Today’s consumers are expecting more relevant and personal experiences online. They’re demanding seamless, hyper-relevant content at each moment of interaction with retailers. The unfortunate reality – the latest research shows fewer than half of retailers are getting personalization right. Merchandisers and marketers alike are facing increasingly fragmented media and audiences, dramatic device and channel proliferation, and a growing focus on data and measurement. How will retailers drive success in this new high-pressure environment? Enter artificial intelligence (AI) and deep learning.
AI and deep learning provide retailers a means of individualizing each customer interaction at a scale unattainable by more manual or rules-based solutions – in real time. Without these technologies, the dream of true 1:1 individualized marketing is fundamentally impossible.
This is a much different technology approach than what has been used in the past. The technology retailers used before was relational-database in nature. Grouping customers into segments based on behaviors and applying specific rules to each segment. AI and deep learning actually allow marketers to manage the requirements of tracking millions, if not hundreds of millions, of preferences, but also discovering those preferences.
The way this technology works is that mathematical models calculate values for thousands of attributes. Often there are hidden vectors that emerge from the data which become important in driving results. We use code to represent those mathematical models and set them against the data and events. This requires a delicate balance of both data science and computer science to discover attributes about an individual shopper, based on a collection of data and events that are occurring while they are shopping. We’re able to accomplish this at massive scale, across thousands of retailers’ webpages and millions of simultaneous shopping sessions because of AI.
By leveraging an AI and deep learning-driven platform and technology architecture, brands can process a tremendous amount of customer, behavioral and product data, respond in real time with the most relevant content or products, and understand the business impact of each new experience created.
The increased popularity of artificial intelligence and deep learning have given rise to a wealth of new opportunities for retailers – specifically merchandisers. Retailers can leverage AI to learn from online and offline shopping patterns and combine it with the wealth of customer data they’ve already collected (i.e., “first-party data”), to deliver highly relevant and engaging shopping experiences that are tailored to each individual customer.
In the end, artificial intelligence can be good for buyers and sellers in the retail world, and will likely help many retailers scale faster. As Kleiner Perkins Partner, Mary Meeker pointed out in her annual “Internet Trends” report earlier this year, some retailers are now achieving $100 million in annual revenue in five years or less; it took Nike 14 years to reach that milestone, and Lululemon eight. The use of AI by retailers will only accelerate this trend. Really, it’s only a matter of time before the industry smartens up.
-Kurt Heinemann of Reflektion