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
Snapchat Self-Serve Ad Manager (Early Versions)
AdTech
Snap Inc.
The early versions of the self-serve ad tool faced technical bugs and lacked advanced features for advertisers.
WHAT WENT WRONG
Limited targeting options compared to competitors like Facebook
Technical bugs in the ad creation process
SIGNALS MISSED
High support requests due to technical issues
Advertiser feedback highlighting missing features
HOW COULD THEY HAVE AVOIDED THIS
Conducting extensive beta testing with key advertisers
Expanding targeting and reporting functionalities
TEAMS INVOLVED
Product, Engineering, Customer Success, Marketing
Twitter Promote Mode
AdTech
A subscription-based ad service failed due to lack of customization and poor ROI for advertisers.
WHAT WENT WRONG
One-size-fits-all approach to ad targeting
Limited control for advertisers over audience and content
SIGNALS MISSED
Negative feedback about poor ROI and low engagement
Low subscription renewal rates among advertisers
HOW COULD THEY HAVE AVOIDED THIS
Offering more targeting flexibility and customization
Testing with pilot users before full-scale release
TEAMS INVOLVED
Product, Engineering, Sales, Customer Success
Rocket Fuel AI Ad Optimization
AdTech
Rocket Fuel
Promised to optimize ad delivery with AI but faced criticism for delivering low-quality placements and lack of transparency in how AI worked.
WHAT WENT WRONG
Weak AI algorithms that prioritized volume over quality
Lack of transparency about AI decision-making processes
SIGNALS MISSED
Complaints about low-quality ad placements
Declining ROI for advertisers using the platform
HOW COULD THEY HAVE AVOIDED THIS
Testing AI with real-world campaigns before scaling
Providing transparency into how ad optimization decisions were made
TEAMS INVOLVED
Product, Engineering, AI, Sales
Yahoo Gemini
AdTech
Yahoo
A native advertising platform that failed to gain traction due to limited reach and poor targeting capabilities.
WHAT WENT WRONG
Weak ad targeting algorithms
Poor user interface for campaign management
SIGNALS MISSED
Low advertiser engagement compared to competitors
Rising customer complaints about poor targeting accuracy
HOW COULD THEY HAVE AVOIDED THIS
Improving algorithmic precision for ad delivery
Enhancing the platform’s usability for advertisers
TEAMS INVOLVED
Product, Engineering, Marketing, Sales
AppNexus Video Ad Server
AdTech
AppNexus
Struggled to compete in the video ad market due to limited features and unreliable ad serving for large campaigns.
WHAT WENT WRONG
Technical instability during video ad delivery
Failure to match advanced features offered by Google Ad Manager
SIGNALS MISSED
Reports of glitches in video playback and delivery
Customer churn to competitors offering more robust tools
HOW COULD THEY HAVE AVOIDED THIS
Ensuring stable ad delivery infrastructure before launch
Adding advanced video targeting and reporting features
TEAMS INVOLVED
Product, Engineering, QA, Customer Success
Facebook Attribution Tool
AdTech
Facebook (Meta)
Struggled to provide accurate attribution insights due to limited cross-platform tracking capabilities.
WHAT WENT WRONG
Overreliance on Facebook-centric data without integrating third-party platforms
Poor accuracy in multi-touch attribution
SIGNALS MISSED
Advertisers reported discrepancies in attribution data
Low adoption rates among large agencies
HOW COULD THEY HAVE AVOIDED THIS
Building stronger cross-platform tracking capabilities
Collaborating with third-party platforms for attribution models
TEAMS INVOLVED
Product, Data, Marketing, Customer Success