When every item looks important

01Rating scales often make every item look important.

02The strongest preference remains difficult to distinguish.

03Long item lists are difficult to rank reliably.

04Relative preference strength is missing from the final ranking.

MaxDiff forces trade-offs — revealing true preference and share.

FROM SETUP TO FIELDWORK

List every item once. See the exact best/worst set respondents get.

No separate preview step — items rotate automatically into sets of 6 across questions.

createsurvey · maxdiff

MaxDiff (Best-Worst Scaling)

PriorityCustom tasks · min. 100 respondents

Items to rank (full pool)

1Advanced search×

2Team collaboration×

3API access×

4Custom reports×

5Mobile app×

624/7 support×

+ Add item

Applied questions rotate 6 items at a time from this pool, so every item gets shown and compared.

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Live preview

Question 1 of 5

Which feature matters most, and which matters least? *

Item👍👎

Advanced search

Team collaboration

API access

Custom reports

Mobile app

24/7 support

‹ Previous

* Required

Next ›

Left: the full item pool every MaxDiff study starts from. Right: exactly what respondents see — 6 items at a time, best and worst.

FROM RESPONSES TO RESULTS

Preference ranking and strength

Every figure below comes from one real example study — 240 respondents picking best and worst from 12 items, computed by the same engine your own survey runs on.

Choice task design

The survey method, the number of items, the set design and how often each item was shown.

Study designbalanced

MethodBest-Worst (balanced exposure)

Respondents240

Items rated12

Set design6 items × 6 sets

Exposures per item3 sets × 240 = 720

Every item is shown exactly three times, so no item is favoured by exposure. Six sets cannot also balance every pair — each pair meets once or twice — which is why the report prints an estimate range next to each score.

Top-priority item

See every item ranked by preference share, normalised so the list sums to 100%.

Preference shareTotal 100%

Uptime

11.1%

Ease of use

11.0%

Fair price

10.6%

Strong security

9.6%

Fast performance

9.5%

Support quality

8.8%

Integrations

8.5%

Collaboration

7.5%

Top 8 of 12 items, normalised so all twelve shares sum to 100%.

Preference and rejection

The difference between best and worst selections distinguishes strong preference from low rejection.

Best/Worst distributionNet Score

Uptime

+16.3

Ease of use

+15.8

Fair price

+13.7

Strong security

+7.6

Support quality

+2.5

Mobile support

−5.4

Data export

−14.2

Offline access

−24.2

Net score = picked "best" minus picked "worst". Its ranking matches the shares above, which cross-checks both.

Preference by customer group

Split respondents by customer type to compare the priority ranking for each group.

Segment differencesby role

37.5%n=90

Individual contributor

Items to emphasize or deprioritize

Group the ranking into primary, secondary, and lower-priority items to support clear communication decisions.

Message guide3 tiers

CoreLead message

Uptime 11.1%Ease of use 11.0%Fair price 10.6%

SupportSecondary

Strong security 9.6%Fast performance 9.5%Support quality 8.8%

DropKeep out of headlines

Data export 6.0% / −14.2Custom options 5.9% / −14.5Offline access 4.3% / −24.2

Recommended actions

The report summarizes practical implications supported by the analysis results.

ConclusionsN = 240

1"Uptime" leads on 11.1% preference share (net +16.3) — lead the headline with it.

2"Ease of use" (11.0%) sits inside the same estimate range, so first and second place cannot be separated — treat them as one core pair rather than a ranking.

3Offline access, custom options and data export rank last — keep them off the main message.

4The top item differs by role — executives lead with uptime, founders with price — so the creative needs splitting by target.

5Best/Worst distribution and preference share rank the twelve items identically, which backs the result.

A COMPLETE REPORT

See the full report from summary to conclusion.

The six cards above are fragments of this. Scroll the real output end to end, right here on the page.

MaxDiff (best-worst scaling) — 12 items · 240 simulated respondents

Analysis Settings

240 respondents · 6 sets · 12 unique items.

Segment by

Executive Summary

240 respondents · 12 items

This MaxDiff (Best-Worst Scaling) study collected choice data from 240 respondents across 6 sets of 6 items each, covering 12 items in total. "Reliable uptime" is the clear leader, capturing 11.1% of preference share, while "Offline access" trails at just 4.3%. The Best/Worst response distribution corroborates this ranking.

Study Design

Metric	Value
Design	Repeated Best-Worst choice (BIBD design)
Fielding period	2026.05.11 – 2026.06.01
Respondents	240
Items evaluated	12
Set composition	6 items × 6 sets
Exposures per item	720 (across all responses)

Preference by item

A 0–100 score reflecting which item was chosen as most preferred or least preferred in each set. A higher score means preference was higher among these candidates. The horizontal line shows the range the score could fall in if the make-up of respondents changed.

Reliable uptime

66.3 (64.7~68.1)

Ease of use

65.8 (64~67.6)

Affordable pricing

63.7 (61.8~65.5)

Strong security

57.6 (55.6~59.6)

Fast performance

56.7 (55~58.3)

Customer support quality

52.5 (50.8~54.1)

Seamless integrations

51 (48.8~53)

Collaboration tools

44.9 (43~46.7)

Mobile support

44.6 (42.7~46.5)

Data export

35.8 (33.6~38.1)

Customization options

35.5 (33.1~37.7)

Offline access

25.8 (23.8~27.9)

Interpretation

6 neighbouring pair(s) have overlapping ranges (Reliable uptime / Ease of use, Ease of use / Affordable pricing, Strong security / Fast performance, and 3 more). Those positions would swap in another sample, so do not read a decision out of the gap between them — treat each overlapping run as one tier, review the priorities together and look at other criteria alongside them.

Preference weight by itemsums to 100%

The weight each item’s preference score carries out of the whole. You can compare where preference gathered among these candidates.

Interpretation

"Reliable uptime" is the most preferred item, accounting for 11.1% of overall preference share, versus just 4.3% for the weakest item, "Offline access".

Most preferred · least preferred choices

The right is the share chosen as most preferred, the left as least preferred. The wider the difference between the two shares, the clearer the direction of preference for that item.

Reliable uptime

+16.3

Ease of use

+15.8

Affordable pricing

+13.7

Strong security

+7.6

Fast performance

+6.7

Customer support quality

+2.5

Seamless integrations

Collaboration tools

−5.1

Mobile support

−5.4

Data export

−14.2

Customization options

−14.5

Offline access

−24.2

Interpretation

The Net Score ranking matches the preference-share ranking (above) closely, cross-validating both derivations.

Answer consistency

Checks whether similar items were preferred in the earlier tasks and in the later ones. Worth keeping in mind when reading the results.

0.96

Rank similarity

3 / 3

Top 3 in common

Rank	Earlier 3 tasks	Later 3 tasks
1	Ease of use	Reliable uptime
2	Affordable pricing	Ease of use
3	Reliable uptime	Affordable pricing
4	Fast performance	Fast performance
5	Customer support quality	Customer support quality

Interpretation

Scoring the earlier 3 tasks and the later 3 tasks separately, the top of the ranking is similar and some positions differ (rank similarity 0.96, 3 of the top 3 in common). The upper ranks largely agree, though some items differ. Look at the group results and the actual priorities alongside this.

How to use these results

What to look at when turning the scores and the ranking into an actual improvement priority.

CORE

Lead message

Top 5 by preference share. Lead with these in headlines and first-screen creative.

Reliable uptime11.1%

Ease of use11%

Affordable pricing10.6%

Strong security9.6%

Fast performance9.5%

SECONDARY

Supporting message

Mid-tier items. Use in detail sections or segment-targeted creative.

Customer support quality8.8%

Seamless integrations8.5%

Collaboration tools7.5%

Mobile support7.4%

REVIEW

Exclude from lead copy

Lowest-ranked items. Drop from primary creative; use only as supporting detail-page info.

Data export6% / -14.2

Customization options5.9% / -14.5

Offline access4.3% / -24.2

Conclusions & next steps

The items to review first and the next steps.

"Reliable uptime" ranks #1 with 11.1% preference share (Net Score +16.3) — use it as the primary headline message.

"Ease of use" (11%) and "Affordable pricing" (10.6%) trail closely behind — bundling them as "top 3 reasons" in messaging is likely more effective than leading with #1 alone.

"Data export", "Customization options", "Offline access" rank lowest — exclude them from primary messaging and use only as supporting detail information.

The Best/Worst response distribution and preference-share ranking agree closely, statistically corroborating this result.

Methodology — Preference scores are normalized from Best/Worst-count importance ((Best rate − Worst rate + 1) / 2 × 100) so the total across all items sums to 100%. Set composition uses a Balanced Incomplete Block Design (BIBD) so every item is shown the same number of times.

Scroll to explore the full report

IN THE REPORT

Priority and preference strength

Best-Worst choices reveal a clear ranking, the strength of preference, and meaningful differences between customer groups.

Utility scores

Best-Worst scaling turns choices into item utilities.

Preference share

Share of preference each item would capture.

Final ranking

A clear, defensible ranking of all items.

Segment comparison

Compare preferences across respondent groups.

Anchored MaxDiff

Separate the truly important from the merely relative.

Auto interpretation

Plain-language reading of the preference structure.

ALSO IN SURVEY ANALYSIS

More survey methods

Each survey analysis method answers a different question — same interface, different lens.

OPP · IDP · PSM

Van Westendorp PSM

Turn four price questions into OPP, IDP, elasticity, revenue simulation, and competitor benchmark.

WTP · Part-worth

CBC Conjoint

Measure attribute importance and willingness to pay with choice-based conjoint analysis.

Kano · NPS

Kano Model

Classify features into Must-be, Performance, Attractive, and Indifferent categories.

AHP · CR

AHP Analysis

Rank priorities with pairwise comparisons — consistency check, segment heatmap, and global weights.

IPA · Regression

Driver Analysis

Find which attributes drive overall satisfaction or NPS using importance-performance analysis.

Recall · Image

Brand Awareness

Track unaided and aided brand recall, brand image dimensions, and competitive positioning.

Turn long lists into clear priorities

Show what matters most, how strongly it is preferred, and whether priorities differ across customer groups.

Get started See pricing

No credit card requiredBest-Worst forced choice design

Reveal what customers value most.

When every item looks important

List every item once. See the exact best/worst set respondents get.

Preference ranking and strength

Choice task design

Top-priority item

Preference and rejection

Preference by customer group

Items to emphasize or deprioritize

Recommended actions

See the full report from summary to conclusion.

Analysis Settings

Preference by item

Preference weight by itemsums to 100%

Most preferred · least preferred choices

Answer consistency

How to use these results

Lead message

Supporting message

Exclude from lead copy

Conclusions & next steps

Priority and preference strength

More survey methods

Van Westendorp PSM

CBC Conjoint

Kano Model

AHP Analysis

Driver Analysis

Brand Awareness

Turn long lists into clear priorities

Analysis Settings

Preference by item

Preference weight by itemsums to 100%

Most preferred · least preferred choices

Answer consistency

How to use these results

Lead message

Supporting message

Exclude from lead copy

Conclusions & next steps

Reveal what customers
value most.