Whitler: As we move rapidly into the holiday shopping season, what are the biggest changes impacting marketing?
Peluso: This is an exciting period for CMOs and CEOs everywhere. You start working on holiday in June, so the preparations, merchandising, engagement, and relationship developing activity have been place for some time—it’s fun when it starts to crescendo and you get to see the planning come to fruition. Over the years, we’ve seen a big shift to online shopping, which means there is an increase in the amount of data CMOs can use to understand their business and enhance the consumer’s shopping experience. However, this year, what I think is most exciting for marketers is the opportunity to use AI to improve CX (consumer experience). AI empowers marketers to not just use readily available data, but to put dark data to use for the first time.
Whitler: How can marketers use AI to enhance CX? Any examples?
Peluso: Let me provide you with four different examples.
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 North Face 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.
For more insight from IBM, check out these articles: 1) Why marketers should care about weather as much as merchants, 2) IBM study finds CMOs face a challenging role, 3) Cognitive technology and why marketers should care, 4) Highlights from IBM’s CMO Huddle, 5) Insight from IBM’s Advani on turning data into insight, and 6) 2017 Marketing predictions from CEOs, CMOs, and Authors.