Understanding what consumers want and need — ideally, before they even do — is an ongoing imperative for marketers. Artificial intelligence (AI) companies like Synaptic can make that job much easier, especially with the emergence of deep learning.

A subset of AI, deep learning has the potential to transform the future of marketing by helping businesses to predict consumer behavior. It’s a machine learning method that uses layered or “deep” neural networks, similar to those found in biological brains, to learn skills and solve complex problems faster than people can. It helps computers (or robots) handle “human” tasks, such as perceiving objects, recognizing voices, and translating languages.

Deep learning provides a way to train AI to predict outputs, given a set of inputs. Sound easy, but it’s not: While it requires less data preprocessing by humans than conventional machine learning techniques, deep learning requires a large data set and a whole lot of computational power. However, if a deep learning system has access to those key elements, it can learn to predict human behavior pretty accurately.

Consider the “Predictive Vision” experiment. Researchers with MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) trained the deep learning system to predict whether characters in scenes from shows like “The Office” would hug, kiss, shake hands or high-five. After observing more than 600 hours of YouTube videos, the system was able to predict the action 43 percent of the time. According to the CSAIL researchers, existing algorithms could only do that 36 percent of the time.

Another well-known example of deep learning’s ability to predict human behavior involves self-driving cars. Researchers at Cornell University and Stanford University developed a “Brains4Cars” system, which includes cameras, sensors and wearable devices, that monitors a driver’s body language and traffic around the vehicle. The system sounds an alert when the driver appears to be on the fast track to a car accident. The system’s algorithm can anticipate driver behavior about 3.5 seconds in advance.

The potential to find patterns inside of patterns

These experiments have compelling results, but what’s the upshot for marketers? As deep learning technology continues to evolve and improve, businesses can finally put to work all the massive amounts of data that they’re gathering about current, previous, and would-be customers across an array of online and offline channels. And deep learning will become an even more important tool for marketers as the Internet of Things continues to grow, and even more data about consumer behavior is generated and collected from a wide array of devices.

Marrying big data with deep learning will help businesses to create personalized marketing approaches that will appeal to anyone who might buy their product.

Deep learning has “the potential to find patterns inside of patterns” in data to help businesses understand what customers really want. The deep learning opens the door to hyper-personalization of marketing messages and the customer experience because it takes a customer’s intent into account, and not just their transactional or interaction history. For example, researchers with Renmin University of China found that information about consumers’ hobbies and work situations, when used as inputs for a deep learning method, can help predict the automobile purchase intent and preferences of different groups of consumers.

The ability to predict a customer’s needs, and get it right, is pure gold for marketers. And with the help of well-trained AI, marketers can rely less on assumptions and guesswork and more on data-driven insights to predict customer behavior more accurately — and even well in the future.