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When operating at scale, systems-level improvements make all the difference to margins and metrics for success. This means growing will require solving problems in routine parts of the business, and processes that are repeated over and over.
In ecommerce, these optimizations can come in the shopping cart where consumers make decisions about whether to check out, or in the fulfillment network where efficiency can bring advantages in speed.
As retailers are doubling down on growing their own ecommerce channels, they are seeking out AI and automation to make the kinds of process changes that can help them stand out to customers, and get more profitable in the meantime.
Here’s a look at three retailers that are adopting new technologies:
Levi’s leverages machine learning
Ecommerce provides choice, but the work to sync up what consumers want with a retailer’s processes to get it to them creates layers of complexity within a supply chain.
At Levi Strauss & Co. a new platform is using AI to help the fulfillment process fit the customer experience, inventory and the costs involved in the steps to ship an item out.
Called Business Optimization Of Shipping and Transport engine, or BOOST, the system can locate specific items within Levi’s assortment, even if they are not within the ecommerce-specific inventory.
“What BOOST is optimized to do is fulfill ecommerce orders more effectively,” said Louis DiCesari, Global Head of Data, Analytics, and AI. “When somebody goes online to make a purchase, we have distribution centers where we keep inventory specifically for those orders. One of the things we can do with BOOST is broaden that search for available product to include stores and allow the engine to choose the best fulfillment option for both the consumer and our bottom line.”
Levi’s, which is embracing a DTC-centered strategy as it seeks to grow digital sales, offered the example of a consumer who wants to purchase a trucker jacket in a particular wash. The jacket may be out of stock in a distribution center, but BOOST can locate the jacket at a store near the consumer, and make it available.
The system also seeks to resolve the issue of split shipments, in which customers receive more than one package when ordering multiple items from Levi’s. It considers shipping, packing and labor into its calculation, while finding a path that gets an order to the consumer in the simplest form.
“The beauty of it is that we’ve been able to automate all of this so it’s really a decision-making engine, not just an information engine, allowing our teams to focus their efforts on other value-adding initiatives,” DiCesari said.
Currently, the system accounts for 40% of eligible ecommerce orders. Levi’s is expecting that number to be 100% by Black Friday.
Gap grows fulfillment
Inside a Gap Customer Experience Center. (Courtesy photo)
At Gap Inc., holiday preparation includes expansion in the fulfillment network that puts automated systems alongside people who are working to ship out orders to customers.
The apparel company in August opened an 850,000-square-foot Customer Experience Center in Longview, Texas. It is outfitted with robotics systems and automation technology that is designed to optimize employee processes for speed and efficiency. It also expands processing capacity in the fulfillment network by one million units per day, bringing total capabilities to four million units per day.
“Peak season is now, and we know with peak season comes increased demand, increased hiring and increased opportunity to delight our customers,” said Kevin Kuntz, Head of Supply Chain at Gap Inc. “As we continue to deliver on our growth strategy, the launch of our Longview Customer Experience Center is another opportunity to further unlock the power of technology and automation, evolve the way we work, diversify our business, and deliver an exceptional experience for customers.”
The expansion comes after Gap Inc. expanded another Customer Experience Center in Fishkill, NY, adding technologies including automated receiving, multi-level pick modules, enhanced returns processing capabilities and new automated storage retrieval systems.
Opening up the network
With the supply chain enhancements, Gap is also seeking to make its network available to other retailers. It recently launched a new initiative called GPS Platform Services, offering logistics and fulfillment capacity to DTC and B2B businesses.
Drawing on a network that includes 13 distribution centers and a workforce of more than 9,000 people, capabilities of the service include ecommerce fulfillment, storage, warehousing, packing, shipping and returns processing.
With this new offering, Gap joins a group of retailers making logistics and fulfillment capabilities available to other retailers. Amazon has a massive fulfillment network and is making plans to deliver directly for other retailers, while Shopify is building a fulfillment network of its own that was accelerated by the recent acquisition of Deliverr. Among fellow retailers that are synonymous with the mall, American Eagle Outfitters also recently launched a network called Quiet Platforms following a pair of supply chain-related acquisitions last year, and has been loud about its intentions to build a group of partners to compete with the largest companies.
Rather than a move to take on others, Gap’s launch may be best interpreted as a sign that in-house fulfillment networks are becoming commonplace among retailers, especially as they seek to build out direct ecommerce channels and take lessons from the supply chain chaos of the last year that showed how there are benefits to owning systems. As ecommerce grows, these networks may even become a requirement for retailers seeking to reach scale. Offering the resources of these networks to others is a recognition of a business opportunity that emerges when one stands up a nationwide network. Gap probably can’t compete with Amazon’s vast logistics operation, but the growing size of the market for delivery as a whole means there is potential to bring some businesses under its wing. That can still be an asset. Plus, it could help the bottom line if there is success. Gap, Inc. reported a decline in sales across its brands in the first quarter, so turning its network into a business opportunity could help. Adding efficiency through automation will only increase the likelihood that its services for others will be profitable.
Dick’s tackles cart abandonmentDick's Sporting Goods. (www.flickr.com)
At Dick’s Sporting Goods, AI is helping to address a prevalent disconnect in ecommerce experiences: Shoppers put items in a cart, but don’t ultimately check out.
Through a partnership with predictive shopper engagement platform Metrical, Dick’s has a tool to analyze real-time customer data about a shopping journey, and provide relevant content that encourages engagement and ultimately helps ease the path to purchasing the items placed in a cart.
“Cart abandonment was a key strategic area for us to optimize at DSG,” said Miche Dwenger, VP of ecommerce experience at DSG. “We tried both third party and in-house developed solutions but none delivered the results we wanted because they lacked a predictive capability. Metrical’s predictive AI engine not only improved cart conversions, but its ability to dynamically present personalized content including messages, offers, and other relevant information has enabled us to dramatically improve the customer experience.”
Metrical is also providing tools as Dick’s seeks to create a connected shopping experience across online and offline shopping.
“A key part of improving customer lifetime value is ensuring the digital and physical store experiences complement and support each other seamlessly,” Dwenger said. “As we gain insights, we’re able to make more informed recommendations in both environments. In addition, Metrical works seamlessly with other vendors in our tech stack, including product recs, email marketing, text messaging and more so we are currently exploring opportunities to expand AI’s use into additional applications.”
Going forward, Dick’s wants to expand its use of AI. It believes the predictive capabilities of this technology will ultimately help make shopping experiences more personalized.
Trending in Operations
"Fashion ecommerce is one of the most cumbersome customer experiences that exists," said Rent the Runway CEO Jennifer Hyman.
The rise of generative AI is bringing with it a groundswell of interest and concern about how the capability to automatically synthesize information and create something new will change how we work.
Given that AI will sit within the architecture of our digital lives, it’s also worth considering how the technology will introduce new tools for other aspects of life, as well.
For two ecommerce innovators in the apparel space, it’s a time to explore how it will transform shopping. Rent the Runway is set to roll out new AI-powered search capabilities, while Stitch Fix is drawing on a long history with data science and machine learning to personalize the inventory buying process.
Here’s a look at the initiatives underway at each company, and their visions for the future:
Rent the Runway: From search to concierge
Rent the Runway is putting a focus on the customer experience this year as it seeks to retain more subscribers and continue a yearslong push toward profitability.
This is resulting in the introduction of a variety of new initiatives, from the addition of an extra item to all orders to speeding up page load times. Yet as CEO Jennifer Hyman zooms out, she sees change being necessary on an industry-wide level in fashion. Beyond adding new features, AI can play a transformational role.
“I think that fashion ecommerce is one of the most cumbersome customer experiences that exists. You are searching through pages and pages and pages of content to find the items that you like and no one likes doing this,” Hyman told analysts on the company’s earnings call this week. “As an industry that still is selling physical products, AI is going to be -- fashion is going to be a major beneficiary as an industry.”
As a rental service, Rent the Runway has a distinct niche in fashion that lends itself to AI’s advantages, Hyman said. As opposed to a retailer that a consumer may visit a couple of times a year, RTR is used frequently by customers. So Hyman said there are opportunities to turn Rent the Runway into a “utility” by creating a more seamless experience.
This frequent use also provides a “highly unique” dataset, Hyman said. They know what a customer is planning to do based on what they rented. They know whether she liked or disliked an item, and many customers are reviewing 10 items per month. They know her size and how an item fits. This can be put to work in tools that allow customers to ask questions, and find answers.
The first application that combines AI and these advantages will appear in the coming weeks, when Rent the Runway plans to launch a beta of AI-driven search. The tool will allow customers to search for common terms or use cases for an item. So a person will be able to write “Miami vibe,” “‘clambake in Nantucket,” or “tropical motifs,” and receive results about what to wear for such an occasion.
The goal is to help customers sift through the endless aisle, and instantly finds what's right for them.
“I think that across all fashion sites, all over the world, the way that people are searching for product is fairly vanilla, it's fairly functional, right?" Hyman said. "You can go to a site and search for a T-shirt, you can go to a site and search for a black-tie gown. The fact that we're going to be able to enable our customers to search how they actually want to use this closet in the cloud, to search for items to wear to my beach bonfire this weekend, that is a completely different way to search, and I think that it really brings out the value proposition of what a closet in the cloud is all about."
Hyman sees this as a first step in the company using AI models to improve the product experience, and expects more tools to appear in the coming months. RTR is also introducing an SMS concierge experience for onboarding that allows customers to text with a member of the customer service team. The company is already exploring ways that AI can be incorporated into that tool, as well.
In the longer term, Hyman said the company has a vision that will leverage AI to allow customers to communicate with Rent the Runway asynchronously across different modalities, and have a stylist that is constantly available to recommend items, pick out new inventory and answer questions.
“If we are utilizing AI appropriately over the next few years, I see no reason why someone even has to come to our website,” Hyman said.
Stitch Fix: Inventory buying and beyond
Stitch Fix has long married AI with human curation to provide outfits on a subscription basis.
“For years, we have utilized capabilities in generative AI, injecting scores and language into our personalization engines and, more recently, automatically generated product descriptions,” CEO Katrina Lake told analysts. “We have also developed and implemented more advanced proprietary tools such as outfit generation and personalized style recommendations that create a unique and exciting experience we believe is unmatched in the market.”
A new area where the company is applying AI is inventory buying.
“We have historically utilized a number of tools to make data-informed decisions with our inventory purchases,” Lake said. “Now, directly leveraging our personalization algorithms, we have developed a new tool that creates an exciting paradigm shift, which will utilize math scores at the client level to drive company-level buying actions. We expect the clarity of demand signals at the individual client level to drive more proactive and efficient inventory decisions as a company. And because of this, we expect to see higher success rates on fixes and drive increases in keep rates and [average order value] over time.”
Early results are promising. When compared with existing buying tools, testing showed a 10% lift in keep rate and AOV. By the end of this quarter, Stitch Fix expects 20% of all purchase orders to be algorithmically informed.
With experience using AI and a team in place to build, Stitch Fix is investing in the technology. Like Rent the Runway, it also has a unique dataset that offers an immediate advantage.
Here are Lake’s thoughts about how Stitch Fix’s AI strategy:
One of the things that I love about our experience is that we have generative AI that's really in more of a visual format. And so, the outfits that we have in our app, those are actually taking into account your preferences, what we know about you, and then in combination with what we know that you own in your closet. And to be able to kind of continue to push that technology and to be able to continue to give people more value in their experience with Stitch Fix, that's a really good example of, I think, a capability that is, firstly, really aligned with our capabilities around data and personalization and really unique to us.
And then I think it's also really compelling because I really think that pushes us as we think about what that addressable market is. I think if we can push outfits to be something that can be an asset to everybody, I think that is a universal thing that people would love to be able to have, is to have access to advice on a daily basis around what to wear and how to wear it.
While these are distinct companies, their plans lead us to a common conclusion: While the talk around generative AI might be new, many technology-forward companies already have assets sitting inside them that can be leveraged to build new tools. Uncover what’s already there, learn about the AI’s capabilities and develop a solution that's right for your organization. Then, talk to customers to determine how to improve it. It might mean commerce looks different, but that’s okay. The point is to create a better experience.