Why is Machine Learning important?
In 1959, Arthur Samuel – an IBM employee and a pioneer in computer gaming & AI, coined the term Machine Learning. What followed was a revolution in the tech world, as we began to prospect the potential of computers improving on their own, based on acquired experience and information.
This particular discipline or field of study & practice employs numerous approaches to help teach computers accomplish tasks where no completely-satisfactory algorithm has been created yet. If we encounter vast numbers of potential answers, one approach is to label some of the correct answers as valid. This is then used as training for the computer to improve the algorithm(s) to determine correct answers.
Today’s Machine Learning (or ML for short) has two primary goals:
- Classify data based on models which have been developed
- Make future predictions based on these models
How does it help a modern-day advertiser?
Improve consumer products and understand preferences
Well, the ways people get things done are constantly changing, from finding the closest coffee shop to organizing family photos. In 2018, Google explored how machine learning was used to improve our consumer products and help people get stuff done.
However, they wanted to go a step beyond that. Later that year, in July, they delivered a live stream presentation on how they want to help advertisers unlock more business opportunities with their largest deployment of machine learning in ads. During this showcase, they explored how this technology works in their products and why it’s key to delivering the helpful and frictionless experiences consumers expect from brands.
Deliver more relevance with responsive search ads
Not only do people want a buttery smooth experience when interacting with their favourite companies, they are also more curious, demanding, and they expect to get things done faster because of the advent of mobile. As a result, they expect your ads to be helpful and personalized. Doing this isn’t easy, especially at scale, and that’s why Google introduced responsive search ads. Responsive search ads combine your advertiser creativity with the power of Google’s machine learning to help you deliver relevant, valuable ads.
Simply provide up to 15 headlines and 4 description lines, and Google will do the rest. It then learns which creative ad performs best for any search query by testing different combinations. Therefore, people searching for the same thing might see different ads based on context.
We know this kind of optimization works: on average, any advertiser who uses Google’s machine learning to test multiple creatives sees up to 15% more clicks.
Maximize relevance and performance on YouTube
People watch over 1 billion hours of videos on YouTube every day. Increasingly, they’re tuning in for inspiration and information on purchases large and small. For example, nearly 1 in 2 car buyers say they turn to YouTube for information before their purchase. Almost 1 in 2 millennials go there for food preparation tips before deciding what ingredients to buy. That means your video ads must show at the right moment to the right audience.
Machine learning helps us turn that attention into results on YouTube. In the past, Google has helped optimize campaigns for views and impressions. In a continued trend, in 2018, they also rolled out Maximize lift to help marketers reach people who are most likely to consider their brand after seeing a video ad. Their new Smart Bidding strategy is also powered by machine learning. It automatically adjusts bids at auction time to maximize the impact of video ads on brand perception throughout the consumer journey.
Drive more foot traffic with Local campaigns
Whether they start their research on YouTube or Google, people still make most of their purchases in physical stores. In fact, mobile searches for “near me” have grown over 3 times in the past two years, and almost 80% of shoppers will go in-store when there’s an item they want immediately. If you’re an advertiser, that means driving foot traffic to your brick-and-mortar locations is critical – especially during crucial moments in the year, like in-store events or promotions.
To further assist in this endeavour, Google has introduced Local campaigns: a new campaign type designed to drive store visits exclusively. Provide a few simple things – like your business locations and creatives – and Google automatically optimizes your ads across properties to bring more customers into the physical store.
Get the most from your Shopping campaigns
In the same vein of helping with purchases, Google rolled out a new Shopping campaign type that optimizes performance based on your goals. These Smart Shopping campaigns allow an advertiser to hit their revenue goals without manually managing and bidding on individual products.
Through these campaigns, beyond maximizing 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. It takes into account a wide range of signals, like seasonal demand and pricing. Brands like GittiGidiyor, an eBay company, use Smart Shopping campaigns to simplify managing their ads and delivering better results. GittiGidiyor increased return on ad spend by 28% and drove 4% more sales while saving time managing campaigns.
Google later provided further integration for this feature, and users are now able to set up and manage Smart Shopping campaigns right from Shopify, in addition to Google Ads.
Advertising and machine learning go together like two peas in a pod, except we didn’t know it until the latter got developed!
Google’s updates represent a momentous occasion for advertisers worldwide, as they provide an efficient way of gauging your consumers. We no longer have to dawdle in the dark and wonder what’s the next trend and how it will spring into action. An advertiser can now foretell results by evaluating human action on an unprecedented level.
Originally published on Google’s blog HERE.