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. 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.

Google LLC has unveiled a new suite of tools for marketers that leverage its latest developments in machine learning, a subset of artificial intelligence that mimics the way the human brain works. The idea is to help marketers create and place better optimized and therefore more effective advertisements on its platforms. First up is the new Local Campaigns service, which relies on machine learning to encourage more users to visit brick-and-mortar stores by optimizing ad placement so they show up when they perform a search for nearby locations. The company said Local Campaigns can also be used to gauge how effective these ads are at driving store visits by using autonomous and aggregated data from users who're signed in to Google and have their location history switched on. Google Vice President of Product Management Jerry Dischler wrote in a blog post that Local Campaigns should be useful as the majority of consumers still prefer to buy items in physical stores as opposed to buying online.

Spotify and TGI Fridays are hooking up with Foursquare as a preferred measurement partner. Solid measurement is what seals the deal with marketers, said Brian Berner, head of US sales at Spotify. "Many of our [brand] partners have a brick-and-mortar presence, so we've seen increased demand for measurement that showcases how our ad platform connects to consumer behavior in the real world," he said. The partnership with Foursquare, announced Thursday, is part of Spotify's effort to help advertisers understand how their ad spend is driving results by making a "connection between our streaming intelligence and offline behavior," Berner said. To meet that industry-wide need, Foursquare has improved attribution with machine learning.

If we told the average person in early 2013 that someday it was going to be very important to learn the correct way to greet your devices, the average person might have thought we'd gone mad. It wasn't that people didn't love their gadgets in the distant wilds of five years ago; nor did the idea of talking to a digital intelligence sound completely outside the realm of normal experience. In 2013, the world had been acquainted with Apple's Siri for almost two years, and Google's first crack at a smart, voice-activated assistant, "Google Now," was released in mid-July 2012. But the idea of voice-activated artificial intelligence (AI), capable of fulfilling more than very simple commands -- and, in fact, being able to "converse" in real-time with a human, recognize a user's voice through biometrics and develop more skills over time so it could gradually "learn" to do better -- seemed literally the stuff of science fiction or superhero movies. The idea that there would not only be that type of AI in the market, but that there would be so much of it out there that users would need to learn a variety of different "wake" commands to initiate conversation with their devices?

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." 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.

Google is announcing a major update to its store visits measurement tool today at its Google Marketing Next conference. Google has used anonymized location and contextual data since 2014 to estimate brick and mortar store visits spurred by online ads. The company is augmenting its existing models with deep learning to bring insights to even more customers. Omnichannel marketing is as big of a buzzword as they come. As obnoxious as the term is, the problem it underscores is a serious one for marketers.