Machine Learning Isn’t Magic, It’s Data-Driven

October 11, 2018 | Article written by Carly Morris

Throughout the year we’ve discussed a variety of current and potential trends in advertising and data. From shoppable content, to cryptocurrency, and now: machine learning.


What Is Machine Learning?

Machine learning is defined as a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data, and in effect improve performance on a specific task without being explicitly programmed.

Essentially, it uses custom mathematical algorithms and lots of historical data to teach software how to accomplish tasks or make predictions. In short, it’s using data to answer questions. (Cue the robot takeover?)

The easiest way to comprehend machine learning is to look at some current examples. Think about every day experiences like autocorrect, facial recognition, recommended videos, and much more.


Why Is Machine Learning Important to Advertisers?

Not surprisingly, we’re big believers in the power of data. And, when it comes to machine learning, the possible applications are almost endless.

Here are just a few ways that this technology can be a total gamechanger for digital advertisers:
● Fight Fraud
As most digital marketers are by now well aware; ad fraud continues to be a significant challenge facing the industry at every level. While there are several ways to combat fraud from the ground up, machine learning has become a huge asset in the ongoing battle, given its ability to learn what kind of activities and behaviors qualify as suspicious in real-time and cut them off on contact.
● Create Key User Segments
Machine learning can look at audience behavior patterns to segment users into groups accordingly. This lets advertisers easily identify who their returning customers are, who their new users are, and who’s most likely to download and ditch.
● Personalize Ads
Machine learning also enables advertisers to use their data to better understand user behavior and predict what they will and will not like when it comes to ad and push notification messaging. This is huge in a time where personalization means everything.
● Improve ROI
Machine learning can predict how many customers you’ll have, how many products you’ll sell, who is most likely to buy them, and more. This can help businesses determine how much product to have in stock, where to focus their marketing efforts, and even how many people to have on staff to manage growth most efficiently.


What Verticals Does Machine Learning Benefit?

The short answer is: just about all of them. Think: predicting what will interest shoppers in the realm of eCommerce or suggesting a new series in the entertainment and VOD sectors.

But even outside of the mobile-first world, machine learning can be applied to nearly any industry. It can be used for everything from simplifying a task for a warehouse, to detecting medical patterns, to gathering and optimizing research.

So how can you apply it yourself?
1. Prepare:
Start gathering data… and tons of it. Machine learning is driven by data, so leveraging an outside partner to securely gather massive data sets can be critical to loading up your algorithms with enough experience to effectively take over a task or begin making predictions.
2. Plan:
Determine what you want to accomplish. Are you looking to simplify a task? Make predictions of user behaviors? Better target your next campaign? The possibilities are endless!
3. Execute:
Find a reliable, trustworthy, and GDPR-compliant partner to help you safely and effectively utilize machine learning at scale to reach your unique goals.


What’s Next?

Machine Learning isn’t perfect, but it is a trend that is forecasted to have a major impact on advertising and app development. Google has even created a Machine Learning Crash Course for developers, or anyone else interested in getting their hands dirty.

Are you ready to train your machine?