View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion | ![]() Growth Funnel Analysis | ![]() Agile Ideal Days | ![]() Facilitation Dot Estimation | ![]() Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. | When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Medium | Low | Low | High |
Timedifferent | 1-3 h | 15-60 min | 5-20 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 2-9 | 3-20 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Ideal Day Estimates, Assumption Notes, Capacity Caveats | Effort Heatmap, Risk Signals, Discussion Targets | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | EstimationEffortAgile | EstimationEffortRisk | ExperimentsGrowthAnalyticsValidation |



