Personalization Tech: Early Movers
Product tagging is always a difficult task. And that’s where AI has come into play by automating the process and enhancing it with in-depth data from various sources. A perfect example of this is the Lily AI platform which applies powerful machine learning to deep product tagging and sophisticated customer intelligence data for an organized shopping experience. The company uses artificial intelligence to use image recognition to automate product tagging. This information is then connected with customers’ past behavior to make smarter recommendations. The company has worked closely with ThredUp to categorize and tag all of the more than 100,000 items that the eCommerce platform receives each day.
Companies like Nike and Netflix are setting the bar for personalized recommendations and content. Nike has been making several investments in data and analytics to power its D2C business. Nike’s acquisition of Datalogue in 2021 is a big step forward in making Nike.com more personalized. It provides a better experience for our customers. Actions such as data preparation and integration allow us to recommend products earlier, and better anticipate when something might need to be replaced or replenished.
One of Netflix’s approaches to targeting content offers retailers valuable guidance on incorporating more consumer data into their personalization approaches. The streaming giant uses advanced forms of machine learning to modulate the content it feeds.
The company has developed a new type of AI called contextual bandits to change the movie or TV artwork that different viewers see on its platform. Contextual bandits take individual users’ contexts (such as location, preferences, and other data points) into account so they can provide the best viewing experience possible. The use of AI to deliver tailored and personalized Netflix content helps boost engagement. This is more important than demographics such as age, gender, ethnicity, etc.
Similarly, some companies like Nike and Amazon are pioneering the idea of a personalized product feed for individual shoppers. The Yes has been part of the wave of successful start-ups in the fully customized assortment world. They do this by gathering shopper preferences via online quizzes. On their first visit to the Yes site, shoppers answer questions about their preferences for brands, color, fit and more. The Yes does this so your feed will be tailored to your preferences. You can have a new outfit delivered to your door every time you say yes to something new on the site.
Startup Prodport helps retailers customize product pages to meet individual shoppers’ needs. The platform helps adjust factors, like the number and type of images on a product page, as well as the prominence of reviews from others in your industry, to line up with how that customer shops online.
Suggestions
- Personalized marketing is all the rage these days, but people are becoming increasingly wary of their privacy. Technological advances like “zero party data” that allow customers to share their data have enabled brands and retailers to get more accurate statistical information and still maintain some level of contact with what those individuals want. Customer data platforms will be essential for retailers to connect with customers across all networks, from offline retail to online channels. They can establish the right message for consumers and send them the right product.
- Fully personalized products are the next step. Nike and Coach are among the brands sponsoring consumers to customize their sneakers and bags, D2C firms like Function of Beauty use quizzes to personalize hair care products. Perfect Corp will most likely use its AR-powered skin diagnostic tool to not only recommend foundation types but also create them on the spot for consumers.
