E-Commerce Funnel Analysis
I analyzed two months of shopping activity to understand where customers were leaving before purchase. Across 109.9 million events, the largest loss happened before shoppers added a product to their cart, while a second opportunity appeared among people who carted but never completed an order.
Overview
The Business Question
Millions of people viewed products, but only a small share completed a purchase. The important question was not simply how many left, but where they left and which part of the shopping experience offered the clearest opportunity to improve.
What I Looked At
I followed shoppers from product view to cart to purchase, then compared behavior across product categories, price levels, weekdays, weekends, and the two months in the dataset. I also looked for purchases that did not follow the expected cart path.
Where Shoppers Leave the Journey
The largest loss happened between looking at a product and deciding to add it to the cart. That made product-page engagement the first part of the journey worth improving.
The cart held roughly $345M in products that were not purchased. That is an upper-bound estimate, not guaranteed recoverable revenue, but even a small improvement could matter.
What the Data Revealed
Product Pages Were the Main Bottleneck
Only 19.8% of people who viewed a product added something to their cart. Improving product information, trust, and relevance should be tested before redesigning the entire checkout.
Cart Recovery Was Still a Large Opportunity
About 46.3% of shoppers who used the cart did not go on to purchase, giving the business a clear audience for reminder and recovery tests.
Some Customers Followed a Different Path
Nearly one in five purchasers had no recorded cart event. That could reflect a “Buy Now” experience or another direct-purchase route that deserved separate analysis.
Weekend Performance Was Worth Testing
Weekend activity showed stronger observed conversion than weekday activity. The pattern was useful for planning a test, but the data alone did not prove that weekends caused the improvement.
How I Worked Through It
The Work Behind the Recommendation
Recommended Tests
Start with the biggest measurable opportunities, learn what changes behavior, and expand only after the results are clear.