1.- AI powered gift selection:
This is a tool that retailers like 1800-Flowers.com are using to help consumers pick out just the right gift. For example, 1800-Flowers.com created “GWYN” (Gifts When You Need), a new AI-powered gift concierge that behaves like your own “personal assistant” and learns your preferences as you interact with the system. Through a series of questions, it can get smarter and predict the type of gift that might be most appropriate for somebody. For example, a customer might type, “I’m looking for a gift for my mother,” and GWYN will be able to interpret their question, and then ask a number of qualifying questions about the occasion, sentiment and who the gift is for to ensure she shares the appropriate, tailored gift suggestion for each customer. Importantly, this is different than conjoint or even Bayesian methodologies, because Watson understands, reasons and learns as it interacts with people in natural language and then applies that insight to the gift recommendation. It pulls data from the interaction but also many other sources such as consumer buying trends and behaviors.
2.- AI powered product selector: The North Face, an outdoor apparel, equipment and footwear retailer, launched a new interactive online shopping experience powered by IBM’s Watson. Consistent with The NorthFace brand’s mission of applying technology to transform the retail experience,customers can now use natural conversation as they shop online via an intuitive, dialog-based recommendation engine powered by Fluid XPS and receive outerwear recommendations that are tailored to their needs. Utilizing Watson’s natural language processing ability, XPS helps consumers discover and refine product selections based on their responses to a series of questions. For example, after a shopper enters details on a desired jacket or outdoor activity, XPS will ask questions about factors like location, temperature or gender to provide a recommendation that meets the shopper’s specific usage and climate needs.
3.- AI powered Out of Stock Management: A key challenge for retailers is managing their inventory levels. Ideally, you have just the right amount of stock on hand to meet consumer needs. If you are out-of-stock, you risk upsetting the consumer and having them go to another store. If you have too much stock, you have wasted money that you could have used elsewhere. So how can AI combat being out-of-stock? Watson is working with retailers to monitor weather, purchase rates and consumer behavior to do a better job of managing and monitoring supply chains to right size inventory levels and avoid out-of-stocks. The tools we use are called “IBM Commerce Insights” and “Watson Order Optimizer”.
4.- AI powered Consumer Insight: AI is changing how marketers generate insight about consumers to provide more contextual relevance. Understanding things like social profiles, movement, weather, and behavior, AI can help marketers understand at a more granular level what consumers want and need. Consumer needs are dynamic—not static—and require an insight machine that can take this dynamism into account and feed it into your marketing plans. AI goes through a progression of understanding, reasoning, learning, and then adapting insight. Further, AI can include a lot more information in its learning process so that the marketing is more customized at the individual level. For example, Watson AI includes a tone analyzer. The system understands (through augmented intelligence) natural language and it learns over time so that you can reason and adjust offerings. Consider cancer patients. By using the tone analyzer, Watson’s AI can better assess consumer reactions to different treatment protocols and tailor the plan to the individual patient to increase compliance. The potential here is unlimited.