LordCrash I have a marketing background - you'll be surprised how much insight can be derived from a simple like. That's why it's one of the primary metrics on Facebook/Instagram/YouTube etc. Top content creators are able to use likes to gauge what content their audience prefers and adjust appropriately.
You're right that there is a myriad of different reasons why people might like a scene, but when we analyse many different videos, we can pretty confidently isolate the effect of an individual performer/director/studio.
Let's take Agatha Vega as an example, who was cast in the top performing non-harem video in the past year. We want to determine whether she is a popular casting choice, or if the video mainly succeeded due to other factors.
To achieve this, we can analyse her videos from other studios. How well did her videos perform compared to other videos by the same studio, released around the same time? This would minimise any changes in camera tech, directors etc.
1) VR Edging
2) VR Solos
3) iStripper
Conclusion
While there is a little variation between studios (perhaps some videos weren't shot well etc), on the whole, videos featuring Agatha Vega consistently perform very well compared to other videos by the same studio, released around the same time.
We can use this same technique for other performers, or even types of performers (e.g. teens vs milfs, blondes vs redheads, natural vs performers with plastic surgery). We can also use this to isolate different settings, videos featuring certain camera angles etc.
One huge advantage of having a simple one-click feedback system is that you will get a lot more responses. And a larger sample size means more reliable data.
