Weighted scoring
Combines criterion scores according to their weights. A strength on one criterion can compensate for a weakness on another.
How scoring works
A score you can
trace back to its inputs.
Your ratings, priorities and questionnaire answers determine the ranking. Here’s how they come together—and what to check before choosing.
From inputs to result
Two parts, one score.
Choose a scoring method in setup. Criteria-only uses the weighted average of criterion ratings × 10. Criteria plus answer fit uses the 55/45 blend illustrated below. Questions can still set priorities and exclusions in either mode; fit ratings only affect the blended mode.
Criteria score7.8 / 10
Your criterion ratings, weighted by importance.
55% of the final scoreAnswer fit8.4 / 10
Match ratings attached to your questionnaire answers.
45% of the final scoreFinal score
81 / 100(0.55 × 7.8 + 0.45 × 8.4) × 10 = 80.7, rounded
What to check in a template
Review example scores, fit values and exclusion rules before using a template. Renaming an option does not change those assumptions. New CSV imports use criteria-only scoring. Answer fit contributes only if you explicitly choose the blended method.
The homepage slider shows a weighted average on its own. It does not include questionnaire fit.
Make trade-offs explicit
Give the right things more weight.
Questionnaire answers adjust criterion weights. You can change them in the analysis tools to see how your priorities affect the ranking.
Compare priorities in pairs
AHP pairwise weighting asks which of two criteria matters more. Its consistency check helps identify conflicting judgments. It sets weights; it does not supply evidence about an option.
Look at it another way
Test how the method affects the result.
Different methods answer different questions. Their scores use different scales and are not interchangeable.
TOPSIS
Compares each option with the best and worst criterion values in the evaluated set, using the selected weights.
PROMETHEE II
Compares options in pairs and combines criterion-level preferences into a net preference score.
Pareto view
Shows options that are not outperformed on both criteria score and answer fit. It does not test every possible requirement.
Sensitivity
Explores whether changing priorities changes the leader. Interpret the result within the range and assumptions tested.
Before you decide
Agreement is a useful check.
When methods agree, the leader is consistent across those calculations. That does not prove the inputs are accurate or that the decision will succeed.
When they disagree, inspect trade-offs, missing evidence and sensitivity. Verify mandatory requirements separately. If AI assistance is enabled, review suggested scores and explanations before applying them.
Put the method to work