Conversion
Sessions that become qualifying orders.
Business Domains · Module 15
E-commerce Analytics.
E-commerce analysis connects traffic, merchandising, conversion, basket size, repeat behavior, inventory and returns into one revenue system.
Core idea
Revenue is an outcome. The analyst should explain it through traffic × conversion × order value × repeat behavior.
01
Context
Traffic is up. Revenue is flat.
“We bought more traffic, but sales barely moved. Is the campaign bad or is the store underperforming?”
Start by decomposing conversion, average order value, product availability, customer mix, discounts and returns.
A flat top-line can hide a severe conversion issue or a deliberate shift toward lower-value acquisition.
02
Commerce drivers
Break revenue into the behaviors that create it.
Basket
AOV, items per order and category mix.
Repeat
Purchase frequency and returning-customer share.
Merchandising
Availability, stockouts, discounts, returns and margin.
Rule
Do not celebrate gross sales without understanding discounts, returns and margin.
03
Challenge
Explain why traffic did not become revenue.
Exercise · 20 minutes
Decompose the top line.
- Did conversion change overall and by device/channel?
- Did AOV or item count change?
- Are high-demand products out of stock?
- Did discounts shift product/customer mix?
- Are returns/refunds changing net revenue?
- Did new traffic have lower purchase intent?
04
AI assist
Ask AI for a revenue bridge.
E-commerce diagnostic prompt
Revenue is +1% while sessions are +18%.
Build a diagnostic plan using:
sessions, conversion rate, completed orders, AOV, items/order,
new-vs-returning mix, category mix, stockout rate, discount rate,
refund rate and contribution margin.
Create a revenue-driver bridge.
Separate gross sales from net/contribution outcomes.
Do not assume the marketing campaign caused the gap.05
Validation
The e-commerce checklist.
01
Are traffic and orders measured on consistent windows?
02
Is conversion denominator defined?
03
Are cancelled/refunded orders excluded consistently?
04
Did category or device mix shift?
05
Are stockouts visible?
06
Are gross and net economics separated?
06
Worked takeaway
Explain the revenue equation before blaming a channel.
Confirm the additional sessions are real and comparable.
Find where added traffic fails to purchase.
Check AOV, item count and category mix.
Include discounts, returns and contribution margin.
Analyst habit
A revenue change should be decomposable into a small number of behavioral and economic drivers.