Find a price customers accept, before you publish it
Asking “what would you pay?” produces low, unreliable numbers. Scrutinizr shows each participant one randomly assigned price or package, asks what value they expect and tracks clicks on a buy button, keeping what people say separate from what they do.
Why this is hard today
Guesswork
Prices are set by copying competitors.
Wrong signal
Surveys about price produce wishful answers.
Slow answers
Packages are designed without knowing which features matter.
How Scrutinizr does it
- 01
Add price points or packages
Two to four options with the features in each.
- 02
Randomise exposure
Each participant sees one option.
- 03
Ask about value
What they would compare it to and what makes it feel expensive.
- 04
Track the buy click
An optional buy button records intent separately from stated interest.
The result
- Buy-click rate per price
- Acceptable price range
- Main objections in customers’ words
- Which features justify the higher tier
Example: £8 versus £12
£8 had twice the buy clicks of £12, but most objections at £12 compared it to a free app, not to the value. The team kept £12 and added a free tier.
Good to know.
Is a buy click a real purchase?
No, and the report says so. It is a stronger signal than a stated answer, not a sale.
Can I test annual plans?
Yes. Add monthly and annual options as separate variants.
How many people do I need?
At least 30 per price point to compare click rates.
Make your next move with evidence.
Start with a question and bring your websites, documents, data and customer voices into one evidence trail.