User Behavior Path Analysis and Shopping Experience Optimization on Orientdig Using Spreadsheets

Data Collection Methodology

Orientdig, an e-commerce purchasing agent platform, employs data tracking points across website pages to systematically capture user interaction data in spreadsheets. Three primary datapoints are collected:

Browsing Behavior: Page views, dwell time, button clicks, and scroll depth
Search Queries: Keywords used, frequency of searches, and null-result searches
Cart Actions: Item additions/removals, checkout initiations, and abandoned carts

Path Visualization and Analysis

Using spreadsheet tools (Google Sheets/Excel), the team:

Creates user flows with timestamped event sequences
Calculates conversion rates between key pages (landing→product→cart→checkout)
Identifies drop-off points where ≥40% of users exit the funnel

Sample user path heatmap showing high-exit pages — Visualization of user navigation patterns (higher exit rates shown in red)

Optimization Implementation

Spreadsheets enable quantitative prioritization of improvements:

Problem Area	Solution	Impact Metric
28% cart abandonment at shipping info	Auto-fill address for registered users	↓12% abandonment
400ms product image load delay	Compress images to ≤200KB	↑0.8s page speed

Performance Outcomes

Over 3 optimization cycles (90-day intervals):

+22% Checkout completion

17%↓ Support tickets

"Spreadsheet analysis revealed that simplified payment options (adding Alipay/WeChat) reduced mobile user frustration by 31%" - Orientdig UX Lead