Google unveiled three new machine learning-powered tools to help advertisers better reach consumers across devices and channels, in advance of Google Marketing Next.
Google has a new tool to better personalize ads and analyze their success: Machine learning. This technology represents a growing trend for advertisers that will shape successful campaigns into the future, according to a Tuesday blog post by Sridhar Ramaswamy, Google's senior vice president of ads and commerce, published ahead of the Google Marketing Next event in San Francisco.
"This technology is critical to helping marketers analyze countless signals in real time and reach consumers with more useful ads at the right moments," Ramaswamy wrote in the post. "Machine learning is also key to measuring the consumer journeys that now span multiple devices and channels across both the digital and physical worlds."
The blog post included three key announcements from Google:
1. Google Attribution
Google Attribution is a new product that helps marketers determine if their campaigns are actually working, taking into account data from all devices and channels that a consumer may use. It integrates with AdWords, Google Analytics, and DoubleClick Search, to more easily bring together marketing data. "The end result is a complete view of your performance," Ramaswamy wrote in the post.
The tool uses machine learning to determine each step in the customer's journey, from the first time they come across your brand to the moment before purchase. Known as data-driven attribution, this process analyzes your account's individual patterns, and compares customers who make a purchase to those who don't, so you can more accurately tailor your messaging.
As ZDNet's Liam Tung noted, this basically gives search advertisers the ability to match in-store credit card purchases with its online ads, to prove that the technology is effective.
Google Attribution also integrates with AdWords and DoubleClick search, so that results are immediately available for reporting and making changes.
Google Attribution is currently in beta, and will be released to more advertisers over the coming months, the post stated.
2. Mobile marketing innovations
As more customers use Google.com and Google Maps to find stores, products, and services, marketers are using Promoted Places and local inventory ads to inform people of special offers. Google is now adding the ability to help customers find a store from a YouTube video ad, using location extensions.
Advertisers using Google's store visits measurement—which helps marketers track customers who journey from online into the store—have seen over 5 billion store visits globally using AdWords since its introduction in 2014, the post stated. Now, Google is upgrading the technology with machine learning models and mapping tools to more accurately measure store visits at scale, and use them to better tailor local ads. This technology will allow advertisers to track visits in multi-story malls or highly populated cities like Tokyo and São Paulo.
The store visits tool is currently available for Search, Shopping, and Display campaigns. Soon, marketers will be able to access it for YouTube TrueView campaigns, to help measure the impact of video ads on foot traffic to brick and mortar stores.
Google is also releasing a store sales measurement tool at the device and campaign levels, to better measure in-store revenue along with the store visits delivered by Search and Shopping ads.
By including store sales, Virgin Holidays said that its search campaigns generated double the profit, as opposed to looking at online KPIs alone. "Store sales measurement gives us a more accurate view of the impact our digital investment has on in-store results, especially through mobile," said James Libor, performance marketing and technology manager, in the blog post.
3. Machine learning tools for more search ad effectiveness
Google is introducing in-market audiences to its Search feature, to help marketers better target customers who are ready to purchase their products and services. In the post, Ramaswamy gives the example of a car dealership increasing its reach by better targeting users who have already searched for "SUVs with best gas mileage" and "spacious SUVs."
"In-market audiences uses the power of machine learning to better understand purchase intent," Ramaswamy wrote in the post. "It analyzes trillions of search queries and activity across millions of websites to help figure out when people are close to buying and surface ads that will be more relevant and interesting to them."
Other announcements from Google are forthcoming at Google Marketing Next, which you can watch Wednesday May 24 at 9:00 a.m. PT/12:00 p.m. ET here.
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