SAN FRANCISCO – A trend that has been taking shape for several years has emerged this week in the forefront of Google Marketing Live, the company's annual conference for advertisers. L & # 39; initiative? Types of automated campaigns showing ads on multiple Google properties.
What started with universal application campaigns (now called campaigns) in 2017 to automate the delivery of application promotion ads and creative messaging across multiple Google properties has become the new Google model. Types of ads campaign.
Application campaigns are seen as the model for this approach, but if we go even further, Google's campaign type with its relatively short campaign type was launched in 2013 and used . An algorithm to extend search campaigns to GDN locations should work well for its low-budget advertisers – could be seen as the harbinger of the current situation.
The idea of doing search and display at the same time in a single campaign still thrills many advertisers. But most new types of campaigns do not give advertisers the opportunity to unsubscribe from the channel inventory. Google will say that it was a necessary tactic in a world powered by pre-machine learning. Machine learning may be a little overused, but it underlies almost every aspect of the campaign and will continue to grow in importance.
Where Search was once the center of AdWords, it only became one of Google Ads spokespersons.
One Campaign, Multiple Channels
Here is the latest summary of campaign types and ad formats that may (or will be) released on several Google properties:
] Campaigns Google announced last week to I / O that app campaigns could now be streamed to YouTube – in YouTube's RSS feed and in video inventory in stream – in addition to Search, GDN, YouTube, AdMob and Google Play. Smart Campaigns launched in June 2018, it was the first new campaign solution under the Google Ads brand. Designed for small businesses, ads are shown on Google.com, Google Maps, and the Google Display Network (GDN). Local Campaigns Introduced in 2018. Ads are shown on Search, YouTube, Maps, and GDN. Last week, Google announced a new inventory in Maps for Local campaigns. The Discovery Campaigns announced this week will be launched later this year (read our coverage of new Discovery Announcements). Announced on Tuesday, Discovery campaigns will show on the YouTube home feed, Gmail and Google Discover social media promotions and tabs on mobile, the content on Google's home page. Google has been testing ads in Discover for several months. Showcase Shopping ads launched in 2016. These multi-image Shopping ads on Search, announced this week, will soon be extended to Google Images, YouTube and Google Discover, Google said Tuesday. Shopping campaigns. The standard PLA formats have been available in Google Images since 2016. As with Showcase Shopping ads, these ads will also appear on YouTube and Google Discover starting the week of July 15, 2019, when you opt in to the network. research. Google Shopping Actions launched in 2018. Shopping ads allowing users to buy products via Google Universal Validation through the Google Shopping Actions program can already surface with Google Assistant and Search. Soon, their ads will also appear on Images and YouTube.
From the last click to the customer journey campaigns
These new solutions are not really called customer journey campaigns, but it's the case of Google: it can offer marketers full coverage to reach potential customers, from discovery to discovery. sale.
Research had long been considered as a bottom of the funnel channel. This was partly due to measurement limitations and Google has been encouraging marketers for years to go beyond the last click to boost investment in top-funnel search engine marketing. This model ceased to be the default AdWords campaign award template in 2016.
I asked questions about this passage from one One channel campaign to a fully multichannel channel at a press conference with Google executives on Monday. Sissie Hsaio, vice president of mobile ads, said the change was driven by two factors. The first is obviously that Google has access to many surfaces where people are in different modes of intention and discovery, said Hsaio.
"It makes it easier to reach consumers with different ways of thinking," Hsaio said. is the ability of machine learning to search for users and customize messaging and authoring assets based on these intent modes. Hsaio concluded that these two concepts come together and are applied to meet the different needs of advertisers and users.
Beyond the research intent, more. The keyword research intent was the original monetary signal that made the success of Google search ads. There was no better signal of intent, until Facebook publishes an audience targeting based on the centers of interest, the activity on the Web and applications, demographics and other signals and algorithms that can match the advertisements to these signals. Google has rapidly moved from keyword targeting to supporting various types of audience targeting that incorporate a range of interests and behavioral signals captured in its properties. Intention remains the core of the search, but Google has removed keyword targeting controls (and others to come), and it's quite possible to launch search campaigns based on keywords. Other signals and no keyword.
Previously, the signals consisted of two to three word search queries, "said Prabhakar Raghavan, Google's senior vice president of ads and commerce, when I told him about this change on Tuesday in a interview. "The click was Nirvana." Marketers have become more sophisticated, he said, and machine learning has progressed to be able to assign intent to different phases of the funnel.
Anticipating the needs of consumers. Allan Thygesen, president of Google America, said the omnichannel approach will help marketers "predict" where their users will be, what they will look for, what questions they will ask and what problems they will try to solve. The attribution may never be perfect, but there are enough directional measures that can be combined to help marketers better anticipate the needs of consumers in order to create better complete funnel strategies. "It's a change as deeply disruptive as it is mobile," Thygesen said.
Measurement and Confidentiality
"The perfect attribution to multitact is not yet a reality, but we should not let perfect be the enemy of good," said Thygesen . Google's measurement efforts have been complicated by GDPR and CCPA regulations and the potential for federal regulation in the United States, on which Google actively campaigns to influence.
Philipp Schindler and Thygesen, general manager of business at Google optimistic and optimistic, Google is getting closer to more efficient solutions, but some expectations have been defined.
"We all have an interest in protecting privacy so we may need more time to deliver the tools you need," Schindler said. "Doing this is very difficult even for the best data scientists in the world."
Raghavan said that he was encouraged by many developments related to computing progress in the cloud. Ads Data Hub, he noted, "although you can think of it as a platform, there are elements that come together that allow us to form calculations that are related to attributions without exchange data. And I think it's a huge technical progress.
Google has hammered the privacy message. In part, the company's tarnished reputation for privacy is due to the fact that it is not more open about how it has thoughtfully addressed data segmentation for years. "Data richness is really used to personalize consumer experiences, far more than the small fraction used for advertising," said Raghavan.
He tries to distinguish between what Schindler has described as a commitment to offer. "Total visibility" for marketers while protecting the privacy of users.
Raghavan said, "What we think the hardest here is how to get that level of click modeling and consumer conversion behaviors without compromising user trust. "Conversion modeling is underway for users who choose not to track their account settings or block cookies. In no way does it show marketers the ratio of modeled conversions to assigned conversions.
About the Author
Ginny Marvin is the editor-in-chief of Third Door Media and manages the daily editorial operations of all of our publications. Ginny writes on paid online marketing topics, including paid search, paid social networks, targeted posting and retargeting for Search Engine Land, Marketing Land and MarTech Today. With over 15 years of marketing experience, she has held senior management positions in both in-house and agency management. It can be found on Twitter under the name of @ginnymarvin.