The company takes customer interaction and satisfaction to a staggering new level, light years beyond the traditional practice of predicting user preferences by examining past behavior. “Analytics, by definition, is taking past data and uses it to apply to something to the future,” Spector states. “Instead, you should take current data and apply it at the moment that you receive it. This is a game changer.”
The most well-known machine learning personalization system came out of Google, starting with YouTube. In fact, LiftIgniter’s Founder and CEO Indraneel Mukherjee has a PhD from Princeton in theoretical machine learning and was recruited to help develop this system, which became one of the largest, well-known and most successful personalization engines in the world– adding billions of dollars in incremental new revenue nearly overnight.
The LiftIgniter team has developed a way to take this technology to a new level and bring it to the masses by melding two critical factors. First, they employ an infrastructure capable of processing terabytes of data in real time. The second component, Spector says, is “the ability to have machines truly learn from this massive and ever changing data set.
Everywhere you touch a user, you should personalize that experience
Speed is critical– digital properties and their users are ever changing. Learning and evolving on this data becomes a massively powerful differentiator.”
LiftIgniter provides service for customers in three general markets: media, e-commerce and enterprise B2B clients. “All three have similar needs. They have content, whether it is articles, videos, items to buy, or advertisements, but they want to get their users to take specific actions, such as to buy a product or to quickly sign up for a demo, or to watch a video.” With installation and integration of LiftIgniter’s tools taking a maximum of four hours, results are fast and easy to measure. “They install us, we learn and the output is an optimized, personalized list of items. That list of items says, ‘For this given impression that the user just clicked, these are the things that we should show the user to achieve the business goals set by our customer.’ We’re enhancing the user experience in very clear terms, at 80 plus percent.”
Spector envisages that “machine learning personalization will become an underlying component of every single digital property within the next five years.” Not only will personalization be able to predict what an end user may do on the site, but he says that they will be able to impact all components of a business. “Everywhere you touch a user, you should personalize that experience. Our personalized platform can personalize on-site, recommendations, personalized apps, personalized search, and personalized emails and newsletters. For the first time ever, without any extra work on the part of the customers, we are able to enable fully dynamic, personalized experience throughout their entire journey– always learning, adjusting and optimizing.”