Decoy Pricing
Decoy pricing introduces a deliberately worse third option to make your target tier look like the obvious pick. Here's how it works, when it lifts conversion, and where it backfires.
Decoy Pricing
A pricing tactic that adds a deliberately inferior option to make a target option look like the obvious choice.
Decoy pricing — also called the asymmetric dominance effect — works by introducing a third option that is clearly worse than your target option on at least one dimension, and no better on the others. The decoy is not meant to sell. Its job is to anchor judgment so the target tier looks dominant by comparison.
The canonical example is the Economist subscription test from Dan Ariely's research: a print-only tier priced identically to a print-plus-digital tier flipped buyer preference from the cheap digital plan to the premium combo. In subscription, SaaS, and DTC bundle design, the middle or top tier is usually the one engineered to win, and the decoy sits next to it doing the comparison work.
Decoy pricing is a specific tactic inside the broader field of pricing psychology. Unlike anchoring (which uses a high-priced reference point to make everything else feel cheap), the decoy is structurally similar to the target option but strictly worse on the dimensions buyers compare.
On a Shopify pricing page, the decoy might be a 'Medium' size bundle priced €5 below the Large but containing 40% less product. The Large suddenly reads as the value pick, and average order value climbs. The trick only works when the comparison is easy to make at a glance — three options, simple feature grid, one dominant axis.
Decoy Lift % = ((Target Share With Decoy − Target Share Without Decoy) / Target Share Without Decoy) × 100
Target Share With Decoy
Target option share (decoy present)
% of buyers choosing the target tier when the decoy is in the lineup
Target Share Without Decoy
Target option share (control)
% of buyers choosing the same target tier in a two-option control
An apparel brand A/B tests its bundle page. Control: two bundles (3-pack at €45, 6-pack at €75). Variant: three bundles, with a 4-pack at €72 added as the decoy next to the 6-pack.
6-pack share without decoy: 34%
6-pack share with decoy: 51%
→ Decoy Lift = +50%
The 4-pack 'decoy' at €72 is strictly worse than the 6-pack at €75 (3 cents per unit higher, two fewer units). Adding it shifted half a point of every existing 6-pack buyer plus 17 percentage points of new ones into the target tier.
Real-world lift varies by category. Decoys work best when the buyer is in deliberation mode and comparing on a feature grid; they underperform on impulse purchases where shoppers don't read past the price. Below are typical ranges we see across DTC verticals.
Typical decoy-pricing lift on target-tier share, by category
| Vertical | Without Decoy | With Decoy | Relative Lift |
|---|---|---|---|
| Apparel bundles (Shopify) | 32% | 47% | +47% |
| Beauty subscriptions | 28% | 41% | +46% |
| Electronics accessories | 38% | 44% | +16% |
| Supplements (3-tier) | 30% | 49% | +63% |
| Home goods single-SKU | 35% | 38% | +9% |
Notice supplements and subscription beauty post the strongest lifts — categories where buyers commit to a recurring spend and actively scan tiers before clicking. Single-SKU impulse purchases barely move, because there's no real comparison shopping happening on the page.
Frequently asked questions about decoy pricing
Anchoring uses any high-priced reference (often the most expensive tier) to make adjacent prices feel reasonable. Decoy pricing is more specific: the decoy is engineered to be strictly worse than the target option on at least one dimension, with the goal of making the target look dominant. All decoys anchor, but not all anchors are decoys.
It sits in a grey zone. The decoy is a real option a buyer could pick, so nothing is hidden or misrepresented. But you're deliberately structuring the comparison to steer choice. Most CRO teams treat it as acceptable when the target tier is genuinely the best value for most buyers; it becomes manipulative when the decoy steers people away from the option that actually fits them.
Three is the sweet spot. Two options force a direct comparison without room for asymmetric dominance. Four or more dilute the contrast and increase decision fatigue, which often drops conversion overall. If you need more SKUs, group them into three visible tiers and let buyers expand from there.
Adjacent to the target option, visually. If the target is the middle tier, the decoy goes either left or right of it. The decoy needs to be close enough that the eye compares them directly — putting it at the far end of the page weakens the dominance signal.
Yes, in two ways. First, a poorly designed decoy can look like a typo and erode trust ('why is the 4-pack more expensive than the 6-pack?'). Second, adding a third option increases cognitive load, which can reduce overall conversion even if it shifts mix toward the target tier. Always A/B test rather than assume lift.
Occasionally, usually under 5% of buyers. Some shoppers misread the grid; others have a specific edge-case preference. That's fine — fulfil the order normally. If the decoy starts selling more than 10%, it's not really a decoy anymore and your comparison logic needs reworking.
Pick the tier you want to win (usually the middle 'Pro' plan). Build a decoy next to it that matches on most features but is missing one or two the target has, at a price within 10-15% of the target. The classic move: a 'Starter+' that costs almost as much as Pro but caps users or storage where Pro doesn't.
Run until you hit statistical significance on the primary metric (usually target-tier share or revenue per visitor), with a minimum of one full purchase cycle. For DTC bundles that's typically 2-3 weeks; for higher-consideration SaaS it can stretch to 6-8. Don't call it on three days of traffic just because the lift looks big.
Less reliably. Repeat buyers already know what they want and skip the comparison grid. Decoys earn most of their lift on first-time visitors who are actively deliberating. If most of your revenue is from returning customers, the effect size will be smaller than the benchmarks above suggest.
A decoy priced too far from the target (say, the decoy is 30% cheaper than the target) stops being dominated and just becomes the value pick — buyers shift down, not up. Another failure mode: a decoy that's hard to parse, like adding a fourth feature column buyers don't understand. The decoy must be instantly, obviously inferior to the target on a single comparison axis.
Test ideas before you ship them
Run unlimited A/B tests, attach hypotheses to outcomes, and build a searchable archive of what works — and what doesn't.