Is your middle tier secretly killing upgrades?
Decoy Score is a pricing-decision calculator that computes an Asymmetric Dominance Index (ADI), 0–100, from your actual tiers. It runs four cited behavioral-economics tests in real time and tells you whether your middle tier is a working decoy that pushes buyers up — or a leak quietly making your top tier look overpriced. It is the only tool that scores all four conditions against your own numbers and returns one specific fix.
The decoy ("asymmetric dominance") effect was established by Huber, Payne & Puto (1982) and popularized by Dan Ariely's Predictably Irrational (2008). We turn it into a number you can act on.
Paste your tiers. Get the autopsy.
Add 2–4 tiers with monthly prices and up to 8 features each. Score numeric features (e.g. seats, GB, projects) or use 1 / 0 for on / off. Everything computes live — no login, nothing stored.
Tip: the middle tier is the one you want buyers to reject in favour of the top tier. Decoy Score tests whether your numbers make that happen.
Add tier data to begin.
8 real SaaS pricing pages, scored
Pre-computed ADI scores using the same four-condition model. Sorted high to low.
All eight scores estimated from each company's public pricing page as of Q1 2026 using Decoy Score's four-condition model. Prices and structures change; recompute against the live page for current numbers.
Decoy Score vs. everything else
Indie SaaS founders lose deals to competitors whose pricing pages are psychologically engineered, but they cannot diagnose why their own page underperforms. The ADI replaces "this feels off" with a defensible number and a single highest-leverage change.
How the ADI is computed
The score is the sum of four sub-scores, each 0–25, totalling 0–100. Each condition maps to published behavioral-economics research. Computed transparently from your inputs — nothing is hardcoded for live results.
- 1. Price Ratio Test (0–25). The middle tier price should sit at 55–75% of the top tier price to trigger the compromise effect. Inside the band scores full marks; the score falls off linearly outside it. Source: Dan Ariely, Predictably Irrational (2008), Ch.1 — the Economist subscription experiment — plus the compromise-effect literature (Simonson 1989, Journal of Marketing Research).
- 2. Feature Asymmetry Score (0–25). The middle tier should share ≥70% of the top tier's headline features to create perceived near-parity. We compute overlap from your feature values. Source: Huber, Payne & Puto (1982), Journal of Consumer Research — the original asymmetric-dominance paper.
- 3. Value-Per-Dollar Gradient (0–25). The top tier should deliver ≥2.5× the value-per-dollar of the middle on at least two headline (numeric) features, so upgrading reads as obviously worth it. We compute (feature value ÷ price) ratios per feature.
- 4. Dominated Option Condition (0–25). The middle tier must be strictly worse than the top on every dimension where it is close in price — the formal definition of asymmetric dominance. We flag any feature where the middle matches or beats the top while priced near it. Source: Huber, Payne & Puto (1982).
On the "3-tier converts ~20% better" claim
The widely cited figure that 3-tier structures lift conversion versus 2-tier is an industry estimate, not a single peer-reviewed result. The underlying mechanism (compromise + decoy effects) is well-established in the cited journal papers above. For the conversion framing specifically, see Price Intelligently / ProfitWell pricing analyses and Stripe's SaaS pricing guide. We present it as a directional benchmark, not a precise law.
Questions founders actually ask
What is a decoy pricing tier and which SaaS companies use it effectively?
A decoy tier is a deliberately weaker, near-priced option whose only job is to make a target tier look like the obvious choice (asymmetric dominance, Huber, Payne & Puto 1982). Among the pages we scored, Intercom (ADI 83), Figma (78) and Airtable (71) use it effectively — the cheaper-but-clearly-inferior middle pushes buyers to the tier above. Linear (44) and Basecamp (22) do not, because they lack a true dominated middle.
How does a competitor use psychological anchoring on their pricing page and how do I counter it?
Most anchor with a high "Enterprise / custom" tier on the right so every other price reads as cheap by comparison, then place the tier they want sold immediately left of it. Counter it by anchoring your own top tier visibly, then engineering your middle tier as a decoy: keep it at 55–75% of your top price and strictly inferior on two headline features. Run both pages through Decoy Score and compete on ADI, not on raw price.
What pricing psychology tricks do top SaaS companies use on their pricing pages?
The recurring ones: a decoy middle tier, an annual anchor ("billed yearly, save 20%"), a "most popular" highlight on the target tier, charm pricing ($12 not $15), and a custom Enterprise anchor to inflate the perceived ceiling. The decoy is the only one Decoy Score measures, because it is the only one that depends on the math between your tiers rather than on copy.
How do I structure my SaaS pricing page to win against a cheaper competitor?
Do not race the cheaper competitor to the bottom. Add a tier above your target so the competitor's price becomes the floor, not the reference. Make your target tier the compromise choice and your middle tier the decoy that makes the target look efficient. Lead with value-per-dollar on the two features your buyer cares most about — a ≥2.5× gradient (sub-score 3) does the persuading.
How do I write a SaaS pricing page that reduces loss aversion and increases upgrades?
Frame upgrades as avoiding loss, not gaining extras ("Don't lose your data after 30 days" beats "Get 1 year retention"). Pre-select the target plan, show annual savings as a number, and ensure your middle tier is a clean decoy so upgrading feels like the safe default. A sound decoy (ADI 70+) lowers the perceived risk of choosing the higher tier.