The retail industry is awash with tech industry buzzwords that no one wants to admit they don't understand. That's okay, IBM's Darin Archer is here to help. The former Adobe and Intel exec with the curious sounding title (Director, Offer Management, Commerce & Merchandising, IBM Watson Customer Engagement) leads the tech giant's digital commerce and customer analytics offerings. He spoke with Retail Leader about innovation, artificial intelligence, cognitive technologies and what's new with Watson.
Retail Leader: Your bio says you are "redefining what e-commerce means." That's a tall order. How should retailers be thinking about digital and trying to manage their e-commerce business?
Darin Archer: I don't think they should be thinking about e-commerce, at all. It's just commerce. In a lot of organizations, the org chart influences a lot of what we do, how we operate, how we see customers, etc. If you go to Google or LinkedIn and search for the title of "chief digital officer" at retailers, that's the trend I have been watching. How many retailers have been moving past traditional roles and org charts and naming CDOs or even chief customer officers?
RL: Quite a few, but structural challenges persist.
DA: Customers do not think of retailers as having separate store and e-commerce teams. It tends to be retailers that think that way. It's amazing how many companies still have these silos. We have a long ways to go. Look at click and collect. A lot of retailers now have these special "buy online, pick-up in store" sections in the store. Those confuse customers. Customers don't understand, for example, why something purchased online has to be picked up or even returned in a special part of the store. A lot of retailers just have to get past this. Some of these new CDO titles and roles are helping with that. They are getting with their teams and telling them, "The customer journey flows across many channels."
RL: When you talk about the customer journey flowing across many channels, that's having a huge impact on supply chains.
DA: We have to focus on understanding and mapping the customer journey. Retailers need to understand where customers inform themselves about products, where they make decisions, how they decide to purchase in that moment. Once they get that good baseline of, "Here's what's really happening," then retailers will get a better handle on supply chain efficiency. IBM introduced a product about a year ago called Journey Analytics. This is a tool that was developed to fix these exact supply chain problems. We realized that no one is really collecting and analyzing the data: where those touch points are, the journeys, the paths, and how one influences the other. So IBM took some digital analytics and behavior analytics and mapped them out in terms of the customer journey perspective, to tell that retailer: "Here's your priorities. This customer shopped in-store, but also went to your Facebook page. And that's a common path, so maybe you should invest there." A lot of retailers are doing all this stuff: e-mail marketing, geo-fencing, social media, promotions, etc. And they really don't know whether it's working. Now retailers can step back and definitively know what's working. Another thing that's possible with Journey Analytics is testing hypotheses. Retailers can test what they think will work.
RL: Artificial intelligence was a recurring theme at IBM's Amplify event earlier this year, but there's so much confusion about AI. How do you define it and how can retailers leverage it to drive growth?
DA: AI is a crucial technology that helps retailers provide stellar customer experiences. AI and cognitive technologies can look at incredible amounts of data, and make sense of it, far quicker than we can alone. However, rather than replicating human intelligence (artificial intelligence), we are leveraging AI to enhance and scale human expertise (augmented intelligence), which helps people make better decisions that solve today's most important challenges.
RL: So what is a practical application of AI in a retail environment?
DA: With AI, retailers can work from real-time, data-driven insights to craft really engaging and personalized experiences for current and prospective customers. This data is coming from social media, apps, and even in-store experiences. By having the cognitive tools to quickly analyze those data points, it's easier to connect the dots, make more personalized connections and ultimately build brand loyalty. Turning to cognitive technologies is a journey — but it isn't an intimidating one. The benefits of cognitive tools produce competitive advantage, and it's surprisingly easy to get started, even for companies who don't consider themselves data-driven right now.
RL: A lot of retailers are eager to capitalize on jumping on the personalization trend. What does a personalized retail experience powered by AI look like to you?
DA: Retailers can redefine what a personalized customer experience because of AI. When a retailer is drawing insights from data and uses cognitive technology to analyze it, more customized interactions occur. And I don't just mean interactions the customer has with the brand — like recent purchases. Companies can also use AI to analyze outside information like the weather or shopping trends. Personalized retail experiences in the AI era means that every interaction is human and ubiquitous across all channels and devices. For example, we worked with 1-800-Flowers to create a Watson-power concierge called Gwyn. Customers can chat with Gwyn and tell her what they're looking for, like a Mother's Day gift, and Gwyn will ask a number of relevant questions to help her recommend an appropriate gift based on those specific responses. Despite never stepping foot in store or speaking with a sales associate, customers are still getting an experienced tailored to their individual needs.
RL: What else are your retail customers telling you when it comes to new consumer behaviors?
DA: The data show that there's a lot more engagement post-sale than I think a lot of retailers know about. Retailers all design their conversion goals for the sale. Whether it's online or in-store. But when you look at the analytics data related to the customer journey, there's tremendous engagement afterwards. A lot of the engagement is product-specific, whether it's electronics or apparel. But even in categories like beauty, there's tremendous post-sale engagement. Sephora gets it: Not only do they want to get the customer excited about products upfront, but they also understand that customers will go back to the website or the store to get a sort of "refresher" on how to use the product. And so they actually focus on nurturing the customer way after the sale. Very few retailers are doing a good job of nurturing the customer after the sale. They may have the data, but they don't know the "why." Sephora knows that eventually the customer will run out of the product and by nurturing them after the sale, the customer will more than likely buy again from them.
RL: Do you think apps still play a role in this "nurturing" of the customer?
DA: I love apps. Websites are clunky and slow, and no matter how hard we try to make them responsive, they are not designed for smartphones. When a customer pulls out a retail app, he or she knows they will be able to perform all manner of tasks within that space. Whether looking at loyalty points or past orders or searching for merchandise. Apps make the customer experience so much easier, and they are not going away. None of the web browsers can come close to what an app can do for a customer and for the customer experience. I also don't think social media can replace apps either, in terms of having a rich customer experience. Social media is just a billboard.
RL: Are there any other retailers you can single out as doing a good job of bridging the online-physical gap?
DA: Target is doing a great job with their multi-app strategy. Not only have they not given up on apps, they have doubled down on apps and invested in several apps. Target customers love how the Cartwheel app allows you to input a shopping list and then spits out a route of the quickest way to shop for your items. Cartwheel also has a gamification component in there as well, allowing customers to earn discounts for navigating certain aisles and buying certain products. This is how Target gets a customer to walk into an aisle they might not have otherwise walked in to, and Target gets an unplanned purchase.
RL: Any other examples?
DA: Lowe's is another great example. They have taken a Pokemon Go approach with their app, in which a customer points their smartphone camera at a place in the store and a map of the store pops up with blue dots. The blue dots are superimposed, with machine vision. It's the retailers like Lowe's that are thinking beyond the cart with their apps that will be successful.
RL: AI has a role to play in helping retail cope with exponential growth of data and Watson is a leader in the space. Talk about some of Watson's use cases or emerging applications.
DA: We were one of the first companies to enable the omnichannel use cases for click and collect. So many retail CEOs said they wanted to offer that, and they committed. And then they found out that, oh, they don't know what their inventory is, they have no idea where the inventory is. There were all these systems for order processing (POS, e-commerce, etc.) but nothing that put everything together. There was suddenly a demand for a centralized system that shows the entire lifecycle of an order. Then we also added mobile app capabilities so that store associates could have access to it. So that's how pick and pack is all mobile-enabled. Watson comes into play with: where is the product, how fast can we get to it, where should it be picked up. We are looking at a lot of optimization techniques, where you should source from, fulfill, etc.