Description
High cart abandonment rates on our site. Use pandas to analyze the website analytics data and identify where users are dropping out of the conversion funnel.
Technical Requirements
- Load and clean website_analytics.csv
- Create conversion funnel stages: view → product view → add to cart → checkout → purchase
- Calculate conversion rates between each stage
- Segment analysis by device type, traffic source, and user demographics
- Identify statistical significance in drop-off patterns
Acceptance Criteria
- Working pandas funnel analysis code
- Visualizations showing conversion rates at each stage
- Breakdown of performance by segment (device, source, demographics)
- List of specific technical improvements based on analysis
Attachments
Priority
P1 (High)
Estimated Size
M
Additional Notes
This analysis will directly inform our Q2 website optimization initiatives. Focus particularly on mobile conversion patterns as we've seen a growing proportion of traffic from mobile devices.
Questions
- Should we focus on specific geographic regions?
- Is there a particular segment we suspect is having the most trouble?
- Are there specific time periods we should analyze separately (e.g., weekends vs. weekdays)?
Potential Task Range
This task could be split into smaller tasks:
- Data cleaning and initial funnel visualization
- Segmentation analysis by device type
- Segmentation analysis by traffic source
- Segmentation analysis by demographics
- Statistical validation and recommendation development
Task Request (ACK)
High cart abandonment rates on our site. Use pandas to analyze the website analytics data and identify where users are dropping out of the conversion funnel.
Technical Requirements
Load and clean website_analytics.csv
Create conversion funnel stages: view → product view → add to cart → checkout → purchase
Calculate conversion rates between each stage
Segment analysis by device type, traffic source, and user demographics
Identify statistical significance in drop-off patterns
Acceptance Criteria
Working pandas funnel analysis code
Visualizations showing conversion rates at each stage
Breakdown of performance by segment (device, source, demographics)
List of specific technical improvements based on analysis
Description
High cart abandonment rates on our site. Use pandas to analyze the website analytics data and identify where users are dropping out of the conversion funnel.
Technical Requirements
Acceptance Criteria
Attachments
Priority
P1 (High)
Estimated Size
M
Additional Notes
This analysis will directly inform our Q2 website optimization initiatives. Focus particularly on mobile conversion patterns as we've seen a growing proportion of traffic from mobile devices.
Questions
Potential Task Range
This task could be split into smaller tasks:
Task Request (ACK)
High cart abandonment rates on our site. Use pandas to analyze the website analytics data and identify where users are dropping out of the conversion funnel.
Technical Requirements
Load and clean website_analytics.csv
Create conversion funnel stages: view → product view → add to cart → checkout → purchase
Calculate conversion rates between each stage
Segment analysis by device type, traffic source, and user demographics
Identify statistical significance in drop-off patterns
Acceptance Criteria
Working pandas funnel analysis code
Visualizations showing conversion rates at each stage
Breakdown of performance by segment (device, source, demographics)
List of specific technical improvements based on analysis