What Went Wrong...
Examining the missteps of various software products across industries reveals common pitfalls that can derail even the most promising innovations. From inadequate market research and poor user experience design to insufficient testing and failure to adapt to technological advancements, these challenges underscore the importance of thorough planning and execution. The following section outlines specific cases, offering insights into how these factors contributed to their downfall and the lessons that can be gleaned to inform future endeavors.
Available Lessons:
200
ASOS AR Try-On Tool
FashionTech
ASOS
An augmented reality tool to let users virtually try on clothing failed due to poor usability and limited realism in its outputs.
WHAT WENT WRONG
Poor accuracy in virtual try-on sizing and fit
Limited device compatibility for users
SIGNALS MISSED
Negative user feedback about the accuracy of try-ons
Low engagement rates compared to other product features
HOW COULD THEY HAVE AVOIDED THIS
Refining AR algorithms for better accuracy in sizing
Conducting usability testing across a broader range of devices
TEAMS INVOLVED
Product, Engineering, Design, Marketing
Rent the Runway Unlimited (Early Versions)
FashionTech
Rent the Runway
The subscription service struggled with inventory management and fulfillment delays, leading to customer dissatisfaction.
WHAT WENT WRONG
Poor backend systems for tracking inventory and logistics
Inability to meet demand spikes during peak seasons
SIGNALS MISSED
Customer complaints about delayed shipments and availability
High churn rates among subscribers
HOW COULD THEY HAVE AVOIDED THIS
Investing in robust inventory management software
Scaling operations gradually with proper forecasting
TEAMS INVOLVED
Product, Operations, Customer Success, Engineering
J.Crew Mobile Checkout
RetailTech
J.Crew
A mobile checkout system was discontinued due to technical bugs and low adoption by in-store staff.
WHAT WENT WRONG
Technical issues during payment processing
Resistance from store employees to adopt the system
SIGNALS MISSED
Reports from staff about unreliable functionality
High customer frustration with failed transactions
HOW COULD THEY HAVE AVOIDED THIS
Conducting usability testing with store staff before launch
Offering better training and support for employees
TEAMS INVOLVED
Product, Engineering, Customer Success, Operations
Farfetch Curate AI
FashionTech
Farfetch
An AI-driven personalization feature failed to resonate with users due to poor recommendations and a lack of transparency in the algorithm.
WHAT WENT WRONG
Weak AI model training on diverse fashion preferences
Lack of explainability for how recommendations were made
SIGNALS MISSED
Low engagement rates with recommended items
User feedback about irrelevant or repetitive suggestions
HOW COULD THEY HAVE AVOIDED THIS
Testing AI models with real customer data before scaling
Adding options for users to customize recommendations
TEAMS INVOLVED
Product, AI, Engineering, Customer Success
Nordstrom Personal Stylist App
RetailTech
Nordstrom
The app, designed to connect customers with in-store stylists, failed due to low engagement and poor scheduling functionality.
WHAT WENT WRONG
Weak user interface for booking appointments
Poor integration with stylist availability
SIGNALS MISSED
Low adoption rates among customers and stylists
Feedback about scheduling errors and app crashes
HOW COULD THEY HAVE AVOIDED THIS
Conducting iterative testing with both customers and stylists
Streamlining scheduling workflows for better usability
TEAMS INVOLVED
Product, Design, Customer Success, Operations
Memory Mirror
RetailTech
Neiman Marcus
A smart mirror that allowed customers to try on clothes virtually failed due to high costs and low adoption.
WHAT WENT WRONG
Poor ROI for the high-cost technology
Limited consumer interest in the in-store experience
SIGNALS MISSED
Low customer engagement with the mirror
Complaints from stores about the cost-to-benefit ratio
HOW COULD THEY HAVE AVOIDED THIS
Testing with a larger audience to gauge interest
Offering lower-cost versions for wider rollout
TEAMS INVOLVED
Product, Operations, Marketing, Design