The complete glossary for marketers
Machine learning is a subfield of computer science that involves the ability of computers to “learn” from past experiences and observations. This predictive programming combines data, code, and science to find patterns that rule-based programming cannot. With machine learning, instead of creating a program based on “if-then” rules, an algorithm is programmed to find opportunities based on mining data to produce reliable decisions. These decisions are consistently improved when more data is stored and analyzed.
Artificial Intelligence (AI) and machine learning are related, but not the same. AI is the concept and programming of machines to perform and complete tasks in a “smart” manner. Machine Learning is an application of AI giving machines access to data to process and learn autonomously, making decisions and bettering the decision making process without human involvement.
Machine learning already affects our daily lives. The Google Pixel 2 phone utilizes Google’s AI capabilities for video capture to anticipate how the user will move, creating extremely stabilized videos. Another popular example: self-driving cars. In this emerging application of machine learning, real-life humans navigate a vehicle while a computer records the decisions the human makes as they encounter obstacles. Once the computer has obtained enough observations, it will have “learned” how to drive, and can successfully navigate the world by itself. (Or so we are promised!)
Websites are quickly adopting machine learning technology to provide results that are catered to an individual. Machine learning on these digital properties is called personalization. Personalization uses behavioral targeting and predictive analytics to serve each user dynamic content to increase positive interactions with your brand.
Applied to the world of ecommerce, machine learning enables brands to deliver 1-to-1 personalization at scale. Computers observe which messages and promotions work for which individuals, analyzes the associated behaviors, and learns which content performs well for which individuals. Computers observe which messages and promotions work for each individual user. The algorithm analyzes associated behaviors and learns which content performs well for each individual, improving interactions as it processes more data.
Instead of needing to search endlessly for the product you want to purchase, ecommerce personalization learns your needs as a customer and shows you results based on your intent.
By seeing each customer as an individual, the Monetate Intelligent Personalization Engine™ focuses on creating a website experience to your customers based on who you are, what you like, and what you do using goal-driven machine learning to observe and better serve your customers with real data in real-time.