MaxDiff (short for Maximum Difference Scaling, also known as best-worst scaling) is a survey research technique for forcing respondents to prioritise a long list of items — features, messages, needs, concerns — against each other. It produces a cleaner, more differentiated ranking than traditional rating scales.
How it works
Rather than ask respondents to rate every item individually (which produces compressed, undifferentiated scores), MaxDiff shows small sets (typically 4–5 items) and asks respondents to pick the best and worst. By rotating items across many sets, every respondent effectively ranks every item against every other item.
Each best-worst answer is decomposed into a rank-ordered logit:
$$P(\text{best}=b, \text{worst}=w \mid S) = \frac{e^{u_b}}{\sum_{i \in S} e^{u_i}} \cdot \frac{e^{-u_w}}{\sum_{i \in S \setminus \{b\}} e^{-u_i}}$$
Item utilities are estimated hierarchically (so each respondent's unique priorities are preserved), then re-centred so the population mean per item is zero — fixing the otherwise arbitrary additive constant.
Why MaxDiff beats rating scales
No scale-use bias — can't be gamed by respondents who rate everything high or low
Forced trade-offs — reveals genuine priorities rather than enthusiasm
Comparable across cultures — avoids differences in rating-scale usage patterns across geographies
Discriminates between items — even items that would all score 8/10 on a scale differ clearly on MaxDiff
Anchored MaxDiff
Standard MaxDiff only tells you relative importance — you know Feature A is more important than B, but not whether B is “important” in absolute terms. Anchored MaxDiff adds a per-respondent threshold so the scale becomes “important vs not important” rather than purely relative. This is what makes money-denominated or classification results possible.
When to use MaxDiff
Prioritising a long list of product features for a roadmap
Testing messaging claims to find the most persuasive
Needs-states research — which customer problems matter most
Benefit prioritisation — which benefits should headline a product
Brand attribute importance — what matters most about a brand
Items on the list should be at the same conceptual level (don't mix “low price” with “feature X”) and ideally number 10–30 (fewer makes the exercise trivial, more fatigues respondents).
MaxDiff vs Conjoint
Conjoint tests trade-offs between attribute levels within a product (e.g. Brand A vs Brand B, £10 vs £15). MaxDiff tests trade-offs between items at the same level (e.g. Feature A vs Feature B vs Feature C). Use conjoint for pricing and attribute-level decisions, MaxDiff for prioritising items on a flat list.