THE TEAM
Sunny Lee - Interaction Designer, Information Architect
Serrah Sawers - User Researcher
Shruti Arora - Visual Designer, Project Manager
DURATION
1.5 Weeks
CLIENT
Macy's - Conceptual Client
TOOLS
Sketch, InVision, Omnigraffle, Pen & Paper, Post-Its, Whiteboard, Keynote
PLATFORM
iPhoneX, iOS
OVERVIEW
In a last ditch effort to stay in business, Macy’s sold 100 stores in early 2017 and reinvested $250 million into their digital departments. Finding it difficult to compete with Amazon's low overhead, Macy’s is looking for solutions to grow online sales.
PROBLEM
Having a loyal customer base in their upper 40's, which represents roughly 50% of Macy's annual revenue, our priority was to re-engage this market by simplifying their existing information architecture. In order to continually attract new customers, we had to also consider the primary motivation for shoppers ages 24-35 years old - cost.
Group fact finding mission led by user researcher Serrah Sawers
First look at Macy's original application and browsing screen flow.
User journey mapping pain points
GOALS
To create a user interface that's more accessible to capture a wider range of potential customers. We wanted to add value to the application by creating a personalized shopping experience that would connect users with products that resonated with them at an economic price point.
SOLUTIONS
To create a more efficient application, we streamlined the menu options to four essential app services that we then housed in an ever-present tab bar.
Based on the cumulative information gathered from users' profiles, order history, and searches we crafted a machine learning experience that would continually produce focused product suggestions to anticipate shoppers' behaviors.
We enhanced the wish list feature to allow price-sensitive customers to input values that would generate price alerts and cost comparisons with competitors.
Progression of generic landing page upon sign-up to personalized landing page once preferences are learned.
Mid-fidelity wireframes of wish list with price alert and cost comparison feature.
KEY PERFORMANCE INDICATORS
10-15% or more in online sales growth over the next quarter
Total number of purchases based on price alerts and comparisons
Amount of orders placed based on machine-learning recommendations vs. product searches
Visual designs by Sunny Lee, 2 weeks after project completion
NEXT STEPS
Build interface to search and compare competitors’ prices and inventory.
Expand upon their existing camera recognition software and integrate it into the search navigation.
Create framework for promoting and managing loyalty and rewards points.
CONCLUSION
Macy's is faced with the daunting task of modernizing their online presence to appeal to current customer shopping habits. Financially dependent on their loyal, older demographic of customers, our approach was to expand our outreach by simultaneously addressing the needs of their existing customer base, while attracting a new target market of millennials. The price-alert feature that would be appealing to a broad clientele, also has the potential of informing future pricing strategies. Our process, to design an application that would satisfy the needs of the broader market, led us to building a creative and holistic solution at the intersection of a user need and business goal.
CASE STUDIES
BESPOKE SERVICES
SHARED VISION
SMART CAMPUS
PERFECT MATCH