Tool · Layer 2: Try it
Will your price change pay off?
A discount needs more sales. A price increase can tolerate fewer. Find the tipping point before you decide.
New here? Walk me through it (5 minutes) →
Your starting point
Use one product and the same selling period throughout.
A planning average is fine, e.g. 37.5 a week. Keep the same period for every quantity.Add the costs you incur per sale. For example, $13 to buy the item plus $2 to fulfill the order gives $15 per unit before any shipping subsidy or expected return costs. Enter percentage fees separately.Fees, campaign costs & stock
Charged on each option’s own selling price, so they fall when you discount. Exclude sales tax and anything already in the unit cost. Fixed per-order fees, tiered fees and channel-specific rates are not modelled.Added to every option equally, including one at today’s price. The baseline — no price change, no campaign — never includes it.Physical units you can sell this period (whole number). A simple cap: if stock arrives during the period, timing needs a separate review.Prices to compare
What would need to happen?
You don’t need a demand forecast to calculate the hurdle: the units each option needs to maintain today’s contribution.
How much could sales change?
Give each price its own range.
Not sure? The hurdles above are still useful. You can explore ranges without treating them as forecasts.
Enter a lower and upper change in unit demand versus baseline for each candidate. The example ranges are hypothetical—not estimates from your sales history. “−10%” means 10% fewer units; “20%” means 20% more.
| Candidate | Fulfilled units | Contribution* | vs baseline |
|---|
These are outcomes within your assumptions, not confidence intervals. A range that looks safe is useful only if its assumptions are credible.
How can I choose a sensible range?
Start with comparable in-stock periods, noting price, traffic and promotion changes. Check equivalent competitor offers and stock availability. Use a broad range when evidence is weak, and include outcomes that would make you reconsider.
A before/after sales change is a starting clue, not proof of price response. It is fine to leave this section off and use the hurdles to design a bounded test.
Turn the calculation into a decision
Know the hurdle. Then investigate the response.
- Check the economics. Reconcile realized prices, fees and returns.
- Check the market. Compare equivalent delivered offers and availability. Consider why customers choose you.
- Choose a bounded test. Record price, sales, availability, traffic and other promotions. Review contribution and related-product effects.
What would a deeper pricing review add?
Evaluate your sales history, competitive position, promotion design and inventory constraints; then select prices worth testing and an appropriate comparison. A sales change alone does not identify the effect of price.
The assumptions explainer sets out what this calculation does and does not cover.