Last week I was inspired that maybe we can find a better way to evaluate a dribbbler’s activities and contributions to the community, for example, likes/views rate is a better metric than just likes counts. So to have fun with it, I spent a weekend digging deeper on this idea with Dribbble API and other tools.
And here is Analytttics.
How It Works
I’ve come up quite a few different models in the very first place, but due to the limitations of Dribbble API (and my poor programming skills), in the end I used these 5 metrics to build a rough image of a Dribbbler:
- Appreciation: based on ( favs + buckets ) / views for recent shots.
- Attractions: based on the percentage of followers who have 100+ followers.
- Diligence: based on total shots / total years since joined Dribbble.
- Engagement: based on ( comment + rebounds ) / views for recent shots.
- Influence: based on followers / total years since joined Dribbble.
And the Total Score is a weighted mean of the 5 scores above.