I had an opportunity to attend the Retail Value Chain Federation Spring Conference last week in Teaneck, NJ and co-present with Mark Lightbody, a Partner at Newmine, on the topic of “Leveraging AI (Artificial Intelligence) and ML (Machine Learning) to reduce consumer Returns.” Mark and I also presented the first of an education series for RVCF on “Building a Strong Defense Against Rising Returns”.
RVCF brings retailers and vendors together throughout the year to solve supply chain problems and grow profits. The agenda included many Supplier Only and Retailer Only forums to address key challenges the industry faces as the industry transforms, such as drop shipping or growing merchandise returns.
One of the highlights of the conference was a full-day workshop that familiarized attendees with Design Thinking methodology, a human-centered approach to problem-solving that focuses on approaching a problem through the eyes of the end-user, or the customer. The workshop was intended for those who manage returns from consumers and direct to consumer shipments. The workshop was moderated by Jeff Warren, President and Founder of Barkley Consulting.
Why Design Thinking?
Design Thinking is a customer-focused, solution-based approach to problem-solving that is divided into a series of iterative phases. It enables the problem solver to challenge their own assumptions and redefine problems to identify creative, alternative solutions to the problem. It is a way of thinking as well as a series of hands-on processes that Include the following stages:
Jeff divided the group into three project teams and taught Design Thinking concepts and techniques such as: how to use open-ended questions when interviewing end-users to collect valuable insights. Each team was challenged to move through the design thinking process to uncover consumer insights and then ideate solutions, prototype them, and test them.
The Design Thinking Challenge
“Rethink the Returns Process to Provide Better Value to Consumers and Increased Benefits to Retailers and Manufacturers”
Our project team focused on one of the leading causes of returns: Inaccurate Product Descriptions, which are often vague or incomplete. We conducted interviews with consumers who returned merchandise they had purchased online in the last two weeks, or to the store within the last week. Customers frequently referenced lack of detail in product descriptions for apparel items they returned. The consumer interviews our team conducted provided additional insights on how to improve product descriptions. In addition, the interviews we conducted allowed us to capture several other “voice of the consumer” concerns such as:
- Consumers can be reluctant to share their comments on product reviews because of privacy concerns due to publicizing their personal information on an eCommerce website.
- Retailers who do not have a loyalty program or recognize their loyal customers miss out on the opportunity to personalize the returns experience.
- Consumers feel slighted when brands do not provide loyal customers with the ability to request a return credit against their original method of payment.
With the initial research done, it was time to now prototype. Barry Graff, the COO of www.alpha3pl.com introduced a creative idea to leverage user-generated content (product reviews) to improve product descriptions, similar as to how an individual can contribute to a wiki. Call it a “Product Description Blockchain”. As consumers share their insights on why they like or do not like an item, key product description attributes could be automatically updated. The manufacturer of the item could accept or reject the additional description identifiers.
All the solutions that were prototyped included Artificial Intelligence (AI) and Machine Learning (ML) elements. Another innovative idea featured an online Concierge Chat Bot guest order assistant. The Chat Bot guest order assistant was non-invasive and designed to enhance the online shopping experience. The Chat Bot leveraged both AI and ML to review prior orders and the customers return history plus the customer’s body profile information maintained online. The Chat Bot suggested that there were items the customer had placed in their shopping cart that may not be the “perfect fit”, prior to checkout, or would recommend substitute brands that would better fit.
If multiple sizes of the SKU were ordered (which is commonly referred to as “bracketing”) then the ChatBot might even flag the order to be held to engage a “fit expert” after order capture, especially if this was the very first order. The “fit expert” could reach out and request additional body dimension data before shipping the order or allow the customer to upload a picture of the front and side view of their body profile to ensure the retailer was shipping a product that would fit. The logic being, that if online retailers spend more time with the consumer at the beginning of the relationship, and if we can allocate more time to making sure the items ordered will be the “right fit,” then we can minimize returns.
The three different teams prototyped solutions to address the rising returns challenge. What amazed me was the quality of the solutions that the project teams created after spending only one day together in a moderated session on Design Thinking. If we were presenting to private equity investors…I’m sure a few of the prototypes would have generated an investment interest.
Newmine has adopted many core Design Thinking principles into the product conception, creation, and launch of Chief Returns Officer, the Returns Reduction Platform. We partnered with several retailers, beginning in 2004, and captured their interview comments, insights, and the key business challenges when managing returns.
We encourage both brands and retailers to conduct a historical Look Back Analysis of all return transaction data and user-generated content (product reviews) by Vendor, Brand, and Style. Leverage the vendor insights we provide to collaborate with your suppliers during 1:1 sessions at the RVCF fall conference, November 3-6th, in Scottsdale, AZ.
For additional information on how to think outside the box for new remedies to stem the flow of returns from consumers, or to schedule an overview of how the two (2) year Look Back Analysis can be leveraged in 1:1 sessions with your trading partners, please contact Felton Lewis firstname.lastname@example.org or Mark Lightbody email@example.com.
Author: Felton E. Lewis IIII
Felton has 30+ years of experience helping CPG, Retailers, and 3PL’s recognize business value from their investment in ecommerce, OM, WMS, and Store Fulfillment technology.
Felton established a twelve-year supply chain footprint in line level management with the Kellogg Company in Distribution, Manufacturing and Corporate Logistics. He led the rollout of the Kellogg WMS and OM to several outsourced logistics providers (EXEL, DSC, and GATX). Felton led the design and delivery of the Kellogg Distribution Management System, as well as several efficient consumer response initiatives in the grocery industry between Kellogg’s and its retail trading partners.
Felton established a twelve-year technology footprint with YANTRA, a tech startup that launched DOM (Distributed Order Management), as well as AT&T, IBM, eBay Enterprise. He led the early adoption of DOM deployments in the Retail space with Walmart, Circuit City, Academy Sports, WMS deployments with Eaton, Motorola, Honeywell, and in the 3pl space with EXEL Logistics, APL, and FedEx.
Felton heads up alliances and business development for Newmine, a commerce optimization consulting company that has partnered with RVCF to help retailers understand the root cause of the consumer returns. Felton’s MBA is in International Logistics at Georgia Institute of Technology and residences completed in the UK, APAC, and LATAM.
This blog originally posted on Felton E. Lewis IIII’s LinkedIn Blog