☠️ The issue
When you use customer feedback managgement tools, you ether have seperated feedback from single users, or a community based feedback where customers share suggestions and ideas (and maybe up- and downvote items). The problem is in both cases, you may ask yourself what to do with the feedback, should you bild feature A or feature B, or both and which to build first? - Since you don't have accurate data to make a good priorization.
Seperated feedback is the most bad case, since every user who gives you feedback thinks his optinion is worth most, which is totally human, he just thinks about his own needs.
A community based feedback tool helps you to get a better sense of what the majority of your users needs. But even that can lead you astray. Let's say 5 users want feature A ( they are new users who bring you an MRR of 50$) a long time user who brings you an MRR of 200$ but wants feature B. Following a community based tool with up- and downvoting you would choose A, even though B might be the better choice. You just lack the right information.
🥳 The solution
The impact score is an automatically generated metric that helps you to priorize what to build next and what to focus on in terms of your average customer satisfaction as well as the impact on your product success.
🤖 Parameters influencing the impact score
The the impact score calculation is made for each single feedback item and gets updated on each interaction with that feedback item. The calculation is based on metrics given by the feedback item itslef as well as metrics from the user who intact with that item (e.g. vote, subscribe or comment).
Customer based metrics
Level of participation
Date of joining
Item based metrics
Discussions, votes, viewrates