Pay Per Click News
Last week at the Consumer Electronics Show, we learned about today’s more empowered consumer. They’re more curious, demanding and impatient than ever before, and expect assistive experiences everywhere–like checking in and unlocking their hotel room using their smartphone.
Meeting these rising consumer expectations is critical. Over the next two weeks, we’ll explore some of our favorite AdWords products and show how machine learning is enabling brands to meet those expectations, while saving time and improving performance.
Applying machine learning in AdWords
Campaign management involves time-consuming tasks. Rather than manually adding thousands of keywords or individually testing headlines to see which ones work best, you can train Google’s machine learning platform to do it for you.
For example, you might’ve had new products added to your inventory or more content added to your website recently. Dynamic Search Ads would see this and automatically fill gaps in keyword coverage to help you reach people who are searching for those new products and services.
Or to show relevant ads that fit anywhere across the millions of sites in the Google Display Network, you can upload more creative assets to your Smart display campaign and automatically show relevant ads to the right people. Machine learning makes all of this possible.
Changing the app game
For app developers and marketers, we know competition is fierce: the number of developers with more than 1 million monthly installs grew by 35% year over year.1 There are more apps and experiences competing for your users’ attention and dollars than ever before. This is another area where machine learning is changing the game.
Universal App campaigns (UAC) enable brands like Rappi, a delivery service in Latin America, to reach their most valuable users across Google Play, Search, Display Network, and YouTube with a single campaign.
Rappi uploaded as many creative assets as it had, allowing Google’s machine learning platform to rotate each asset, understand which ones perform best across each channel, and show the ads that users are most likely to engage with. After only one month, Rappi’s conversion rates grew by 10X, and the brand expanded into Brazil, Mexico and Argentina.
AutoGravity, an auto financing company, reached tens of thousands of car buyers and increased user engagement by 120% in only 5 weeks. The brand plans on increasing UAC investment by 200% to reach more of its highest-value users, people who are most likely to receive credit ‘approval’.
How does UAC reach these types of high-value users? Google’s machine learning platform uses insights from Google.com and Google Play, web data and other signals, in addition to information about your app. This data is analyzed across each channel where AdWords shows your ads and is updated in real time. That’s how AdWords can quickly pick up on trending keywords, like events and holidays, and ensure your ads show to the right users.
AdWords then looks at people who have completed your selected action, like ‘approvals’, and those who haven’t, as well as user signals that are unique to each auction. Device type, operating system, network, apps they already have, and other signals create patterns that help identify high-value users. These patterns are used to predict future auctions, where and how to bid, and what ads to show and to whom.
Using machine learning, brands are not only delivering better performance at scale, but they’re also unlocking their most precious resource: time.
Paul Teresi, Growth Executive at Skyscanner, a travel app, says he’s been able to save a lot more time thanks to UAC. “Now, I can focus on truly understanding our users, metrics, and discovering growth and expansion opportunities necessary to keep us ahead of the curve.”
To learn more about how Universal App campaigns can help you reach your most valuable users, take our new education course.
Next week, we’ll conclude our journey with a look at how machine learning is being applied to bid optimization, including an interesting case study from Google’s in-house media team.
Posted by David Mitby, Director of Product Management
1. Google Internal Data, May 2017
Today, we’re launching a new interactive education program for Universal App campaigns (UAC). UAC makes it easy for you to reach users and grow your app business at scale. It uses Google’s machine learning technology to help find the customers that matter most to you, based on your business goals—across Google Play, Google.com, YouTube and the millions of sites and apps in the Display Network.
UAC is a shift in the way you market your mobile apps, so we designed the program’s first course to help you learn how to get the best results from UAC. Here are a few reasons we encourage you take the course:
- Learn from industry experts. The course was created by marketers who’ve been in your shoes and vetted by the team who built the Universal App campaign.
- Learn on your schedule. Watch snackable videos at your own pace. The course is made up of short 3-minute videos to help you master the content faster.
- Practice what you learn. Complete interactive activities based on real life scenarios like using UAC to help launch a new app or release an update for your app.
Happy New Year and hope to see you in class!
Posted by Sissie Hsiao, VP of Product, Mobile App Advertising at Google
There’s no denying 2017 was a difficult year, with several issues affecting our community and our advertising partners. We are passionate about protecting our users, advertisers and creators and making sure YouTube is not a place that can be co-opted by bad actors. While we took several steps last year to protect advertisers from inappropriate content, we know we need to do more to ensure that their ads run alongside content that reflects their values. As we mentioned in December, we needed a fresh approach to advertising on YouTube. Today, we are announcing three significant changes.
Stricter criteria for monetization on YouTube
After careful consideration and extended conversations with advertisers and creators, we’re making big changes to the process that determines which channels can run ads on YouTube. Previously, channels had to reach 10,000 total views to be eligible for the YouTube Partner Program (YPP). It’s been clear over the last few months that we need the right requirements and better signals to identify the channels that have earned the right to run ads. Instead of basing acceptance purely on views, we want to take channel size, audience engagement, and creator behavior into consideration to determine eligibility for ads.
That’s why starting today, new channels will need to have 1,000 subscribers and 4,000 hours of watch time within the past 12 months to be eligible for ads. We will begin enforcing these new requirements for existing channels in YPP beginning February 20th, 2018.
Of course, size alone is not enough to determine whether a channel is suitable for advertising. We will closely monitor signals like community strikes, spam, and other abuse flags to ensure they comply with our policies. Both new and existing YPP channels will be automatically evaluated under this strict criteria and if we find a channel repeatedly or egregiously violates our community guidelines, we will remove that channel from YPP. As always, if the account has been issued three community guidelines strikes, we will remove that user’s accounts and channels from YouTube.
This combination of hard-to-game user signals and improved abuse indicators will help us reward the creators who make engaging content while preventing bad actors and spammers from gaming the system in order to monetize unsuitable content. While this new approach will affect a significant number of channels eligible to run ads, the creators who will remain part of YPP represent more than 95% of YouTube’s reach for advertisers.
Those of you who want more details, can find additional information in our Help Center.
Manually reviewing Google Preferred
We’re changing Google Preferred so that it not only offers the most popular content on YouTube, but also the most vetted. We created Google Preferred to surface YouTube’s most engaging channels and to help our customers easily reach our most passionate audiences. Moving forward, the channels included in Google Preferred will be manually reviewed and ads will only run on videos that have been verified to meet our ad-friendly guidelines. We expect to complete manual reviews of Google Preferred channels and videos by mid-February in the U.S. and by the end of March in all other markets where Google Preferred is offered.
Greater transparency and simpler controls over where ads appear
We know advertisers want simpler and more transparent controls. In the coming months, we will introduce a three-tier suitability system that allows advertisers to reflect their view of appropriate placements for their brand, while understanding potential reach trade offs.
We also know we need to offer advertisers transparency regarding where their ads run. We’ve begun working with trusted vendors to provide third-party brand safety reporting on YouTube. We’re currently in a beta with Integral Ad Science (IAS) and we’re planning to launch a beta with DoubleVerify soon. We are also exploring partnerships with OpenSlate, comScore and Moat and look forward to scaling our third-party measurement offerings over the course of the year.
The challenges we faced in 2017 have helped us make tough but necessary changes in 2018. These changes will help us better fulfill the promise YouTube holds for advertisers: the chance to reach over 1.5 billion people around the world who are truly engaged with content they love. We value the partnership and patience of all our advertisers to date and look forward to strengthening those ties throughout 2018.
Posted by Paul Muret, VP, Display, Video & Analytics
At the start of the new year, we take time to look at what’s ahead, from eating healthier to spending more time outdoors. This week at the Consumer Electronics Show, we get to take a similar look ahead, at the future of technology. Thanks to innovations like smartphones and voice-activated speakers, consumers are now super-empowered and expect more from their favorite brands. This is redefining the consumer experience and reshaping what’s required of marketers.
To help you meet rising consumer expectations, over the next three weeks we’ll share insights and best practices from brands that have made machine learning an enabler for new opportunities in this “age of assistance”–instead of another challenge to figure out.
Solving problems with machine learning
At its core, machine learning is a new way of problem solving. Rather than spending hundreds of hours manually coding computers to answer specific questions, we can save time by teaching them to learn on their own. To do that, we give the computer examples until it starts to learn from them–identifying patterns, like the difference between a cat and a dog.
To illustrate how machine learning can help solve some of the most complex problems in the world, take the latest advances in medicine. In the US, doctors know survival rates for skin cancer increase dramatically with early detection.1 That’s why researchers at Stanford University used Google’s machine learning platform, TensorFlow, to train a model that can identify cancerous skin conditions from healthy ones with 91% accuracy–on par with 21 board-certified physicians.
New opportunities to accelerate growth
As marketers, you don’t wake up everyday expecting to save lives. But we do ask ourselves a very different question: how can I grow my business faster? This is where Google’s machine learning technology can help.
We know that choosing where your ads show and manually adjusting bids is time consuming, leaving less time for strategic tasks, like capturing the latest trends or entering new markets. Google’s machine learning considers billions of consumer data points everyday, from color and tone preference on mobile screens, to purchase history, device and location. With products like Universal App Campaigns and Smart Bidding, it’s now possible to use this data to help deliver millions of ads customized for your customers, and set the right bid for each of those ads–in real time.
Even if you’re not using these AdWords innovations, you’re still seeing the benefits of machine learning. Google uses information about search queries, historical ad performance and other contextual signals combined with machine learning, to predict whether or not someone will click on your ad. This predicted click-through rate helps determine the selection, ranking and pricing of your ads–meaning machine learning is already working to show the right ads to the right customers.
Over the next three weeks, we’ll continue exploring how you can use machine learning to reach your marketing goals and grow your business faster. To get the latest updates on this series, follow along on the Inside AdWords blog or subscribe to our Best Practices newsletter.
Posted by Matt Lawson, Director of Performance Ads Marketing
1. Stanford News, 2017
With 2018 only weeks away, our team compiled a few AdWords New Year’s resolutions for you to consider.
1. I will try out new AdWords innovations.
The new AdWords experience is packed with new features like promotion extensions and ad variations that have helped advertisers improve performance. For example, Torrid saw a 30% lift in conversion rate when using promotion extensions to highlight limited time offers alongside ad copy that emphasized quality and fit. Merkle also increased conversions by 14% after running an ad variations test with expanded text ads. And new shortcuts like pressing “G” then “T” let you navigate to any page within your account so you can get to the data that matters to you, faster.
2. I will test more.
Testing in AdWords is crucial when optimizing your account. To increase return on ad spend (ROAS), the Honest Company used campaign drafts and experiments for efficiently exploring new strategies—saving 50% more time compared to manual trials. The Honest Company experimented with sending shoppers to product pages versus special offer landing pages for “bath” and “body” keywords. As a result of the test, the Honest Company saw a 47% increase in ROAS when sending shoppers to unique offer landing pages.
3. I will do more in less time.
Smart Bidding helps marketers bid both more efficiently and effectively. Powered by Google’s machine learning, it automatically sets the right bid for each and every auction. Bonprix, a leading fashion brand in Europe, drove 25% more revenue at the same ROAS and more than 50% in incremental revenue on mobile, by using Smart Bidding with Target ROAS. According to Sönke Harms, Bonprix’s Head of Shopping ads, Smart Bidding allowed the team to focus on “delivering key analyses, identifying strategic opportunities, and driving important initiatives.” Read our best practices guide to get started with Smart Bidding.
4. I will reach more shoppers.
Mobile searches for “where to buy” grew more than 85% over the past two years.1 That’s why it’s critical to help shoppers find your business both online and when they’re on-the-go. With location extensions, you can show your address, business hours, a map to your location, and more. You can also reach and bid higher specifically for people who are located near your business. Jerome’s Furniture combined location extensions with local inventory ads and store visits measurement to increase conversions by 93% across online and offline channels.
5. I will stay informed.
With the AdWords app, you can receive timely alerts notifying you of issues and opportunities in your account. You can also easily pause campaigns and adjust budgets and bids. Adding, editing, and removing keywords is also simple. Best of all, you can do all of this right from the palm of your hand. Download the app now on Android or iOS.
To receive more AdWords tips and tricks, be sure to subscribe to our Best Practices newsletter.
From our AdWords family to yours—happy holidays, and we’ll see you in 2018!
Posted by Karen Yao, Director of Product Management, AdWords
1. Source: Google Data, U.S., Jan.-June 2015 vs. Jan.-June 2017.
Would it surprise you to hear that we see 34% more shopping searches on Christmas Day than on Black Friday1? That’s just one of the eye-opening consumer trends we’re watching closely now that the 2017 holiday season is in full swing.
With mobile, shoppers know they can easily find and get what they’re looking for up until the last minute. So, despite all of the improvements retailers have made to shipping speed and product availability, many people still wait to buy. That means that a lot of December’s holiday shopping happens right before—and even after—Christmas, giving more reason for retailers to continue to drive store traffic from online and offline media throughout the season.
Early birds they are not
Retailers may be pushing their holiday deals earlier and earlier, but some shoppers are still waiting longer and longer, weighing their options to make their final choices.
When shoppers consider a new purchase, they spend 13 days on average shopping for the item. But once they decide to buy, almost half expect it either the same day or the next day2. In fact, mobile searches related to “same day shipping” have grown 120% since 20153.
It’s no wonder, then, that we see online conversions from the week before December’s shipping cutoff date on par with the the week of Cyber Monday4, as holiday shoppers make a last-ditch effort to get their presents sent to their doorstep.
Once shipping cutoff hits, last-minute shoppers make a mad dash
The last week before Christmas is crazy busy, of course, but it’s also very local. Around Dec. 21, when the online shipping cutoff passes, shoppers increasingly turn to their hometown stores to get what they need.
Regardless of which day of the week Christmas falls, the in-store holiday rush starts on the Friday one full week before Christmas. The Saturday after that is typically the second-busiest day of December. The busiest day of all in the last month of the year? That’s Dec. 23, regardless of what day of the week it falls on5.
Searches for “where to buy” peak on Dec. 23 as last-minute shoppers grab their final gifts and stocking stuffers. Some popular examples: “where to buy Cards Against Humanity?”, “where to buy Yeti Cups?”, and even “where to buy coal?”6
Meanwhile, mobile searches for “open now” and “store hours” grow through December and peak on Christmas Day. That includes searches like, “what stores are open near me on Christmas?”, “what grocery stores are open on Christmas?” and “what stores are open right now?”7
This year, retailers have an edge: With Christmas on a Monday, there are two full weekends (Dec. 15-17 and 22-24) in the 10 days before the holiday. This bodes well for store traffic with shoppers out in force on Fridays and Saturdays.
The takeaway? With people turning to stores at the last minute, be sure to highlight your local products for the best chance at drawing shoppers to your door. Check out our Shopping best practices guide to learn how you can drive traffic to your store this holiday season.
Christmas may be over, but the shopping isn’t
The days between Christmas and New Year’s Eve are just as busy as every other day in December (other than Christmas week itself). For general shopping queries (such as “shopping near me” or “store hours”), we see 34% more searches on Christmas Day than we do on Black Friday. Though searches for “where to buy” increase up until Dec. 23, the queries recover to pre-Christmas week levels and stay steady for the final week of the year8.
And this post-Christmas shopping busyness isn’t just happening online. In fact, last year we saw about 20% of all December store traffic happen in the six days after Christmas9. And why is that? With searches for “clearance” spiking on December 2610, shoppers are likely looking to redeem gift cards, make returns and exchanges, find gifts for people they haven’t seen yet, or decide to “gift” themselves a little extra.
While Black Friday is still a major in-store shopping day for some categories, such as electronics and furniture, many specialty stores see more foot traffic leading up to, and after, Christmas Day than on Black Friday. In 2016, toy stores and bookstores, for example, saw the most foot traffic of the holiday season on Dec. 23, while video game stores saw their busiest holiday shopping day on Dec. 2611.
Mobile has fundamentally changed the way holiday shoppers complete their lists. They expect to be able to find what they want, when they want it. And that means holiday shopping is happening right before—and even after—Christmas. That’s a big opportunity for marketers who keep the lights on even after Santa slides through.
For more holiday insights, be sure to check out Think with Google.
Posted by Emily Eberhard, Head of Shopping B2B Marketing at Google
1. Google Data, U.S., Nov.-Dec. 2016.
2. Google/Ipsos Fall Shopping Study, n=4,720, U.S., Sept. 2017, High Consideration Purchases.
3. Google Data, U.S., Jan.-June 2017 vs. Jan.-June 2015.
4. Google Analytics, Based on data from Google Analytics accounts that have authorized Google to share website data in an aggregate way, Shopping vertical only, Nov.-Dec. 2016.
5. Google Data, Aggregated, anonymized store traffic from a sample of U.S. users that have turned on Location History, U.S., Nov.-Dec. 2015 and 2016.
6. Google Data, U.S., Nov.-Dec. 2016.
7. Google Data, U.S., Nov.-Dec. 2016.
8. Google Data, U.S., Nov.-Dec. 2016.
9. Google Data, Aggregated, anonymized store traffic from a sample of U.S. users that have turned on Location History, U.S., Nov.-Dec. 2015 and 2016.
10. Google Data, U.S., Dec. 2016
11. Google Data, Aggregated, anonymized store traffic from a sample of U.S. users that have turned on Location History, U.S., Nov.-Dec. 2015 and 2016.