Cart abandonment is one of the most frustrating problems in ecommerce.
You can see it in analytics dashboards — users reach checkout, then leave. But knowing that customers drop off doesn’t explain why they leave.
Recently, we looked at a checkout flow that showed strong traffic and consistent add-to-cart behavior — but a significant drop-off at the payment step.
Traditional analytics told us:
Users reached checkout
Many exited before completing payment
What it didn’t tell us was what actually happened during those sessions.
Data shows you what happened.
Execution changes what happens next.
Most ecommerce teams rely on analytics to discover friction — checkout drop-off, rage clicks, payment failures, mobile usability problems.
But once friction is identified, the real work begins:
diagnosing root causes
drafting implementation plans
updating frontend code
adjusting content
verifying improvements
monitoring for regression
This is where many teams stall.
Spyglass360 and ProWorkBench approach the problem from two complementary directions:
Spyglass360 provides behavioral visibility.
Few ecommerce problems are more damaging than payment failures.
When a customer reaches the payment step, intent is high. They’ve:
Chosen products
Entered shipping details
Reviewed totals
If payment fails at that moment, the store doesn’t just lose revenue — it risks losing trust.
The frustrating part? Many payment bugs are hard to reproduce.
Customers report:
“It wouldn’t let me pay.”
But developers can’t replicate the issue.
This is where behavioral replay becomes critical.
Mobile traffic now dominates ecommerce.
For many stores, more than 60–80% of visitors arrive from mobile devices — yet desktop conversion rates still outperform mobile by a wide margin.
The reason usually isn’t pricing, products, or demand.
It’s friction.
Small usability issues that barely register during testing can completely break real purchasing behavior on phones.
Mobile checkout failures rarely appear as obvious errors. Instead, they show up as hesitation, repeated taps, and silent exits.
This guide explains how to identify the most common mobile revenue leaks — and how to find them using real behavioral data.
Cart abandonment isn’t a mystery.
It’s a pattern.
Most ecommerce stores treat abandonment like a statistic:
“Our cart abandonment rate is 68%.”
But that number doesn’t tell you why customers leave.
Session replays and interaction data turn abandonment into something visible — something diagnosable.
This guide walks through the 12 friction signals that repeatedly show up before customers exit.
Every ecommerce store owner knows the feeling:
Traffic looks healthy.
Products are getting views.
Customers add items to their cart…
…and then they disappear.
Checkout abandonment is one of the biggest hidden revenue leaks in ecommerce. The problem isn’t just that customers leave — it’s that most stores don’t know exactly where or why they leave.
Traditional analytics tell you that users dropped off.
Behavior analytics shows you what actually happened.
This guide walks through how to identify the precise checkout step costing you sales — and how to diagnose the real cause behind it.