Macy's big ticket items

Overview

Based on an initial discovery lab, testing, and technical research, I designed the experience to allow Macy’s customers to purchase big-ticket items online, including furniture and mattresses. A month after launch, we had $1MM in big-ticket online sales with an average order of $1K. We were able to go from 25% to 100% push in 10 days with success.

Background

Believe it or not, up until recently, while shopping for furniture on macys.com, you still had to call customer service to place the order. The process relied on dated legacy systems and complex delivery requirements. Adding the flow to the existing shopping and checkout was no easy feat. The new feature would integrate product details pages, quick views, sign-in checkout, guest checkout, mixed bag, lists, order history, and email messaging. 

Understand the problem

Component model

I worked with the engineering team to understand the systems involved in the process. Two legacy data systems included MCHUB, which captured the online order and initiated the shipping process, and SOCR, which confirmed the item availability and managed the transactions. Later I would discover that relying on these systems would involve compensating for delayed data transfer by surfacing information, like warranty and delivery later in the flow. 

User research

Our research team tested an initial rough prototype to evaluate the user experience of the purchase flow through an unmoderated user study of 10 Macy’s customers who purchased a big-ticket item last year or at a competitor. Our objective was to learn; do customers understand what they need to do, have enough information to make a purchase, and feel confident with their purchase. 

If it’s on backorder, tell me that before I even enter my ZIP code… I don’t see an estimated availability time. I would like to see it on this page [PDP].

Analysis

Most participants found the MVP prototype flow “easy” and “straightforward,” but some customers wanted to see availability, warranty, and delivery info earlier. While mixed bags posed a few significant usability issues, customers lacked vital information that could push a purchase decision at this point.

Easy to do, particularly if you don’t have any questions.

Scoping

The technology team recommended investing time into the enterprise interfaces before the project started. They learned that the existing SOCR interface would work but require additional time to write new code. For the front-end experience, I would be working on a web application for furniture and mattresses. The flow would cross Product Detail Pages (PDP), lists, bags, and the checkout experience. Operational emails would come later.

Defining the problem

We believe that customers who browse and view big-ticket items online are frustrated that they cannot also purchase such items.

So, if we enable big-ticket checkout, then we can provide customers with a convenient and straightforward online purchase experience,

Resulting in satisfied customers and incremental sales in the category

KPI’s

• Incremental annual sales
• NPS
• Add to bag and checkout conversion
• Call center expense
  

Design the solution

Sketches

I mapped out a rough map as a guide that incorporated all the sections this new experience would touch. I sketched out the user flows to account for the messaging and interactions that would appear on the pages. 

Wires

Dropping the experience into the current site experience was used for presentations and testing the flows to make sure I included the requirements. The wires are a reference for visually branding the user interface and the copy team to optimize the UI copy.

Design

I mocked up every iteration and annotated the flow for both the desktop and mobile flow as macys.com was currently an adaptive experience. A user could shop for indoor and outdoor furniture and mattresses online with the new venture, similar to other products. Through a Product Detail Page (PDP) quick view, users could enter their zip code to check the inventory and shipping availability for PDP collection. The user could now choose to ship or pick up the furniture if available in their preferred store in the bag. In the checkout flow, users would be able to select protection plans, pay for state-specific fees and provide shipping instructions.

Validating the solution

Development

I worked closely with developers to implement the flow as designed with redlines. I supported the engineering team through QA and the launch of the product. 

Final

Results and takeaways

• After the first month, our Big-Ticket Sales resulted in $1MM
• The average order value was $1.1K
• The checkout rate is 13%, and the direct checkout to order rate was 33%
• Mobile users represented 46% of the sessions
• Desktop users represented 95% of those that added to the bag (ATB)
• Desktop represents 88% of the direct to checkout sessions
• I learned that legacy technology could get in the way of the ideal solution; however, getting the feature out to test and learn is more effective than perfection
• Always consider legal regulations by state. In the case of this experience, there were state-specific mattress fees for Rhode Island, Connecticut, California, and all the rest.
• Mattresses come in a standard, low profile, and low-profile split type, which adds selection options for the PDP pages.
• It takes a team to move mountains

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