4 ways machine learning
powers better marketing
At its core, machine learning is a way to label and CPCN[\G;JWIG;FCVC;UGVU;SWKEMN[;CPF;QP;CP;KPƒPKVGN[; larger scale. Here's how you can apply machine
learning to drive growth.
Audience: Find Your Most Valuable Customers
Let’s say you’re trying to get your app into the hands of long-term, paying users but they’re not opening it much after initial
fact, only 37% of app installs remain in use after seven days. So
might be missing out. Machine learning can sort and analyze
sources to help you learn which users are most valuable, and
help you maximize your budget by showing ads only to users
who are most likely to download and use your app.
Creative: Personalize Your Ads
People expect ads to deliver assistive, highly relevant
experiences—whether an ad is relevant or not has a huge
impact on a person’s decision to buy. Our research has shown
that 91% of smartphone owners bought or planned to buy
something after seeing an ad that they described as relevant.
Thanks to machine learning, marketers can create uniquely
tailored ads. Responsive-search ads mix and match
combination for each person, simplifying the ad-creation
process and delivering stronger results.
Optimization: Engage the Right People in the Right Moments
For marketers, this means it’s more important than ever to land
the right bid at search auctions. But it also means landing the
right bid is harder, as a growing surplus of data creates more
complexity for marketers.
Fortunately, there are products to help you automate this
process. Smart Bidding uses machine learning to analyze
millions of signals and make adjustments in real time. You
goal. Then Smart Bidding factors a wide range of signals about
the intent and context of every search.
Measurement: Unlock the True Value of Each Interaction
Let’s say that before making a purchase on your site, someone
decided to search some more, shop around, or click on a few
of your ads across platforms or devices. Typically, credit for a
conversion is given to the last ad a customer clicked. But how
interacting with brands across a growing number of screens
marketing strategy are working.
Data-driven attribution uses machine-learning algorithms to
analyze the clicks across your search ads. By comparing the
click paths of people who purchased your product to those who
For more insights, visit thinkwithgoogle.com.
BY CASSIE KOZYRKOV, CHIEF DECISION SCIENTIST, GOOGLE CLOUD
4'#6'&;+0;2#460' 45*+ 2;9+ 6*
37% of app installs remain
in use after seven days.
91% of smartphone owners
bought or planned to buy
something after seeing an ad
that they described as relevant.