Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

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

493 views

Published on

Sharing a collection of articles that I found interesting over the last 6 months - First 20 are important reading for those who can´t afford to tread water.

Published in: Marketing
  • Be the first to comment

  • Be the first to like this

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

  1. 1. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 1 Articles #14 Jan- Sep 2016 Brian Crotty Babelfish.Brazil@gmail.com
  2. 2. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 2 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
  3. 3. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 3 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
  4. 4. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 4 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
  5. 5. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 5 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
  6. 6. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 6 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
  7. 7. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 7 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.
  8. 8. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 8 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.
  9. 9. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 9 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:
  10. 10. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 10 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.
  11. 11. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 11 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.
  12. 12. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 12 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.
  13. 13. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 13 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
  14. 14. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 14 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
  15. 15. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 15 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).
  16. 16. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 16 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.
  17. 17. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 17 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.
  18. 18. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 18 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."
  19. 19. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 19 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
  20. 20. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 20 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."
  21. 21. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 21 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."
  22. 22. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 22 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.
  23. 23. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 23
  24. 24. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  25. 25. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 25 "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”).
  26. 26. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  27. 27. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  28. 28. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  29. 29. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  30. 30. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 30 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)
  31. 31. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 31 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
  32. 32. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 32 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
  33. 33. Babelfish Articles July 2015-Dec 2015 10-12-15 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 Gartner, Inc. or its affiliates. This publication may not be reproduced or distributed in any form without Gartner's prior written permission. If you are authorized to access this publication, your use of it is subject to the Usage Guidelines for Gartner Services posted on gartner.com. The information contained in this publication has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information and shall have no liability for errors, omissions or inadequacies in such information. This publication consists of the opinions of Gartner's research organization and should not be construed as statements of fact. The opinions expressed herein are subject to change without notice. Gartner provides information technology research and advisory services to a wide range of technology consumers, manufacturers and sellers, and may have client relationships with, and derive revenues from, companies discussed herein. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner's Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see "Guiding Principles on Independence and Objectivity."
  34. 34. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 34 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.
  35. 35. Babelfish Articles July 2015-Dec 2015 10-12-15 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
  36. 36. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  37. 37. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 37 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.
  38. 38. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  39. 39. Babelfish Articles July 2015-Dec 2015 10-12-15 Page 39 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
  40. 40. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  41. 41. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  42. 42. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  43. 43. Babelfish Articles July 2015-Dec 2015 10-12-15 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.
  44. 44. Babelfish Articles July 2015-Dec 2015 10-12-15 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?

×