# How product managers set pricing without willingness-to-pay data on Mac, step by step

> Stated willingness-to-pay runs about 21% above real willingness-to-pay. Here is how product managers on Mac can set prices without it.

URL: https://www.lazur.app/for/product-managers/problems/product-pricing-without-willingness-to-pay-data
Updated: 2026-11-08

You can set a product price without willingness-to-pay data, but do not take a survey number at face value. Start with your margin floor, cut stated willingness-to-pay down, then test real prices by revenue per visitor. The steps below use Excel or Apple Numbers on a Mac.

## Quick answer

- Survey answers about willingness-to-pay tend to run high, by about 21% on average.
- Cut the number further for higher-priced and specialty products.
- Set your margin floor before you read any survey.
- Test prices by revenue per visitor, and watch sales volume too.
- Pay sales reps on price as well as revenue, and set a review date for every price.

## What setting a product price costs you

- **Margin left on the table.** Bain's 2018 press release says 85 percent of the more than 1,700 companies it surveyed see significant room to improve pricing. Your price could be fine. It could also sit well below what buyers accept. Without willingness-to-pay data you cannot tell which.
- **Price cuts that cost more than they win.** Cutting price to win volume can backfire. Simon-Kucher's 2025 Global Pricing Study names sales volume as the top profit driver over the next 24 months, so volume matters. A lower price that wins volume at a thin margin can still shrink profit. Check both sides of that trade.
- **Bad pricing that stays hidden.** The Harvard Business Review article on B2B pricing mistakes says poor pricing can go unnoticed for years. Treat that as a warning. A price set once and never reviewed can cost margin every month until someone checks.
- **A pricing decision made in a rush.** Product Focus reports that the average product manager spends under 20% of their time on pricing, based on its 2009/10 survey. Pricing then gets whatever hours are left. The decision often lands during a launch, when nobody has time to test it.
- **A high price that misses real buyers.** If you set price from raw survey answers, you may set it too high for many buyers. Stated willingness-to-pay runs about 21% above real willingness-to-pay on average. A price aimed at the survey average can miss the real buyer, and the sales team absorbs the miss.

## Why it happens

1. **Pricing is contentious.** Product Focus says everyone has an opinion on pricing, but few people have the skills to judge it well. That gap turns price into a debate instead of a measured decision. Without a shared method, the loudest view often wins.
2. **Price changes hit bonuses fast.** Product Focus notes that price changes have a quick, direct effect on sales, profitability and bonuses. That speed adds pressure. Teams then either avoid change, or they change prices in a hurry with no test at all.
3. **Sales pay rewards revenue, not margin.** HBR describes a company where sales reps were paid on revenue alone. Most of them closed deals at the lowest permissible margin. In that case the pay plan set the price, not the product team.
4. **Stated answers run high.** Surveys ask about price in a setting where nothing is actually paid. The meta-analysis of 77 studies found the resulting bias averages about 21%. A team that skips the correction inherits that bias in its final number.
5. **No feedback loop.** Without a review date, nobody checks whether a price still works. Poor pricing can stay hidden for years. Missing review dates are a process problem, not a math problem, and they are easy to fix.

## How to fix it

- **Cut stated willingness-to-pay before you use it.** Start with the average gap of about 21% for stated willingness-to-pay. Cut deeper for higher-priced and specialty products, because the bias is larger there. Write the haircut and the reason in your pricing doc, so anyone can check the logic later.
- **Align sales incentives with price.** Pay reps on more than revenue, so they have a reason to protect margin. The HBR example shows what happens when pay ignores margin. Ask sales leadership how deals are scored, and check whether reps can see the price floor.
- **Test with real purchase context or A/B tests.** Show two comparable groups two prices, then compare revenue per visitor. Keep sales volume on the same sheet. Do not decide on click rate alone. Set the test length and the rules before you start, and write them down.
- **Set a review date for every price.** Put a review date on the calendar for each price, and log the result you expect. Track it in Linear or Notion. When the date arrives, compare the result with the expectation, then decide whether to keep the price.
- **Use a sheet to show the math.** In Excel for Mac, build a one-variable data table under Data > What-If Analysis > Data Table. In Apple Numbers, type an equals sign to open the Formula Editor and the Functions Browser. A visible formula makes the price debate shorter and more specific.
- **Treat other survey methods as one input.** Van Westendorp and Gabor-Granger are common survey methods. The sources reviewed did not show validation against real purchases. Use them as one input, and compare the results with sales before you commit to a number.
- **Check competitor prices on their own sites.** Competitor prices should come from the competitor's own pricing page. If a number is unclear, check their pricing page directly. Save the URL and the date next to the number, so the next review can recheck it.

## Why survey answers about price run high

Most product managers collect willingness-to-pay the easy way. They ask customers what they would pay, then pick a number from the middle of the answers. That number is often too high. A meta-analysis of 77 studies found that stated willingness-to-pay for consumer goods runs about 21% above real willingness-to-pay on average. Researchers call this hypothetical bias. It comes from the fact that a survey answer costs the buyer nothing.

The 21% is an average across consumer goods, not a rule for your product. Your buyers may sit above it or below it. Treat it as a starting point for a haircut. Then compare it with your own sales as soon as real sales exist.

![Product manager working on a laptop at a desk, reviewing product pricing notes.](https://images.lazur.app/content-images/problem/product-pricing-without-willingness-to-pay-data/product-managers-set-pricing-without-willingness-to-1-47c846.jpg)

## How much each method overstates willingness-to-pay

Not every method fails the same way. The same meta-analysis compared direct questions with indirect methods, such as conjoint-style tasks. Indirect methods overestimate real willingness-to-pay more strongly than direct questions. The bias also grows for higher-priced products, specialty goods and within-subject designs. The authors recommend a stronger downward adjustment in those cases.

| Situation | What the research found | What you do with the number |
| --- | --- | --- |
| Direct question about price | Smaller overestimate than indirect methods | Cut the average, then sanity-check it against sales |
| Indirect method, such as conjoint-style tasks | Overestimates real willingness-to-pay more strongly | Treat the result as a ceiling, not a target |
| Higher-priced product | Bias is larger | Use a bigger downward adjustment than for a cheap product |
| Specialty product | Bias is larger | Use a bigger cut and recheck with real buyers |
| Within-subject design | Bias is larger | Be skeptical when the same people rate several prices |

_Based on a meta-analysis of 77 studies on hypothetical bias._

Read the table as a rule of thumb. The research does not give one adjustment number for each row. Pick a haircut for each product type, write it in your pricing doc, and keep it until real sales show it is wrong.

## Worked example: turning a survey price into a working price

Say your survey puts the typical willingness-to-pay at a figure you call P. Because stated answers run about 21% above real ones on average, a rough real figure is P divided by 1.21. For a higher-priced or specialty product, cut deeper than that. The math is simple. The harder part is writing the haircut down before someone argues for a higher price.

Do the math in a sheet so everyone can see it. In Excel for Mac, put the survey price in B2 and the haircut in B3. Enter 0.21 in B3 for the average gap. Type =B2/(1+B3) in B4. Change B3 to a bigger value for a specialty product, and B4 updates at once.

## Use Excel or Numbers to compare several prices

A survey gives you one number. Revenue depends on how many people buy at each price. Excel for Mac can compare several prices with a data table. Put your revenue formula in B1, and make it use one price cell, such as D1. Enter candidate prices in A2 through A6. Select A1 through B6, then go to Data > What-If Analysis > Data Table. Set the Column input cell to D1.

The buyer count in that formula should come from your own funnel, not from the survey. A survey tells you what people say. Your funnel tells you what people do. Keep both on the same sheet so the gap between them stays visible.

> **Same number on every row?:** If every row in your data table shows the same revenue, the formula does not point at the price cell. Fix the reference in D1 first, then read the results again.

In Apple Numbers, click a cell and type an equals sign. Numbers opens the Formula Editor and the Functions Browser, which appears on the right side of the window. Use the browser to find a function, then finish the formula. Fill the formula down each price row, changing only the price reference.

![Team meeting in front of a whiteboard, discussing product plans and prices.](https://images.lazur.app/content-images/problem/product-pricing-without-willingness-to-pay-data/product-managers-set-pricing-without-willingness-to-2-fec673.jpg)

## Test prices with real buyers, measured by revenue per visitor

A live test beats a survey on realism. The sources point to real purchase context and A/B tests as useful fixes. Show one group one price and a second, comparable group another price. Record revenue per visitor for each group. Do not stop at the click rate on the buy button.

Revenue per visitor matters because a lower price can win more clicks and still lose money. A higher price can lose clicks and still win on revenue. Simon-Kucher's 2025 Global Pricing Study surveyed more than 2,200 business leaders across 28 countries. It names sales volume as the top profit driver over the next 24 months. Keep volume on the same sheet as revenue, and read them together.

- **21%** Average gap by which stated willingness-to-pay exceeds real willingness-to-pay, across 77 studies ([source](https://research.rug.nl/en/publications/accurately-measuring-willingness-to-pay-for-consumer-goods-a-meta/))
- **85%** Of companies say they have significant room to improve pricing, in Bain's survey of over 1,700 companies ([source](https://www.bain.com/about/media-center/press-releases/2018/pricing-prerogative-most-companies-call-pricing-a-high-priority))
- **under 20%** Of their time the average product manager spends on pricing, per Product Focus citing its 2009/10 survey ([source](https://www.productfocus.com/take-control-of-pricing/))
- **2,200+** Business leaders surveyed across 28 countries for Simon-Kucher's 2025 Global Pricing Study ([source](https://www.simon-kucher.com/en/insights/global-pricing-study-2025))

The sources do not give a test length. Pick one with your data team that covers a normal buying cycle for your product. Write the length, the groups and the metric down before you start. Changing the rules halfway makes the result hard to trust.

## Mistakes that make pricing decisions worse

- Treating the survey average as the price. The average is a starting point, and the research says stated answers tend to run high.
- Raising the price for every customer on the same day. You lose the comparison and cannot tell what moved revenue.
- Judging a test by conversion alone. Track revenue per visitor and sales volume next to it.
- Paying sales reps on revenue alone. In one HBR example, reps closed most deals at the lowest permissible margin.
- Waiting a year to review. Poor pricing can go unnoticed for years, according to HBR.
- Using one haircut for every product. Higher-priced and specialty products need a bigger cut.

## How strong is the evidence?

The 21% gap is the strongest figure in this guide. It comes from a meta-analysis of 77 studies on consumer goods, not software or business buyers. Treat it as a starting point for other markets, and test it against your own sales. Bain reports that dedicated pricing software is associated with 2.5 times stronger pricing outcomes. That is an association, not a controlled result.

The time figure is old. Product Focus says the average product manager spends under 20% of their time on pricing, citing its 2009/10 survey. No newer survey of that time turned up in the sources reviewed. Nor did any evidence on errors made by product managers who set prices. That is a gap in the research, not proof that errors are rare.

## Where Lazur fits in a pricing week

Lazur is a voice assistant for the Mac that lives in the notch. Hold ⌥ ⌘ to ask about anything on screen, and Lazur answers out loud. Ask where a control is, and Lazur draws a circle and a label around it. Ask how to do something, and Lazur guides you one click at a time, waiting for each click. Teams that track pricing reviews in Linear can read [Linear for product managers on Mac](https://www.lazur.app/for/product-managers/linear).

For this problem, guidance is the most useful part. Ask Lazur to walk you through the Data Table dialog in Excel. It points, explains and waits for your click at each step. Lazur does not click buttons, edit files or operate Excel for you. You still make every change.

Research helps with competitor prices. Lazur runs research in its own Chrome tabs through the Lazur for Chrome extension, then returns a summary and a report. Point it at competitor pricing pages on their own sites. If you are unsure where a price lives, check their pricing page yourself. A summary can miss a footnote about annual billing.

Dictation saves time on the write-up. Hold fn to dictate clean, formatted text at the cursor in any app. Dictate your haircut rule into the pricing doc. Then ask Lazur to draft a short note for sales. Edit the draft before anyone else reads it.

## Privacy and customer data in pricing work

Pricing work often touches customer data. Lazur listens and looks at the screen only while you hold the shortcut. Audio and the screenshot go to AI providers to answer you, and they are not stored. Content is never used to train AI models. Your employer may still set rules on customer data. Follow those rules before you paste customer records into any tool.

![Person checking numbers in a spreadsheet on a computer screen, product pricing math.](https://images.lazur.app/content-images/problem/product-pricing-without-willingness-to-pay-data/product-managers-set-pricing-without-willingness-to-3-1ed599.jpg)

## What to do next

Write your margin floor first, then the survey number, then the haircut. Put all three in one row of your sheet. Review that row after your first real sales cycle. If the haircut was too high or too low, change it and write down why. A dated note of each change makes the next review faster.

## With Lazur

Lazur is a voice assistant for the Mac that lives in the notch. Hold ⌥ ⌘ and ask; it sees your screen, answers out loud, points at buttons and walks you through apps. Hold fn to dictate. Free for 3 days, then $18/month: https://www.lazur.app/download

- “Walk me through the Data Table in Excel.”: Lazur points at the Data menu, then waits for each click until the Data Table dialog is open. (Walks you through it)
- “Walk me through the Data Table in Excel.”: Lazur points at the Data menu and waits for each of your clicks before it moves to the next step.
- “What is the Functions Browser in Numbers for?”: Lazur explains it out loud and points at the panel on the right side of the window.
- “Research competitor pricing pages for our three closest rivals.”: Research runs in Lazur's own Chrome tabs and comes back with a summary and a report.
- “Draft a short note to sales about the new haircut rule.”: Lazur drafts the text, and you edit it before it goes anywhere.
- “Dictate my notes on the test results.”: Hold fn and speak. Dictation lands at the cursor in any app, formatted as clean text.
- “Where is the Data menu?”: Lazur draws a circle and a label around it on your screen.
- “Remind me to review this price next month.”: Lazur can set the reminder by voice in Apple Reminders, so the review date does not get lost.

## A plan you can start this week

- **Day 1: Write your margin floor.** List each product's cost to serve and the lowest price you accept. Put the number in a Google Sheets row or an Excel row. This is your floor, and no survey number overrides it.
- **Day 2: Haircut the survey answer.** Divide your survey price by 1.21 as a first cut. For higher-priced or specialty items, cut further. Write the haircut in one cell and the reason in the next cell.
- **Day 3: Check the sales incentive.** Ask sales how reps are paid. If the plan rewards revenue only, raise the question with the sales lead. Note the answer in Notion, next to the price row.
- **Day 4: Build the test.** Set two prices for two comparable groups. Track revenue per visitor and sales volume. Agree on a test length with your data team, and write it down before launch.
- **Day 5: Set the review.** Create a Linear issue with the review date. Write the result you expect in the issue. When the date arrives, compare the actual result with that expectation.

## FAQ

### What is willingness-to-pay?

It is the most a customer will pay for a product. Teams estimate it with surveys, live tests or sales data. Surveys are the cheapest method, and they carry the most bias.

### Is a survey useless for setting a price?

No. Use it as one input. The meta-analysis shows stated answers run about 21% high on average, so cut them before you use them. Then confirm the result with real sales.

### Which Mac app is better for the price math?

Excel for Mac has a Data Table under Data > What-If Analysis > Data Table. Apple Numbers opens the Formula Editor when you type an equals sign. Either works for a small pricing model.

### How long should a price test run?

The sources reviewed do not give a duration. Pick a length that covers a normal buying cycle for your product, and write it down before the test starts.

### Should I use Van Westendorp or Gabor-Granger?

Both are survey methods. The sources reviewed did not show validation against real purchases. Use either as one input, and compare the results with sales before you commit to a price.

### Does Lazur see my spreadsheet all the time?

No. Lazur listens and looks at the screen only while you hold the shortcut, which is ⌥ ⌘ for asking about the screen. Audio and the screenshot go to AI providers to answer, and they are not stored.

### Can Lazur change my prices or edit my sheet?

No. Lazur guides, points, explains, answers out loud, drafts text and runs research. It does not click buttons or edit files for you. You make each change yourself.

### Does Lazur work on Windows?

Lazur is for macOS, on Apple silicon and Intel Macs. Windows is planned but not available.

## Sources

1. [Accurately measuring willingness to pay for consumer goods: a meta-analysis of the hypothetical bias](https://research.rug.nl/en/publications/accurately-measuring-willingness-to-pay-for-consumer-goods-a-meta/), University of Groningen research portal, checked 2026-11-08
2. [Pricing prerogative: Most companies call pricing a high priority, but 85 percent say they have significant room for improvement](https://www.bain.com/about/media-center/press-releases/2018/pricing-prerogative-most-companies-call-pricing-a-high-priority), Bain & Company, checked 2026-11-08
3. [Take control of pricing](https://www.productfocus.com/take-control-of-pricing/), Product Focus, checked 2026-11-08
4. [Global Pricing Study 2025](https://www.simon-kucher.com/en/insights/global-pricing-study-2025), Simon-Kucher & Partners, checked 2026-11-08
5. [A Survey of 1,700 Companies Reveals Common B2B Pricing Mistakes](https://hbr.org/2018/06/a-survey-of-1700-companies-reveals-common-b2b-pricing-mistakes), Harvard Business Review, checked 2026-11-08
6. [Pricing Impact: A Decade of Documented ROI](https://publications.pricingsociety.com/pricing-impact-a-decade-of-documented-roi/), Pricing Society, checked 2026-11-08
7. [Calculate multiple results by using a data table in Excel for Mac](https://support.microsoft.com/en-us/excel/calculate-multiple-results-by-using-a-data-table-in-excel-for-mac), Microsoft Support, checked 2026-11-08
8. [Calculate values using data in table cells in Numbers on Mac](https://support.apple.com/en-gb/guide/numbers/tan727173a8/mac), Apple Support, checked 2026-11-08