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Daily build note · October 29, 2026

Price Ladder

Set up good/better/best pricing tiers, drop 2,000 simulated shoppers with different budgets and tastes on them, and see who buys which rung, who walks away, which rung is dead weight or cannibalizing the next one, and what prices would earn more.

Local Business Automation Interactive demo live Static HTML/CSS/JS

What shipped

Price Ladder is a good / better / best pricing simulator. Describe the market (shoppers per month, what a typical shopper would pay for the core tier, and how different shoppers are from each other), then set up to four rungs with a price, how much each is worth compared with the core tier, and your unit cost. 2,000 simulated shoppers, each with their own budget and taste for the premium option, pick the rung that leaves them the most value after price or walk away. An optional middle-option pull models people leaning toward the middle choice. You get a 200-dot shopper grid sorted by budget and colored by choice, buy rate, monthly revenue and profit, a per-rung table (buyers, revenue, margin, profit, and the share who would happily pay for the next rung), and a profit-vs-price curve for each rung with a Try button for its best price. Optimize all prices searches for a better ladder while keeping the rungs in order and every rung selling. A stamp verdict (WELL LADDERED, TUNE THE RUNGS or BROKEN LADDER) comes with chips like DEAD RUNG, CANNIBAL, MONEY ON TABLE, BELOW COST, PRICED OUT, MIDDLE WINS and DECOY AT WORK. There's a markdown report stamped in Central time, and state saves under price-ladder-v1.

How to try

  • The demo opens on SaaS plans (Starter $19, Pro $49, Team $119): WELL LADDERED with 61% of shoppers buying. Hit Optimize all prices and watch the dots recolor as profit climbs about 9%.
  • Load Car wash membership: the three washes are priced $10 apart but barely differ, so Basic takes 81% of sales, Ultimate is a DEAD RUNG, and Basic is a CANNIBAL.
  • Coffee sizes (decoy) prices Large just 20 cents over Medium, so Medium mostly exists to make Large look like a deal (DECOY AT WORK).
  • Consulting packages shows MONEY ON TABLE +31%, and Lawn care (underpriced) has a Mow rung priced below cost and a middle rung nobody buys.
  • Drag the "how different are shoppers" slider or change any Worth value to see how fast a ladder breaks, then Copy markdown report.

Why this (vs neighbors)

Most small businesses and SaaS founders set tier prices by gut, then wonder why everyone buys the cheapest plan or nobody buys the top one. Earlier builds like Plate Cost and Margin Math price a single item from its costs. Price Ladder looks at how rungs compete with each other for the same shopper, which is where most tiered pricing goes wrong.

Scope trim

No competitors, no discounts or annual-vs-monthly toggle, no real survey data import (like Van Westendorp or conjoint), and no churn. Shoppers are a fixed, seeded sample, so the same inputs always give the same answer.

Limitations

  • This is a toy model for building intuition, not a pricing study. Budgets follow a lognormal spread and every shopper is perfectly rational about value left over, apart from the optional middle-option nudge.
  • "Worth" multipliers are your guesses, and the results are very sensitive to them.
  • The optimizer is a simple price-by-price search on rounded prices. It keeps every rung selling at least 10% of buyers, so it may leave some profit behind compared with collapsing to one plan.

Suggested next steps

  1. Let a business paste a few real price-test results or a short willingness-to-pay survey and fit the market from it.
  2. Add an annual plan and a "most popular" badge to see how framing moves shoppers.
  3. Add a competitor rung so shoppers can walk to a rival instead of just walking away.