Diagnose Query Failures in an E-Commerce Search Box
Overview
What this challenge is about.
Cluster e-commerce search failures from 480M query logs, quantify revenue impact, and propose fixes. Earn a verifiable certificate.
The scenario
The retailer (~165,000 staff, ~EUR 35bn revenue) is migrating its tech stack toward more AI; the search team owns conversion on the product-discovery surface.
The Brief
What you'll do, and what you'll demonstrate.
Find and quantify the dominant failure modes behind the failing 3% of search queries, with prioritized fixes.
Earning criteria — what you'll demonstrate
- Profile a real query log for failure modes
- Cluster queries and tag the dominant failure mechanism per cluster
- Quantify revenue impact of each failure cluster
- Translate IR failure analysis into prioritized engineering work
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Query Log Analysis
Apply query log analysis to solve real industry problems and demonstrate production-level capability.
- Clustering
Apply clustering to solve real industry problems and demonstrate production-level capability.
- Ir Failure Analysis
Apply ir failure analysis to solve real industry problems and demonstrate production-level capability.
- Ir Evaluation
Apply ir evaluation to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Revenue Impact Modeling
Apply revenue impact modeling to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Data Scientist
Query-log analysis with quantified revenue impact is the day-to-day of data scientists embedded with search and discovery teams.
This challenge sharpens
- query-log-analysis
- clustering
- revenue-impact-modeling
NLP Engineer
Translating failure-mode analysis into typo, synonym, and query-expansion work is what NLP engineers ship next at any e-commerce search team.
This challenge sharpens
- query-log-analysis
- ir-failure-analysis
- ir-evaluation
AI Product Manager
Owning the prioritized fix list with cost estimates is the AI PM's job on any search-and-discovery surface.
This challenge sharpens
- ir-failure-analysis
- revenue-impact-modeling
- clustering