I am looking for a way to combine Aha's strict scoring approach for ranking features with scientific methods established to measure and priorize opportunities for innovation. Both the Kano-Model and the Ulwick-Opportunity-Scoring algorithm allow (and require) quantitative input to drive qualitative decisions.
For Aha this could mean: For a given feature, with unclear scoring, create a survey that asks for importance and satisfaction (in case of the Ulwick-model) or response to the feature being present or not present (in case of the Kano-Model). In the idea portal, customers/users/partners/experts can then vote on the outcomes and response (not directly on the features) and Aha can calculate the opportunity score or Kano feature category to help the product manager in making a data-driven decision for or against a feature that is not distorted by the end-user's solution-centric thinking.
Having this survey type of scoring both pre-implementation AND post-delivery would be nice. "How well did the feature deliver on the basis of how they rated its importance"
I have built an open source implementation based on Aha's API: https://github.com/trieloff/surveyor