Email is one of the most direct ways for organizations to reach their audiences on a 1:1 basis, which means that it is a rich source of information for research and new product development.
Read more at PPCHero.com
Hero Conf Philly is Tuesday, April 23 – Thursday, April 25 and includes two full, action-packed days of sessions and a 3rd day of workshops. You’ll see a variety of speakers; top-rated veterans that have roamed the world offering up valuable tip and tricks, as well as the newest up-and-comers in the digital marketing landscape.
Read more at PPCHero.com
Google Cloud already powers some of the world’s premier companies and startups, and now it’s poised to put even more pressure on cloud competitors like AWS with its newly-released products and services. TechCrunch’s Frederic Lardinois will be on the ground at the event, and Ron Miller will be covering from afar. Thursday at 10:00 am PT, Frederic and Ron will be sharing what they saw and what it all means with Extra Crunch members on a conference call.
Tune in to dig into what happened onstage and off and ask Frederic and Ron any and all things cloud or enterprise.
To listen to this and all future conference calls, become a member of Extra Crunch. Learn more and try it for free.
At the ripe old age of 20, Google is synonymous with internet search. The famous Silicon Valley brand long ago became a verb.
Google Chrome remains the most popular web browser, leading on most mobile and desktop devices with more than 60 percent share across both platforms. It’s four times more popular than rival browsers.
In the U.S. alone, Google raked in about $ 34 billion in ad dollars tied to its dominant internet search business, per eMarketer.
With all its success and R&D spent to improve its search capabilities, it is surprising what a poor job Google and its core video offering, YouTube, do in two key areas of top importance to advertisers around the globe: search personalization and brand safety.
Just this week, YouTube once again became a shining example of what advertisers are desperately trying to fix: avoiding ad placements next to brand-inappropriate or dangerous content.
Google’s brand safety assurance is not fully baked yet
YouTube’s latest brand-safety debacle was sparked by a 20-minute video that has been viewed nearly 2.5 million times since Sunday.
Blogger Matt Watson said the comments sections on some YouTube posts that featured videos of girls performing things like gymnastics and yoga were being exploited by a “soft-core pedophilia ring.”
The videos were being time-stamped with minors in compromising positions and ads from companies like Disney and Nestle were being served up next to them. Unfortunately, YouTube’s recommendation engine was collecting and serving up more similar videos with associated ads being viewed and interacted with by pedophiles.
The outrage and furor over Watson’s discovery has caused major advertisers like AT&T, Disney, Epic Games and Nestle to pull advertising from YouTube as a result.
In response, earlier this week, YouTube has removed more than 400 channels amidst its latest child exploitation crisis.
However, significant brand damage and revenue loss for YouTube has been inflicted. A lack of faith in Google’s search algorithms and its brand-safety assurance is in the spotlight again following similar incidents that have occurred since 2017.
Brand safety concerns on YouTube
Following these well-publicized crises like YouTube’s most recent one, advertisers have grown increasingly concerned about ads appearing in brand-safe environments, especially on social-media platforms such as Google’s YouTube and Facebook.
A survey of more than 300 advertising decision-makers conducted by Oath, a Verizon company, last spring found that 99 percent of advertisers are concerned with their ads appearing in brand-safe environments. And 58 percent of them were more concerned than previous year.
A more recent study conducted by Teads found that “brand safety is keeping CMOs up at night.” Eight in 10 said that they’re more concerned with avoiding placement of ads next to brand-inappropriate content than ever before. It’s an issue that’s weighing heavily on the global digital ad industry that is now valued at more than $ 628 billion.
Ad platforms’ responses to protect brands
In response to advertisers’ concerns, major ad platforms have been adding more safeguards to avoid embarrassing and ineffective ad placements next to inappropriate content.
For example, Facebook rolled out new capabilities to exclude advertisements from predetermined categories such as conflict, gambling, guns, immigration, religion and tragedy. Google Ads offers some limiting functionality, but it is not as granular as what Facebook offers advertisers today.
Last month, new third-party software solutions from Integral Ad Science (IAS) and DoubleVerify were released to give YouTube advertisers more assurance that their video ads will appear next to brand-suitable content. This type of software is designed to reduce incidents of ads from tech giants, retailers, government agencies and media companies running alongside YouTube channels promoting controversial topics such as conspiracy theories, Nazis, North Korean propaganda and white nationalists, a trend reported on by CNN last April.
Tech giants like Google turn to artificial intelligence to improve ad effectiveness
The new software from IAS and DoubleVerify to improve brand-safety assurance on YouTube incorporates machine learning to create models for determining ad appropriateness.
Similarly, last year, Google launched new features with machine-learning technology – including a new service called AdSense auto ads that helps publishers improve monetization and ad placement. Google claims the relatively new feature ensures that ads will be displayed when they’re likely to perform and provide a good user experience.
Publishers who participated in the beta saw and average lift of 10 percent with revenue increasing ranging between five to 15 percent.
However, the personalization capabilities from Google to improve ad efficiency are not as good as they should be for publishers or advertisers.
How does current Google Ads personalization stack up?
As an example for the latter, I’ll cite a story about a good friend’s recent experience with Google Ads. A small business owner, he runs a local plumbing business in Milwaukee. He spent hundreds of dollars on an ad campaign a few months back to increase incoming business leads using Google Ads.
Google’s auto-generated keywords for the campaign it scraped from his landing page were not relevant, especially in terms of geo-targeting for a local plumbing business. His website traffic went way up, but he did not gain one qualified sales lead as a result of the campaign. It was a dismal failure for him.
How much will deep learning improve it?
Many industry experts view deep learning as the Holy Grail for “changing the game for both advertisers and consumers.” According to a ClickZ story by Daniel Surmacz: “Deep learning is changing the way we think about effectiveness. It’s the most promising field of AI-based research found in Google Translate and Tesla self-driving cars.”
Without an ability for machine learning AI-powered platforms to “think on their feet” like human neural networks, many don’t have the same speed and efficiency-drivers that deep learning provides. It’s simply not possible for machine-learning AI engines to act like personal shoppers and cross-sell relevant items to consumers without deep learning’s more highly advanced algorithms.
Unless Google improves its personalization and brand-safety capabilities, it stands to lose more market share to others, most notably Amazon.
The share of new ad dollars has been on the decline for the longtime duopoly of Google and Facebook compared to two years ago. Amazon, a master of personalization and controller of its own walled garden, has emerged as a search advertising powerhouse and it’s on track to generate more than $ 10 billion in ad revenues over the next year.
Gary Burtka is vice president of US operations at RTB House, a global company that provides retargeting technology for global brands worldwide. Its North American headquarters are based in New York City.
Since its inception back in 2007, Facebook Ads has changed the way companies approach their online advertising strategies. Early on, many advertisers have tried and failed with Facebook Ads NOT because they were targeting the wrong audience, but because they did not fully understand the dynamics of this (non-search like) Ad platform. The confusion (still today) is due to the enormous traffic volume of users (which many of them disclosed their likes, interests, age, sex, race, political views, education, marital status, household income, etc…) that are skewing the overall performance which forces many advertisers into believing that Facebook is a scam. In this post, I will try to reinforce the notion that Facebook Ads can be successful for advertisers if they approach their strategies on a more micro-targeted level.
Over the years, marketers (like myself) started to change the methodologies of campaign structures just like we did with Google to obtain a good Quality Score. In March of 2014, Facebook rolled out a bunch of new features which seemed to model that of Google Adwords. Some of these updates included:
- Self-serve ad tool, Ad Sets, Ads Manager, Power Editor, 3rd party interfaces
Even before the adoption of Ad Sets, marketers started to realize that in order to “offset” the huge traffic volume and identify what was working and not working, they needed restructure everything at a Micro-level. This strategy of creating individual campaigns for each specific interest is what empowered many to re-think their expectations of what Facebook could do for them.
Below is a quick example of a standard Facebook Ads campaign that focuses on one specific audience. As you can see, we are focusing on Green Tea only (not Tea Drinkers in general). We are also segmenting Women-only as well as different Age Ranges which allows for a more granular understanding of interest and interaction.
#1 Why Micro-Targeting Works
In order to get the most out of your Ad dollars as well as identify winners and losers, micro-targeting is a must for every advertiser. Yes, it’s a lot of work and yes it requires many hours to set it up correctly. However, not investing in this time could cost you even more later down the line because all of the work that was done, can be utilized again in the future with little to no effort to update.
#2 Facebook Ads Creates Storytelling
Wouldn’t it be a great story to tell your CEO or client (Tea Company) that the majority of the FB conversions came from Single Women, 35-40, who live in Baltimore MD, and enjoy Pilates and Yoga. That specific piece of information was made possible by the micro-targeting created in Facebook Ads and quite possibly created a whole new level of both online and offline marketing strategies for years to come.
#3 Geo-Targeting Matters:
As mentioned in the storytelling example above, geography is a huge proponent of micro-targeting because of the different social behaviors that surround us. For example, advertisers that are interested in reaching a younger audience (25-35) that enjoy nightclubs and dancing, would be more likely to choose to target their ads in USA cities such as NYC, Miami, Las Vegas, LA, and Chicago instead of other locations that are not as likely to be interested.
#4 The Power of Indirect Targeting:
Lets assume that avid Tea Drinkers are also more likely to be fans of the Food Network and other TV cooking shows. With Facebook Ads, we have the ability to create individual campaigns targeting not only the Food Network, but also specific shows such as Man vs. Food, Barefoot Contessa and others… The fact that we can create TEST campaigns to see if those “in-direct” yet similar audiences could convert is a game-changer in all aspects of marketing.
#5 Why Timing Matters:
We are constantly being bombarded by news everyday coming from TV, radio and the internet. However, the one thing that is NOT constant is the “shelf-life” of the news story and that is where Facebook Ads (including all Social Media) provides a unique advantage for advertisers. For example, lets say the FDA (Food & Drug Administration) comes out with a study that says people who drink 2-3 cups of Green Tea everyday have a better chance to fight the symptoms of the common cold. This report obviously not only shines a positive light on the Tea Industry but it’s also fresh in everyone’s mind and when they see an ad for Green Tea in their Facebook Feed, they are likely to remember that news story about the health benefits and are more inclined to make an impulse buy.
Truth be told, Facebook Ads may not be a fit for everyone. While certain industries may thrive on having a social-friendly presence, many others will not find their target audience in that social environment. However, I implore that all advertisers/marketers to keep an open-mind when looking at Facebook Ads because there is more strategy potential than you think. In my opinion, FB Ads has become more a testing ground than a standard vehicle for website traffic. Facebook Ads may not be a GEM for everyone, but with an open-mind it could be a diamond in the rough.
Former Uber CEO Travis Kalanick may have been nudged out of one of the world’s most highly valuable private companies by investors frustrated over its troubled culture, but his moves remain of great interest given how far he’d driven the ride-share giant.
One such move, according to a new report in the South China Morning Post, looks to be to help foster the growing concept of cloud kitchens to China.
We’ve reached out to Kalanick for more information, but per the SCMP’s report, Kalanick is partnering with the former COO of the bike-sharing startup Ofo, Yanqi Zhang. Their apparent project involves Kalanick’s L.A.-based company, CloudKitchens, which enables restaurants to set up kitchens for the purposes of catering exclusively to customers ordering in, as that’s how a growing percentage of people is consuming restaurant food. (More on the movement here.) The kitchens are established in underutilized real estate that Kalanick is snapping up through a holding company called City Storage Systems.
According to The Spoon, a food industry blog, the trend is beginning to gain momentum in particular regions, including India, where it says many restaurants struggle to afford the traditional restaurant model, which often involves paying top dollar for rent, as well covering wages for employees, from dishwashers to cooks to servers. Using so-called cloud kitchens enables these restaurateurs to share facilities with others, and to do away with much of their other overhead.
Some are even being promised more affordable equipment. For example, according to The Spoon, the restaurant review site Zomato, through its now two-year-old service called Zomato Infrastructure Services, aims to create kitchen “pods” that restaurants can rent, and it’s using data to identity recently closed restaurants that may be looking to offload their kitchen equipment for whatever they can get for it.
Shared kitchens have also been taking off in China, as notes the SCMP, which cites Beijing-based Panda Selected and Shanghai-based Jike Alliance as just two companies that Kalanick would be bumping up against.
Kalanick wasn’t the first here in the U.S. to spy the trend bubbling up, but he seems to be taking it as seriously as any entrepreneur. Last year, he spent $ 150 million to buy a controlling stake in City Storage Systems, the holding company of CloudKitchens, through a fund that he established around the same time, called the 10100 fund. The money was used to buy out most of the company’s earlier backers, including venture capitalist Chamath Palihapitiya, according to a report last year by Recode.
That same report said that Kalanick now has a controlling interest in City Storage Systems. It also said that serial entrepreneur Sky Dayton — who previously founded EarthLink, co-founded eCompanies, and founded Boingo — is a cofounder.
City Storage Systems isn’t interested in on-demand kitchens alone, reportedly. The idea behind it is to buy distressed real estate, including parking lots, and to repurpose it for a number of online-focused ventures.
While the China twist looks like a new development, it wouldn’t be a wholly surprising move. Having had to back out of China with Uber in 2016, Kalanick may be of a mind to jump into the country faster this time around, and with a local partner with whom he has a relationship. Indeed, Zhang spent two years as a regional manager for Uber in China before cofounding Ofo, which has since run into problems of its own.
We’ve also reached to Zhang for this story and hope to update it when we learn more.
The company hopes to do for podcasts what its Music Genome Project did for streaming songs.
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With long summer evenings comes the perfect opportunity to dust off your old boxes of circuits and wires and start to build something. If you’re short on inspiration, you might be interested in artist and engineer Dan Macnish’s how-to guide on building an AI-powered doodle camera using a thermal printer, Raspberry pi, a dash of Python and Google’s Quick Draw data set.
“Playing with neural networks for object recognition one day, I wondered if I could take the concept of a Polaroid one step further, and ask the camera to re-interpret the image, printing out a cartoon instead of a faithful photograph.” Macnish wrote on his blog about the project, called Draw This.
To make this work, Macnish drew on Google’s object recognition neural network and the data set created for the game Google Quick, Draw! Tying the two systems together with some python code, Macnish was able to have his creation recognize real images and print out the best corresponding doodle in the Quick, Draw! data set
But since output doodles are limited to the data set, there can be some discrepancy between what the camera “sees” and what it generates for the photo.
“You point and shoot – and out pops a cartoon; the camera’s best interpretation of what it saw,” Macnish writes. “The result is always a surprise. A food selfie of a healthy salad might turn into an enormous hot dog.”
If you want to give this a go for yourself, Macnish has uploaded the instructions and code needed to build this project on GitHub.
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