Google debuts a host of new ad formats powered by machine learning

The updates include responsive search ads, YouTube tools to measure brand lift and optimization geared to drive in-store visits

Ahead of today’s scheduled Google Marketing Live keynote, and just weeks after the rebrand of its advertising tool suite, the online advertising giant has unveiled a host of product updates.

These include: responsive search ad formats powered by machine learning; YouTube tools which can better measure marketer’s branding KPIs; plus new campaign formats designed to drive tangible business results such as customer acquisition and store visits, etc.

The announcements were made in a blog post by Jerry Dischler, Google, vice president of product management, where he discussed how machine learning is at the heart of all the latest updates, which are geared towards helping advertisers keep apace with the changes in how consumers are interacting with their devices.

The updates include:

  • Responsive search ads

These new ad formats use machine learning to help advertisers better optimize their campaign copy to match the best performing ad format for a particular search query.

“Simply provide up to 15 headlines and 4 description lines, and Google will do the rest. By testing different combinations, Google learns which ad creative performs best for any search query,” reads Dischler’s post. “So people searching for the same thing might see different ads based on context.”

  • Maximize lift for YouTube

This update (currently in beta) helps marketers optimize their YouTube advertising in a way that enables them to measure metrics beyond views and impressions, now it enables them to optimize their ad campaigns to boost brand lift.

“This new Smart Bidding strategy is also powered by machine learning. It automatically adjusts bids at auction time to maximize the impact your video ads have on brand perception throughout the consumer journey,” adds Dischler.

  • Local Campaigns

A new ad tool geared towards helping advertisers drive footfall to particular outlets, this new offering works by allowing media buyers to provide their budget, business locations and ad creative, and then Google’s machine learning does the rest.

“Whether they start their research on YouTube or Google, people still make the majority of their purchases in physical stores,” adds Dischler. “Provide a few simple things—like your business locations and ad creative—and Google automatically optimizes your ads across properties to bring more customers into your store [see image].”

  • Smart shopping campaigns

This new campaign type that uses machine learning to optimize performance across multiple business goals, such as revenue, acquiring new customers and driving visits to a store, using signals such as seasonality etc and price optimization to better place ads on Google Shopping.

“This Smart Shopping campaign helps you hit your revenue goals without the need to manually manage and bid to individual products or keywords. In the coming months, we’re improving them to optimize across multiple business goals,” adds Dischler.

“Beyond maximize conversion value, you’ll also be able to select store visits or new customers as goals. Machine learning factors in the likelihood that a click will result in any of these outcomes and helps adjust bids accordingly.

“Machine learning is also used to optimize where your Shopping ads show—on Google.com, Image Search, YouTube and millions of sites and apps across the web—and which products are featured.”

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