Data insights

AzgardCKJ This is a great point.

AzgardCKJ they should continue with PT content and not reduce the amount of Non-PT scenes

I don't really like PT videos and I do have a Q3. I still don't care how it looks but that is just me.
There would be peace in SLR land if they didn't take away regular scenes for PT scenes. I never signed up for PT scenes.
I have a feeling that we are about to get a lot of PT scenes from europe now with weeks of no regular.

rerun119 I have a feeling that we are about to get a lot of PT scenes from europe now with weeks of no regular.

Looking at the pipeline and booking schedule - doesn't appear to be the case at all.

rerun119 I sure hope not

doublevr So users that are using the app less than once per week are non-existent? US lawmakers can't know about this, otherwise the porn tax will go up to 20%!

At first I was a bit taken aback by what the top hidden lists contain especially the performers, then realised only 9% of people have hid a performer

It's hard to know how much impact low quality videos or "too many uploads" skew these results

RIP having BBW or mature SLR scenes

I wonder if we can get some kind of data insight relating to boob jobs vs natural with views/likes although people that have a boob size preference might skew that result a bit

Hurto11 I'm confused why you say this, I don't see it at all?

Hurto11 Also really surprised chlor surreal is on the hide list.

Because people have different taste than you?

Hairsational armpits

I think they forgot to include the POV kissing segments that include the armpits. Here it looks like no one would be watching it, while the popularity graphs along the scrub bar in the app say otherwise.

SchnuppiLilac not only this for anal, most anal videos don't have anal segments and anal is actually mixed into cowgirl, doggie, mish and what not...
I also don't even see the creampie segment here, making you think they are not liked. I find it really doubtful.

Seems these stats are worthless anything else than positions.

wenworth
We wouldn't see creampie since the metric is 'share of streamed time'. And the creampie segments are going to be very short.

These stats are super interesting though - I can imagine a few ways these findings can be applied. Would also be interesting to get pivots on these based on segment order (to de-bias cases where the first scene, typically bj, might introduce bias in the results).
Segment utilization (proportion of segment watched over segment length) could also be super useful for content creation.

@doublevr , btw I love stuff like this. This is probably my favorite thread on this forum. Please keep sharing data insights like this

This makes pretty good sense to me considering BJ is usually at the start of the scene. I figure most people just watch a scene until they orgasm and then they end the experience and close the app shortly after.

Looks like most people outlast the BJ and then they start dropping off as the positions start getting more intense.

Hairsational I think the big reason is because it is always the first thing to happen.
If you look at the heat maps on the videos. The beginning is always the biggest part. I think this is why the beginning of the story is so important. People turn on the video to see what this is going to be all about. They watch to see if she turns them on and that starts with the BJ.

I don’t know if I totally agree with the speculation around blowjob. While blowjob is toward the beginning it’s usually some talking, undressing, or other stuff I can’t get past fast enough. I personally watch the first part of the scene long enough for the script to load, then I skip to other sections which include all the BJ portions. I personally think blowjob is watched more because it’s usually the one of the fastest part of the script.

HughMungus I figure most people just watch a scene until they orgasm and then they end the experience and close the app shortly after.

That’s an interesting thought. With a large selection of porn, I stay on a video for 1-2 min before loading the next in search of scenes/scripts I do like.

@doublevr I also love the data and insights, threads. When you use these metrics to influence development decisions are you only looking at single data points like this or do you dig into correlations? Like what scenes/scripts/features/functionality was released mid-May through July in 2023 causing a spike in missionary views? (Same with BJ in April-June)?
Do you cross reference segment type with script yes/no, script speed, time on segment, time in scene, segment before/after, etc to determine if metrics paint a pattern or are anomalies?

Love it, can’t wait to hear/see more?