Marketing automation, a piece of software based on big data that is used to execute, manage, and automate the cloud of marketing tasks and processes. This software changes the manual repetitive marketing process and is replaced by performance-oriented applications built for specific purposes.

Optimize for growth instead of efficiency

Machine learning is only as good as what you ask it to optimize. Top performers optimize for profitable growth and take a holistic view of their marketing, while others are obsessed with efficiency or measure too granularly, missing the forest for the trees.

For example, by focusing on long-term profitability instead of short-term ROI, HomeAway was able to dramatically turn around its business, increasing 2017 revenue by 115% year over year.

As another example, Google has worked with some top-performing financial services companies that optimize for product purchases made online, by phone, or in person while others optimize only to online information requests. A machine learning algorithm optimizing for actual products purchased in every sales channel will drive a lot more sales, much more effectively than one optimizing only for an information request made online.

Or consider online financial services company Betterment. Instead of focusing only on search or only on video, it made them work together. Betterment used custom intent audiences to engage YouTube viewers who recently searched for financial keywords on Google. The brand significantly improved its YouTube campaigns, and also saw a 245% increase in brand searches on Google.

Improve creative

In a world where online marketing will be automated, the power of your brand, the personalization of your ads, and the emotional connection you create with consumers will matter even more.

For search ads, machine learning can create hundreds of tailored ads for a single keyword by using a new tool called responsive search ads. It creates unique ads from a few headlines and descriptions, and automatically serves the right ad to the right customer.

On YouTube, advertisers can use machine learning to personalize content at scale. Frito-Lay identified the most popular YouTube content categories – everything from gaming to 90s fashion – among its target audience. It then used YouTube’s Director Mix tool to quickly create different creative variations for each of the top categories. Finally, it set up the campaign so that the relevant creative was served to the right person at the right time. If someone was about to watch a music video, for example, they might have seen music-related creative.

Invest in better mobile experiences

It doesn’t matter how beautiful or effective your ad creative is. If you have a poor mobile site experience, users won’t convert. Top marketers understand the value in having fast, frictionless mobile experiences. With automated marketing, machine learning bidding algorithms automatically drive more customers for better-converting sites. Underperforming mobile sites are at a disadvantage.

Most marketing automation now divides customers into pyramids, which are examples of patterns that help marketers identify goals and meet marketing needs. The pyramid is a stable and long-term partner customer object, while the bottom is the lost customer and potential customer. These are possible objects, which require marketing automation to analyze and determine the percentage of customers that meet business needs.

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