Auditable formula · fictional example
Average Customer Shipping Price: Pass-Through Measurement
Direct answer: Average customer shipping price divides net shipping charges collected from customers by orders charged for shipping. It measures checkout price, not carrier cost, internal logistics cost, or service quality.
Numerator
R$72,000 net shipping charges collected
Denominator
6,000 orders charged for shipping
Fictional result
R$12.00 average customer shipping price
Formula and worked example
Average customer shipping price = net customer shipping charges / charged orders
Fictional example: R$72,000 of net customer shipping charges / 6,000 charged orders = R$12.00 average shipping price.
The numbers demonstrate the calculation only. They are not a benchmark, forecast, target, vendor result, or promise.
Four-step measurement method
- Step 1
Separate customer shipping charges from product revenue and taxes consistently.
- Step 2
Count charged orders and classify free-shipping promotions separately.
- Step 3
Compare the same lane, package profile, service level, and period.
- Step 4
Report operating cost and service outcomes alongside the checkout price.
Checks before comparison
- Discount funding is identified
- Free-shipping orders are not silently mixed
- Tax treatment is consistent
- Lane and service mix are comparable
Common measurement errors
- Calling internal cost a customer price
- Hiding regional increases inside a national average
- Assuming operating savings must be passed through
Attribution boundary
A change in this metric does not prove that AI caused it. Compare a frozen baseline and controlled pilot, then inspect route mix, distance, fuel, tolls, carrier rates, service level, package profile, promotions, weather, exclusions, and policy changes. Protect service and failure metrics while evaluating cost.
Frequently asked questions
Do AI savings automatically lower this price?
No. A company may lower price, protect margin, improve service, expand coverage, or absorb other rising costs. Measure the customer charge directly.
Does this metric prove that AI caused the result?
No. A before-and-after change can also reflect route mix, distance, fuel, carrier rates, package profile, promotions, weather, exclusions, or operational policy. Use a controlled pilot and inspect segments before attributing causality.