Monadic pricing model

In a monadic design each respondent is exposed to ONE price, not a price ladder. This eliminates comparison effects and yields realistic acceptance data that mirrors real purchase decisions.

Most pricing studies show the respondent multiple price levels — either sequentially (Van Westendorp, Gabor-Granger) or simultaneously (conjoint). The problem is that this creates artificial comparison effects. Once you have seen 49 SEK, 59 SEK feels expensive — not because it is expensive, but because you just saw a lower price. In reality, the consumer sees only one price at a time.

Monadic design solves this by giving each respondent exactly one price point. By distributing a large sample across the price range, we can map the entire acceptance curve without contaminating responses with comparison effects. It requires larger samples but produces data that actually matches reality.

Reflect has worked with monadic price measurement for over 15 years. We have calibrated our model against thousands of real price changes and know that monadic data consistently produces better forecasts than sequential methods. The precision costs more in fieldwork but saves many times over in better pricing decisions.

Key takeaways

• Each respondent sees ONE price, no comparison effects
• Requires larger samples but yields realistic acceptance data
• Maps the entire price acceptance curve empirically
• Better forecasts than sequential pricing methods
• Calibrated against real price changes for 15+ years

Example

The same product was tested with Gabor-Granger (sequential) and monadically. Gabor-Granger indicated an optimal price point of 42 SEK. Monadic measurement showed 37 SEK. Actual market data after launch confirmed that 37-38 SEK was the right level.

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