Web Performance:
Perception & Metrics

http://instartlogic.github.io/p/SFHTML5

This section:

  1. SpeedPerception Study Overview
  2. Hypothesis
  3. Results
  4. Learnings
  5. Phase 2

SpeedPerception

“SpeedPerception is a large-scale web performance crowdsourcing study focused on the perceived loading performance of above-the-fold content.”

Premise: Perception of perceived performance is relative.

Credits & Links: SpeedPerception

Phase-1 crowd sourced 07/28/2016 - 09/30/2016.

Study Hypotheses

Hypothesis 1: Visual metrics will perform better than non-visual/network metrics


Hypothesis 2: No single metric can explain human choices with 90%+ accuracy


Hypothesis 3: User will not wait until “Visual Complete” to make their choice (despite the explicit instruction to wait until video turns grey)

Study Metrics

  • 5,444 sessions, of which 51% were complete and valid
  • 77,482 votes, of which 75% were valid
  • graph demonstrating each of the 160 pairs webkit-font-feature-settings tested between 230 and 330 times

Feedback

Perception of speed and UX strongly impacted by popups / overlays

histogram of comments made, highlighting that pop ups was commonly mentioned

Hypothesis 1

Hypothesis 1: Visual metrics will perform better than non-visual/network metrics

Not True

Questions to Consider

  • Does presence of visual jitter / interstitials interfere with metric performance?
    • Can metrics be improved?
  • Will there be different trends for sites that are free of visual jitter like modals and overlays?
  • Is it possible to automatically predict the presence of jitter to help choose a better set of metrics?

Hypothesis 1: Visual metrics will perform better than non-visual/network metrics

True

Hypothesis 2

Hypothesis 2: No single metric can explain human choices with 90%+ accuracy

True

Hypothesis 2: No single metric can explain human choices with 90%+ accuracy

Still True

Conclusions & Thoughts

  • There appears to be no one unicorn metric but, is there a combination synthetic metric (joint ML model) that will do a better job?
  • People only looked two videos and made the call. Is there some additional information that we can extract from videos that will improve our models?

Hypothesis 3

Hypothesis 3: User will not wait until “Visual Complete” to make their choice (despite the explicit instruction to wait until video turns grey)

Speed Perception Phase 2

  • How do visual jitter & interstitials impact perceived performance?
    • Do they interfere with metric performance?
    • Can metrics be improved?
    • Are sites free of visual jitter like modals and overlays viewed as more performant?
    • Is it possible to automatically predict the presence of jitter to help choose a better set of metrics?
  • Does a long DOM Content Loaded impact perceived performance?

User Experience > Developer Experience

Thank you

Speed Perception: Understanding and Measuring Perceived Performance

http://instartlogic.github.io/p/SFHTML5