Volume Discount Offer

Scale the unit price down as quantity rises, giving buyers a visible reason to order more in a single purchase.

Pro simple Pricing & Packaging Offers

What it adds

The builder reads your unit economics and order history to build a quantity ladder where the per-unit price falls at defined thresholds, each threshold placed just above a common order size. It converts by making the next bracket cheap to reach, so buyers round their order up to capture the better rate. The goal is a higher average quantity per order without changing the product.

What your builder is told to do

The actual instructions, in order.

1
Read the order history and cost source files and plot the distribution of order sizes, marking the clusters where most orders currently land.
2
Place each discount threshold slightly above a cluster, so a typical buyer sees the next bracket as a small step rather than a different scale of purchase.
3
Set the per-unit price at each threshold so total spend always rises with quantity while unit price falls, and verify no threshold creates a point where ordering more costs less in total.
4
Display the ladder with three figures per row, the quantity range, the unit price, and the total, because buyers evaluate volume offers on total spend even when the discount is expressed per unit.
5
Build a proximity prompt in the cart or configurator that tells the buyer exactly how many more units are needed to reach the next rate and what the resulting unit and total price would be.
6
State the conditions attached to volume pricing, including whether quantities must ship together, whether the rate applies to mixed items, and whether it can combine with other discounts.
7
Specify responsive behavior: on mobile, show the buyer's current bracket and the next-bracket prompt above a collapsed ladder; on tablet, render the ladder as a scrollable table with the active row highlighted; on desktop, present a quantity selector beside the full ladder with the active bracket and next-bracket saving highlighted live as quantity changes.

Edge cases it handles

The things an agent skips when you only say "build a volume discount offer".

A buyer ordering just below a threshold should be prompted, but the prompt must not appear so aggressively that it reads as pressure on every quantity.
Partial cancellations after a discounted order need a stated rule for whether the rate is recalculated.
Mixed-item orders require an explicit statement of whether quantities aggregate across items.
Fulfilment or delivery constraints can make very large quantities impractical and need a stated maximum.
If the source files do not include order history, threshold placement is guesswork and must be flagged.

Definition of done

Your builder is required to check every one of these before reporting the work finished.

Threshold placement is justified by the order-size distribution in the source files.
Every ladder row shows quantity range, unit price, and total price.
Total spend increases monotonically with quantity across all brackets.
A proximity prompt states the exact additional quantity needed and the resulting prices.
Aggregation, stacking, and shipping conditions are stated explicitly.
Mobile, tablet, and desktop presentations of the ladder each match the specification.
The builder reports which source files supplied cost and order data, and lists any threshold or rate it set without evidence.

Related offer files

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Separate the one-time work of getting started from the ongoing service, so the monthly figure stays low and the launch is funded.

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Decoy Pricing

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How it works

1

Copy the link

Grab the Markdown blueprint URL for this offer type.
2

Give it to your builder

Paste it into Claude Code, Cursor, Codex, or whatever AI builder is already working in your app.
3

It maps, then builds

Your agent reads the blueprint first, then builds the offer into your app around the product, audience, and stack.

Works with your stack

These blueprints are written to adapt. They tell the agent to detect your framework, match your existing design system, and use your source files instead of guessing the offer.

Need it tighter than that? Customize the offer file and tell it exactly which source docs and stack to use.