LifterLMS Advanced Videos tracks watch progress on video lessons by writing to wp_lifterlms_user_postmeta with keys for watched seconds, percent complete, and completion timestamp, tied to each user and lesson. The default reporting shows aggregate course progress but exposes very little of the per-video signal that engagement analysis actually needs. Anything you want shaped differently (per-video drop-off, partial-watch queues, per-cohort engagement) needs custom queries.

SleekView reads the user-postmeta rows directly so program teams can build the engagement views their workflows demand. A per-student watch table joins user, lesson, watched percent, and last-update timestamp. A drop-off report aggregates watch percent across users per lesson to find the videos where most learners stop. A partial-watch queue filters where watched percent is over zero but under a threshold, so a content lead can investigate the friction.

Inline edits to completion status route through LifterLMS's APIs where they support the change so completion hooks fire normally. Direct postmeta edits skip hooks by design for back-fill scenarios. Multisite installations get per-subsite scoped views automatically.

Video is where most courses spend the bulk of their production budget, and video is also where most learners decide whether to keep going. The signal of engagement, drop-off, and partial watch is the earliest indicator of whether content is working, but it is buried in lifterlms_user_postmeta with no native surface beyond a few aggregate course-progress numbers. Instructors don't know which lessons are losing learners until the completion rate craters.

Content leads can't tell which video out of fifty needs trimming because they have to query the database to find out. Customer success can't help a stuck learner because the watch position isn't on any screen they can open. SleekView turns watch data into a workspace: per-student watch tables for instructors, per-lesson drop-off reports for content teams, partial-watch queues for support.

The data has always been there. The missing piece is the row-shaped interface that lets each team act on it in real time, before drop-off becomes attrition.