required for business operations?" and "Can anyone use the data without additional extraction,
transformation and loading (ETL), or other transformations?" This will provide a baseline for future

Page 33
application updates, data integration and data quality program modifications, and possible enterprise
master data or other data standardization efforts.
• Identify and inventory the analytics capabilities being applied in the target initiative. Focus on
answering questions such as, "Are there analyses we would like to be doing but do not have the
knowledge or skills to perform?" and "What are the training and staffing investments that need to be
made to raise business analytics maturity"? This will provide a baseline for both determining gaps in
analytic prowess relative to competitors, as well as identifying human (and machine) resource
development investment areas.
• Reimage the business process as an intelligent business process by reforming the decision
model, using the new data, the new sources and the new analytic techniques.
• Define the quantifiable impact of what is enabled by treating data and analytics as a foundation
of digital business. Analyze the end-to-end impact of an enterprise view of instrumentation,
data/information exchange, analytics capabilities and the ultimate effect on the decision-making
protocols.
Communicate
Communication will be critical to the efforts of CDOs, CAOs, and other data and analytics leaders to
build consensus around this strategic preparation approach. The narrative that the CDO and the other
data and analytics leaders use needs to be linked to specific business outcomes. These early
projects or initiatives may best be sponsored by an analytics center of excellence as a way to
demonstrate collaboration and enterprise buy-in for the project and approach.
Harvest and Iterate Solutions
Accepting data and analytics as a keystone in the infrastructure foundation of digital business is
important to your long-term implementation strategy. Alternative solutions should be framed in the
context of "as is" (instrumentation, data stream characteristics, and analytics capability) and "can
be"/"to be" — i.e., what would we like to achieve is framed out by what can we achieve in the
following time period on our path to the ideal.
Data and analytics will increasingly be seen as a core capability for digital business. This will require
organizations to reconsider long-standing process and process modification approaches on the path
to intelligent business operations. This is difficult and requires a dedicated and systematic effort.
Take the leap; do not be incremental!
© 2016 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of
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Objectivity."

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Setting effective marketing metrics
8 September 2016
LONDON: If measurement is crucial to understanding marketing effectiveness, then choosing the
right metric is no less so and marketers can ask five questions to help decide what metric is
appropriate.
In a Warc Best Practice paper, How to set marketing metrics effectively, Neil Bendle, Assistant
Professor in Marketing at the Ivey Business School, Western University, London, Ontario, Canada,
outlines the benefits of the WAITA model – Who, Assumptions, Ingredients, Theory, Action – when
assessing which metrics to use.
The first question to ask, he says, is "who uses the metric?" Metrics that relate to a firm's published
financial accounts or stock market valuation, for example, will reflect many things that individual
marketing managers can't influence much.
"An effective metric should connect to something that the metric's user influences," he states.
It's also important that marketers understand the assumptions behind any given metric. When
considering customer lifetime value, for example, the standard formula assumes an infinite life of
customers – something that is clearly impossible, but which Bendle observes isn't as divorced from
reality as it at first sounds.
"The formula's usefulness comes from appreciating that, providing retention rates are not very high
(that relatively few customers survive for a very long time) and discount rates are not very low (that
the value of future cash is considerable less than today's cash), the impact of the far future on CLV
becomes trivial."
Subsequent use of the chosen metric will require an understanding of the source of the data that is
going into it; a survey reporting aided brand awareness typically produces very different results from
an unaided one.
And a grasp of the theory behind a metric is advisable, says Bendle, otherwise marketers can find
themselves mistaking correlations in data for casual links. "Along with insight there is a lot of
nonsense to be found in big data if you look hard enough," he cautions.
Finally, "marketers should always have a clear idea of why they want to calculate a metric before
doing so" – and know what action they intend to take as a result.
Establishing a historic customer's value over their lifetime, for example, is useful only if one can find
new potential customers similar to the prior customers.
Bendle cites Netflix as an example of a brand that has extended customer lifetime value by using a
full range of data to track customers' viewing habits and determine how to better engage each
individual customer; by doing so it has reduced churn to 4%, he notes.
Data sourced from Warc
Ashley Friedlein’s 10 digital marketing &
ecommerce trends for 2016
By Ashley Friedlein @ Econsultancy
Each year I select digital trends and developments which I believe will shape the industry and digital
marketing planning and thinking.
These are a personal selection, so are somewhat esoteric and likely skewed to those which most
interest me.
And each year there seem to be a different number.

Page 35
There are a whole load of trends that will no doubt happen but seem to me so self-evident as not to
be worth detailing.
Among those: continued war for talent, increased focus on privacy and security, morenative ads,
more programmatic media buying, ongoing culture challenges, ad blocking increases, more social
channels to master, more payment options, ongoing efforts to be agile, emphasis on the importance
of personalisation and customer experience, omnichannel this and that, and, of course, fifty shades of
data.
There are also lots of exciting technology developments which no doubt will have a wider impact on
marketing in the future but which do not make it into my list for the coming year.
Among those: 3D printing, virtual/augmented reality, wearables, nearables, internet of things, the
blockchain.
I am more immediately excited about what machine learning and artificial intelligence can bring to
marketing.
This is quite a long read, so to make it more digestible you can jump to the sections you’re most
interested in using these links:
1. Marchitecture
2. Funnel Wars: CRM strikes back
3. The return of push
4. Digital/Physical: will it blend?
5. The ascendance of design
6. Digital Transformation: the teenage years
7. Robobranding
8. It’s mobile, stupid
9. Video
10. Peak content
Now, on with the show...
1. Marchitecture
Could this bastard lovechild of marketing and architecture become a buzzword for 2016?
Even if not I would at least expect to hear much more talk about ‘martech’ and challenges around
architecting your martech stack. Move over ad tech, martech has arrived.
Why is this?
In the preceding years we have been busy collecting data, buying technology, trying to integrate
systems, launching new channels (particularly social and mobile) and trying to deliver increasingly

Page 36
personalised customer experiences against a background of increasing complexity and
fragmentation.
It is hard. It is a bit of a mess. We are worried the whole thing might fall over at some point.
No-one is quite sure of all the triggers, rules, tags and automation in place.
Some questions for you:
• Are you confident you have made the right decisions in your marketing technology ecosystem
between buy, build, integrate or inter-operate? Are you sure whether a single marketing platform
(‘cloud’) is better for your business than integrating best of breed point solutions? Do you consider the
martech landscapewith a sense of calm?
• Are you happy with your data governance, data integrity, and confident in your marketing
resource management with security, privacy and process issues nicely buttoned down?
• Do you have faith in the data taxonomies, metadata, models and schemas powering your
digital content and marketing?
• Is it clear what marketing logic (rules, processes, triggers, events, automation etc.) drives all
your various marketing touchpoints with your customers and what this means in terms of the
customers’ actual experiences across devices and channels?
• Is your marketing stack clearly articulated? Here are 21 marketing stacks for illustration.
These are hard questions. But they are not going away and they will become more frequently asked
in 2016.
There is a great interview with BCG’s Philip Evans on ‘stacks’ and ‘architecture’ as business
concepts. There are clear parallels with marketing.
Shearing layers was a concept coined by architect Frank Duffy, then elaborated by Stewart Brand in
his book “How Buildings Learn: What Happens After They’re Built”, and refers to buildings as
composed of several layers of change.
This concept has already been adapted to tech system architecture by the likes of Gartner, but also
makes a lot of sense as a framework for architecting marketing ecosystems that can deal with the
level of change we are experiencing.
There are even greater parallels between marketing and engineering as the worlds of digital, data,
technology and marketing collide.
We have no shortage of data but we now need to create rules and logic, a form of marketing
middleware, to drive all forms of marketing automation. And this is essentially programming.
Not just programmatic media but programmatic marketing more generally.
Start-up marketers (aka ‘growth marketers’) are already used to the likes of IFTTT andZapier to wire
up their marketing tech. Marketing ops have a lot to learn from dev ops.
The rise in the strategic importance, and difficulty, of all this is why even strategy consultancies like
McKinsey are growing their marketing ops practice and why it bought Agiliti just over a year ago.
Expect more M&A in the agency and consulting worlds around ‘marchitecture’.
2. Funnel Wars: CRM strikes back
Just when you thought it couldn’t get any more complex...
In the graphic below on the left is a classic marketing funnel. In the middle, at the top, you can see
the famous LUMAscape graphic showing the complexity of the vendors in the display ad tech space.
These typically cover the top half of the marketing funnel.
In the middle, covering the bottom half of the funnel, is Scott Brinker’s Marketing Technology
landscape graphic which is equally busy.
To the right are the service businesses (agencies and consultancies) with a crude split showing the
(mostly media) agencies servicing the top of the funnel and the SIs and consultancies servicing the
bottom half.
Agencies tend to talk about DMPs (Data Management Platforms) whilst the back end centres more
around CRM (Customer Relationship Management) platforms.

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My observation, and trend, is not only how complex this all is and how it needs some brains to
properly architect it all (see previous trend) but that these two “halves” of the funnel, historically quite
distinct, are fast merging into a single view of the customer journey where there is data visibility,
tracking and tech inter-operation throughout the funnel.
The big resulting question is who should be in charge and which system, or what data, should drive
the other?
Do you dump your media agency and give it all to a management consultancy who is good with
business/CRM data and can use programmatic platforms to drive the top of the funnel?
Or do you open up your back office data to your media agency and target them on metrics like sales
and margin rather than more traditional media metrics?
This is the war that is raging in agency-consultancy land.
WPP bought Acceleration and Essence, among others, to bolster its data-throughout-the-funnel
capabilities (note GroupM’s Gotlieb: ‘Media Needs To Morph From The Top Of The Funnel To The
Transaction’) whilst all the big consultancies (Accenture Digital, IBM Interactive Experience, Deloitte
Digital, PWC Digital, McKinsey, BCG, Cap Gemini, Tata etc.) are rapidly encroaching on traditionally
agency space.
And in techland DMPs and CRMs are the front lines of the/martech tussle.
Oracle’s acquisition of BlueKai, a leading DMP, connecting it natively into its marketing cloud, is one
example of the bottom of the funnel swallowing the top half.
Expect more marketing cloud companies to assimilate DMP and CRM offerings this year.
So who will win these battles?
Obviously there is no simple answer. But certainly the once-so-sexy world of media and advertising at
the top of the funnel is looking seriously threatened by its historically less glamorous below-the-line
cousin.
Argos’ case study in joining up real-time advertising through the customer funnel is one of an
increasing number of brands using CRM data to drive top-of-the-funnel advertising and media in real-
time.
The idea of ‘streaming CRM’ will become more commonplace: read about streaming CRM in the
context of travel here and note Sociomantic is owned by dunnhumby, in turn owned by Tesco, both
companies known much more for transactional data than media.
Recent Marketing Week articles include “How CRM is becoming the ‘new advertising” and “Why
CMOs are shifting their focus from customer acquisition to retention” backed with data and trends to
support a view that the bottom of the funnel might usurp the top rather than the other way round.

Page 38
3. The return of push
The early days of digital marketing were all about push marketing.
Display advertising, of course, but email lists were a big thing. Lists you built yourself or lists you
bought. And then hammered away at.
Then we shifted to more of a pull paradigm. ‘Inbound marketing’ is very much pull not push.
SEO in its more mature form is pull, content marketing is more pull than push, social likewise.
But I think we are seeing a shift back towards more of a push architecture. In a small way this is just
desperation around those who have spent money on content and mobile apps, find they are not
getting much traction, so resort to more push advertising.
But more fundamentally this about messaging, notifications and more context-aware services.
Already the notification screen is the primary interface for mobile. All the big players (Google,
Facebook, Apple, Microsoft, Amazon etc.) are rapidly developing services that are ‘smart’ and
assistive.
Whether the slew of personal assistant type applications (Siri, Google Now, Cortana, Facebook M
etc.) or sensor-driven smart services (Amazon Dash, Google Nest etc.) or simply the sky-rocketing
usage of messaging apps like WhatsApp and WeChat and the resulting ‘tings’ on our phone craving
our attention.
The evolution I believe we are in goes something like this:
• First we focus on joining up data and systems, then...
• We deliver experiences that are consistent, synced and responsive across devices/channels,
then...
• We make them personalised, proactive and contextual.
‘Context’ has a lot of possible dimensions: behaviour, location, the weather, what is happening in the
world, the time of day, device, pretty much anything.
Because of mobile, and the growth in location intelligence (iBeacons being just one example but the
likes of Estimote are doing interesting things), it is likely that user behaviour and location will be the
most common forms of ‘context’ to be used in our marketing and customer experience thinking this
year.
The best articulation of this shift I have read is Fjord’s concept of ‘Living Services’ where they not only
talk about new interaction paradigms like gesture, voice and touch but how we need to consider how
environments and context are changing more than how industry sectors are changing.
We need to build aware platforms where the customer is the operating system we plug into.
For example, this case study from Telefonica Research shows how it is possible to tell how bored
someone is from their mobile activity with an 83% accuracy rate.

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In this test the bored participants were sent notifications recommending content on Buzzfeed and
were much more likely to respond than the non-bored segment.
So we are witnessing behaviour whereby a prod (i.e. push), mostly in the form of a notification, is
required to get attention.
But that interface (now mostly via the lock screen on your phone) is controlled by the mobile
operating systems and who knows how they will choose to prioritise what the user gets and how
those notifications will be prioritised in the future.
And with predictive and assistive services it may be we will not expect to “go” to anything on our
phones - it will come to us.
The big question for us as marketers then is how on earth do we fit in? And how will we make sure
our notifications are seen and heard amidst the torrent of others?
As we re-enter an era of push, albeit ‘smart push’, we will need to re-learn the lessons from email
marketing about permission, relevance, context and personalisation.
4. Digital/Physical: will it blend?
The blending of digital and physical is not a new trend but it is one that will continue to be front of
mind throughout 2016 and beyond.
Last year we saw a lot of interesting developments from the big ‘digital’ players in the physical world:
Amazon opened a bookshop and turned domestic appliances into a retail channel via its Dash
Buttons; Google opened its first store in London.
There was some impressive innovation around digital/physical from major brands too. Highlights for
me included:
• Burberry lets passers-by take over Piccadilly Circus screen to create personalised scarves.
• Domino’s Anyware service and rival Pizza Hut’s box that turns into a movie projector.
• The Starbucks Roastery App Experience (see video below)
• Carlsberg’s #happybeertime and its point of sale Barbox platform.
• Hive’s #tweettoheat Twitter-operated bus shelter.
• The Women’s Aid digital out-of-home campaign.
This year we will see further innovation, for example more programmatically driven digital out-of-
home media.
Where it gets really interesting is when digital is used to create the physical. The opportunities around
3D printing are very exciting here of course.
Eyewear business Warby Parker already provide a mobile app called Bookmark that allows
customers to see a photo of themselves and buy the glasses, but CEO Neil Blumenthal envisages
"...that in the very near future you’ll be able to get your glasses prescription through your mobile
device" and, who knows, perhaps you will be able to print them out at home too?
From a brand point of view it is interesting to see how digital is seeking out further depth and
substance through a physical connection and manifestation.
Evernote has partnered with Moleskine to create Evernote books for example.
3M’s Post-it notes, quintessentially physical, were given a quasi-physical manifestation asreborn
retargeted banner ads.
5. The ascendance of design
One of my three digital marketing mega trends for 2015 was the return of creativity and design. Then
I focused on creativity.
This year I want to highlight design. More specifically, digital product/service design.
It is always helpful with trends to look at the jobs market and see which roles and expertise are most
in demand.
Great developers are still gold dust but in the last six months or so the question I keep hearing is
‘does anyone know a great (digital) designer’?
That special person who not only gets the big idea, the brand, the look and feel, but can also do
information architecture, gets UX and UI, appreciates the customer journey, obviously knows

Page 40
responsive inside out, is current with this morning’s latest trends in iOS vs Android transition effects,
and is working on conversational interfaces in his/her spare time.
And, like good childcare or a great plumber, if you do know this person you sure as hell are not giving
their details to anyone else.
Speaking to a few agency Creative Directors recently they admitted they were starting to feel out of
touch with aspects of their craft.
In particular, prototyping and app design/concepts. Talk to startups and product managers/designers
and you will hear about Sketch, Invision, Marvel and the like.
The corporate world is catching up. Indeed Adobe’s imminent launch of Comet must be its response
to this need.
Expect a lot of activity in this area, both tech, talent and techniques, over 2016.
Also indicative of underlying trends is what is happening in mergers and acquisitions. Here are some
headlines that tell a story around the ascendance of design:
• Accenture bulks up design capabilities with Fjord Expansion.
• Consulting giant McKinsey buys itself a top design firm.
• Agency acquisition frenzy: Now Deloitte snaps up UX agency.
• EY UK looks beyond audit with digital design purchase.
• PwC completes asset acquisition of digital creative consultancy BGT.
• Cognizant acquires Cadient Group.
• Wipro to acquire Danish firm Designit.
• BCG Digital Ventures acquires S&C, an award-winning strategic-design firm.
• You get the idea...
All the major consultancies, both management and strategy, as well as the systems integrators are
investing considerably in design services.
Indian outsourcing companies recognise they need to beef up their design credentialsand I expect we
will see Chinese businesses buying their way into this space too.
Let us not forget that IBM Interactive Experience last year announced a $100m investment to expand
its interactive design business, acquiring talent and opening interactive experience labs and studios
around the world.

Page 41
Indeed even in 2014 IBM Interactive Experience was named the largest global digital agency by
AdAge and in 2015 IBM IX came second only to Sapient in Econsultancy’s Top 100 Digital Agencies.
Perhaps the most interesting acquisition in this area was at the end of 2014 because it was a major
financial services brand buying a leading product design consultancy:Capital One acquired Adaptive
Path.
In 2016 it would not be surprising to see more brands make design acquisitions or acqui-hires.
At the very least expect to see design and product people become part of senior leadership teams
e.g. Mike Bracken’s hiring of his former Government Digital Services’ colleagues to The Co-Op Digital
Service includes a Digital Services Director and Group Design Director to help lead the Co-Op’s
digital transformation.
Finally, whilst the big tech companies may have been focusing on data and digital marketing
platforms and services to date, expect to see much more focus on design this year e.g. with Adobe’s
launch of Comet and Google (behind Material Design of course) set to further empower designers
with Google Web Designer.
6. Digital Transformation: the teenage years
While Econsultancy cannot quite claim to have coined the term ‘digital transformation’ (I would
probably give that accolade to Cap Gemini), we certainly helped popularise the term.
My presentation on Slideshare on Digital Transformation from 2013 attempted to define the term at
the time.
Certainly we have been researching, writing about, consulting on, and helping deliver digital
transformation for longer than most.
I describe digital transformation simply as the journey towards being a digital organisation where
“digital” means two things: firstly, focusing on the customer experience irrespective of channel, and
secondly, having a digital culture.
I believe the seven defining characteristics of a digital culture are:
1. Customer-centric
2. Data-driven
3. Makers & Doers
4. Transparent
5. Collaborative
6. Learning
7. Agile
As part of this transformation journey most organisations follow a similar evolution of organisational
structure.
Full details of this are given in Econsultancy’s recently updated Digital Marketing: Organisational
Structures and Resourcing Best Practice Guide.
The graphic below outlines a typical five stage evolution towards true multi-channel customer-
centricity. Each stage has a typical corresponding job title and organisational structure for digital.

Page 42
My observation for 2016 is that most businesses are somewhere between stages two and four. We
are entering the teenage years for digital transformation.
These are years of change, of experimentation, of pain, of growth, of tumult, of crises of self-identity,
of commotion and instability.
We have already seen in my trends two and five above how the agency and consultancy worlds are
colliding and blurring.
Apparently pretty much everyone these days offers ‘digital transformation’ services of some sort.
On the client side we will continue to see re-organisations, new job titles like Chief Digital Officer or
Chief Customer Officer, new joint ventures, labs, innovation centres, start-up partnerships,
accelerators and acquisitions in an attempt to kick start or accelerate their transformations.
2015 saw a number of examples of brands buying, or investing in, digital agencies and talent: Jaguar
created a joint venture with agency Spark 44 to manage its global communications; Coty bought
content agency Beamly; Unilever has its Foundry; Visa set up Europe Collab; Barclays has its
Accelerator; the list goes on.
In the early years of digital transformation most businesses had digital in a silo.
This created obvious problems so the broad consensus was that actually digital needed to be
embedded throughout the core business.
So the last years have seen efforts to ‘digitize’ the mothership and make digital part of the operating
model and DNA of the whole business. It turns out this is not very easy either and has all sorts of
challenges too: the biggest of which is a lack of speed.
One possible approach to address this problem, promoted by McKinsey, is a two-speed operating
model for accelerating digital transformation.
Either this is somewhat of a bodge to avoid driving through difficult but necessary change, or it is a
smart and realistic way to get where you want faster without dangerous levels of disruption.
Whichever it is, expect to see more struggles, at varying speeds, with digital transformation this year.
7. Robobranding
Trying to humanise technology is not new. You may remember Microsoft’s paperclip character.
Around five to ten years ago there was also a fashion for putting characters on virtual agents which
were typically for customer service and sat on top of an ‘intelligent FAQs’ database.
National Rail has Ask Lisa and has done since 2007.
With the progress in machine learning and AI (artificial intelligence), conversational interfaces, and a
flurry of branded bots appearing this trend is back.
The popularity of emojis, and digital stickers, also show the desire to embed more feeling and
emotion into digital communications.

Page 43
In trend four above we saw how the world of pure digital is trying to connect more deeply through
physical manifestations.
Similarly, brands, particularly digital services, are now seeking to create more emotive connections by
bringing personality to their technology.
We are moving beyond robots that only deal in commands, interactions and transactions.
Technology can detect our emotions (e.g. Emotient, or Google’s Cloud Vision API), robots can detect
how we feel (like Pepper) and any self-respecting cool piece of tech has a bot (e.g. Slackbot) and,
increasingly, extensible platforms to create your own bots, e.g.Telegram’s Bot Platform or Slack’s
Slash Commands.
Ray Kurzweil, director of engineering at Google, recently forecast that in 15 years’ time it will be
possible to have an emotional relationship with computers.
This was made real in the 2013 film “Her” portraying a man, Theodore Twombly, who falls in love with
‘Samantha,’ an artificially intelligent operating system.
If this seems far-fetched I should point out that I have recently been interacting very naturally and
successfully with “Amy Ingram” an AI-powered personal assistant for scheduling meetings.
Amy seems happy to work long hours and even replies at the weekend.
The mixing of human and machine is also evident in the many concierge services springing up.
Among them Pana (for travel), Operator and GoButler.
Typically, these services work using part human, part machine learning. The interesting one to watch
here of course is Facebook M.
Pure human assistance is very useful but not very scalable. Pure machine is very scalable but not
always very useful. M’s challenge, and services like it, is to be both.
What does this all mean for marketers? It creates all sorts of exciting opportunities to create more
intelligent services and ones which, though digital, really resonate with the brand and have
personality.

Page 44
In a few years I expect we will find it odd not to be able to message a brand and have a conversation
which we will expect to be bot-powered to start with.
Some of us may even prefer to interact with branded bots rather than humans.
The challenge for us, as marketers, will be how to imbue these robobrands with the right brand
sentience.
It will mean great copywriting is once more highly prised and interfaces will become more verbal.
Getting the right tone and the right attitude will be hard but those that do will win.
8. It’s mobile, stupid
We all know that the fabled ‘year of mobile’ was about a decade ago.
In the last two years most of us have finally got round to mobile-optimising our websites and emails
typically using responsive design.
However, what slightly surprises me is that for many marketers I get the sense they think that means
they have ticked the mobile box, mobile is covered, mobile is mostly ‘done’.
Mobile (and the same is true of video and even social) tends not to appear on the hot topics or
buzzwords list.
Which is odd given we surely recognise that mobile is eating the world?
So I have put mobile in as a trend largely as a collective slap in the face to remind ourselves just how
big a thing this still is.
Remember:
• By most metrics mobile now IS the internet. And for most developing nations mobile is the
internet.
• Last year we passed the point where there are more searches on mobile than desktop.
• For many businesses and customers things are not just mobile first, they are mobile only. Last
year McKinsey published some fascinating research on mobile shoppers in South Korea: among
those who shopped on a mobile device, 13% did not shop in stores, and 53% did not shop online.
• More than half a billion people access Facebook solely from mobile and sometime soon
Facebook will become mostly a mobile experience with the majority of video views and sharing
already mobile-dominated.
• Atom Bank will launch in the UK this year as a mobile-only bank.
• Mobile messaging is HUGE and growing massively. Not just in B2C but B2B – you may have
noticed LinkedIn’s recent developments in messaging?
• Messaging apps have caught up to social networks in user numbers and now dominate mobile
• Mobile commerce is predicted to grow to $31bn next year, up from $3bn in 2010.
• Walmart reported that over 70% of the traffic to Walmart.com is now mobile and that mobile
accounted for over half of its orders since Thanksgiving – double last year.
• Alibaba’s Singles Day in China saw 27m mobile transactions in the first hour.
• Get your mind blown by what WeChat can do and read about Facebook’s big bet on Facebook
M.
Really we shouldn’t be asking ourselves what our mobile strategy is anymore. We should be
wondering what our desktop strategy is given most of what our customers do is mobile?
So if you think you are mostly done with mobile then think again.
Some mobile questions that should be on your mind for 2016:
• How might our brand be present in the notifications stream? What is a good notifications
experience and how might we deliver smarter notifications?
• What could the trend towards conversational interfaces and bots mean for our brand?
• How do we capitalise on message and mobile-social commerce?
• What will the changes in mobile payment options (including Apple Pay roll out) mean for us?
• Following Google’s “Mobilegeddon” algorithm update last year what do we need to be doing in
SEO for mobile this year?
• Now that native apps are being indexed for search what opportunities does that give us?

Babelfish Articles Jan-Sep 2016 12-09-16 final

Babelfish Articles Jan-Sep 2016 12-09-16 final

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