The North Face & Watson: Bringing the In-Store Experience Online
E-Commerce has exploded in recent years, with consumers choosing to make many of their purchases online in favor of traveling to brick-and-mortar locations. However, there are many retail sectors where consumers still prefer to buy in-person, even if their pre-purchase research is largely aided by online channels. Apparel is one area that fits this pattern, with consumers wanting to try on sizes, see how the products actually look, and wear them to ensure an adequate level of comfort. In addition, consumers of specialty retailers enjoy the in-store experience due to the knowledgeable sales associates who are able to educate them and guide them towards relevant products and services. For this reason, many retailers have struggled to match the online shopping experience with the traditional brick-and-mortar shopping experience.
One of our clients, The North Face, is combining the power of big data and artificial intelligence (AI) to tackle this issue and close the gap between in-store and online shopping for consumers. In collaboration with Fluid and IBM Watson, the brand launched an AI-powered personal shopper called XPS. Essentially, the tool acts as a digital brand expert, helping users navigate the online experience like a sharp in-store sales associate. Here is a quick, yet impressive, demonstration of the technology.
A Case for Artificial Intelligence in E-Commerce
Brands using e-commerce are facing a real challenge to get their users through the entire purchase funnel without losing interest. In fact, 70% of shopping carts are abandoned before completing the check-out process. Certainly, strategies such as display retargeting can be effective, but the key ingredient missing to convert on digital platforms is someone helping the buyer through each stage with confidence. Introducing personal shoppers online that can guide users via chat is a great way to help them find what they want while staying engaged. However, this solution is extremely expensive at scale. Building an AI-powered personal shopper is a more scalable and efficient way to guide the consumer to a point of purchase. Additionally, machine learning models like the one created for The North Face continually learn as they are used, meaning the program will become even more effective over time.
XPS and other AI-based programs rely on a Natural Language interface (either voice-based like Siri or text-based like XPS). This is important because it allows the user to speak to the computer in the same way he or she would speak to another human being. It also removes the need to type in items you want to buy, removing friction often associated with online shopping. For these reasons, Natural Language processing is one of the most successful applications of AI to date.
Finally, AI-based e-commerce experiences can help alleviate a common human condition that is exacerbated by online shopping: The Paradox of Choice. When confronted with too many options (many of which irrelevant), consumers will opt most often to make no purchase at all. Artificial intelligence can execute an initial curation, limiting the set of choices for the end user while still allowing him or her to be in control of the final decision. In this way the decision is split in two parts, the machine curates the best options from a technical standpoint and the consumer chooses among these the ones that best fits his or her style. The process is similar to what Olapic does with our Photorank tool, combing through thousands of images available to our clients to surface the set that is most impactful, and allowing their marketing teams to make the final decisions with confidence in the quality of the curated set.
As AI continues to become more widely accepted in broader society, brands will begin to test ways to incorporate it into their customer-journey, which will have two distinct benefits:
- It will remove friction points for the end user such as data entry and overwhelming choice
- It will improve efficiency and conversion rates for marketing teams
Has your brand started working with AI, yet? How do you think it might benefit your customers in the future?