4 ways machine learning powers better marketing
At its core, machine learning is a way to label and analyze huge data sets quickly and on an inƒnitely 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 longterm, paying users but they’re not opening it much after initial download. You wouldn’t be the ƒrst to encounter this issue. In fact, only 37% of app installs remain in use after seven days. So how can you ƒnd the right audience? If you’re using siloed sources to identify your audience, you 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
multiple headlines and descriptions to ƒnd the best possible combination for each person, simplifying the ad-creation process and delivering stronger results.
Optimization: Engage the Right People in the Right Moments
People are searching more frequently and with more speciƒcity. 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 choose a strategy designed to achieve your company’s speciƒc 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 can you be sure the last click is the most valuable? People are interacting with brands across a growing number of screens and channels, making it difƒcult to identify which parts of your 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 didn’t, this model identiƒes patterns among clicks leading to conversions and identiƒes the most valuable touch points.