How Brands are Leveraging AI
Artificial intelligence continues to reshape the retail industry, at large, on both the customer and enterprise side. In an industry that typically performs antiquated practices, AI implements cutting-edge advancements in operations with the benefits of personalizing the customer experience, tailoring the product design, and streamlining operational costs to reduce waste. Implementing the latest technologies successfully, however, requires brands to critically consider the areas where innovation and data can drive value to the customer or reduce operating costs to the business.
For the fashion industry, as a whole, brands are finding more of their customers are moving online which poses the challenge of how do you personalize the online experience while differentiating the retail experience. Currently, online customers are overwhelmed with pages upon pages of new arrivals, dresses, and other accessories as brands present their static product categories for every customer.
The use of AI data offers customers a more personalized experience that reduces friction in the process, and allows brands to curate lookbooks, and satisfy unique needs of individual customers. Consider the personalization of your Amazon or Netflix account, they are suggesting targeted options for you based on your simple preferences and historical purchases, which accelerates the selection experience or exploration of new options. The collection of customer data to understand preferences, removes obstacles for the customer and streamlines sales for the business. A creditable example in the fashion industry, is Net-a-porter’s capitalization of this approach, through development of an AI scanning software that collects imminent travel bookings and upcoming events from a customer’s digital footprint. Net-a-porter tailors the product suggestions that appear on their e-commerce site to meet personal lifestyle needs. Further expansion of this layer of personalization across the retail industry would stimulate growth and profit.
To implement personalization within the online experience, brands should adopt AI that draws on customer history and customer persona preferences. For example, Nordstrom’s “The Look” has look books generated off the products you are searching to complete the entire look - whether it is casual, night out or work related. Creating ideas and options for the customer can bring together all the elements of a look online. Liketoknow.it is an application that offers a similar service to customers, by allowing them to locate the sellers of clothing they come across on various channels online. Through a simple screenshot, Liketoknow.it connects brands, influencers, and customers to make online shopping simple. Presenting curated options complete a look or match an aesthetic seen on an influencer, entices customers, increases sales and reduces the friction of the buying process.
With more emerging local brands entering the market, expensive innovation strategies aren’t always accessible. If we simplify the concepts, the foundation of AI starts with data that is organized in a manner that helps a brand make more informed decisions. With the various data sets that exist within social platforms, ecommerce platforms and search, new brands can leverage data strategies to identify digital customer attributes. These digital attributes can be used to prototype marketing campaigns that price sensitivity and product viability. Merging social feedback, user generated content and analytics can help emerging brands be effective with their limited marketing and advertising budgets, while designing more made to order products. Using social campaigns to test price points and aligning the intended customer with the digital customer attributes can be a simple, yet effective approach to growing a brand. If social feedback on ad campaigns or user generated results are pointing to a price or presentation issues, these can be assessed by the business to meet the needs of the customer. Additionally, data and intelligence can be implemented to strategically shape the pop-up retail experience. In many cases, digital customer attributes can be applied to flexible store locations to place locations where ideal customers exist.
To conclude, throughout the entire retail product and service cycle, artificial intelligence is taking off with momentum. Despite the expansion of AI in retail, issues are arising for companies who implement innovation trends without a clear strategy or value proposition. The business case for implementing data and intelligence strategies starts with identifying use cases that would drive sales or reduce operating costs.