Main applications of machine learning in marketing
Thanks to advanced algorithms and machine learning, there is a wide range of applications that digital marketers can use to grow their marketing strategies and drive more revenue for their organizations.
There are many branches in the machine learning tree, but we believe that these are the differences that matter most to marketing practitioners, like demand generation managers and growth marketers. By understanding which algorithms are appropriate for which business problems, marketers can get practical value out of machine learning.
In this video, Intellimize CEO Guy Yalif will walk through several common problems that marketers face, and how machine learning can help solve them.
What is machine learning good at in marketing?
- Lead scoring
- Finding the ideal price to sell your products and services
- Finding the ideal promotional amount to use for your products and services
- Determining whether or not a person will click on an ad
- Determining whether or not an email is spam
Determining what product or content to show on your website - Recognizing the content of an image
- Writing an email subject line
- Understanding speech
- Customer segmentation
- Finding business insights from data
- Fraud detection or outlier detection
- Conversion rate optimization
- Determining a sequence of emails to send to prospects
Each of these common marketing tasks falls under a specific type of branch in the machine learning tree. To find out more about machine learning and how it influences marketing, watch the video above.
Personalization is another area where machine learning is making a big impact. To understand how you can apply machine learning at scale to optimize your website for each individual customer with Intellimize, simply click on the Request Demo button on our website.
