Evaluating Ezbuycn's Shopping Agent Campaign Performance on Spreadsheets & Optimization Strategies
2025-04-24
This analysis evaluates the sales promotion campaign data of Ezbuycn's shopping agent service recorded in spreadsheets, examining its impact on sales volume, revenue growth, and customer engagement metrics. The assessment combines quantitative data visualization with actionable recommendations for campaign improvement.
I. Data Analysis Methodology
- 1. Core Metrics Tracking: Created pivot tables comparing baseline vs promotion period for:
- • Daily order volume (+37% MoM)
- • Conversion rates (22% increase)
- • Average basket size (+US$18.50)
- 2. Funnel Visualization: Used stacked bar charts to identify dropout points in:
- • Landing page clickthroughs
- • Cart abandonment rates
- • Payment completion
II. Campaign Strengths Identified
1.9X revenue multiplier
III. Areas Requiring Improvement
| Issue | Data Evidence | Impact Level |
|---|---|---|
| Website performance lag | 23% slower load time during peak traffic | High (11% abandonment) |
| Mobile UX friction | 38% lower conversion on mobile vs desktop | Medium |
| Clearance item depletion | 72% of featured items sold out in <2h | High (lost goodwill) |
IV. Actionable Optimization Recommendations
A. Campaign Structure Adjustments
- Implement wave‑based flash sales
- Add price‑matching guarantee
B. Data-Driven Targeting Improvements
- Segment buyers by:
- • Frequent agents→VIP perks
- • Strategic coupon distribution
C. Interface Optimizations
- Redesign mobile checkout with one‑tap address reuse
- Add live stock counter
Implementation Roadmap Priority
Based on ROI projections from spreadsheet models, prioritize:
- 1. Server capacity upgrade (3-week implementation)
- 2. Mobile UX fixes (2-week sprint)
- 3. Intelligent coupon targeting (4-week development)