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Play counts and average watch time never told you the one thing that mattered: which second moved the buyer. These tabs do. Open any video and you get six tabs.

General

Your metric cards, each with a sparkline and a trend. Fully customisable. See Custom metrics.

Retention

The drop-off curve, second by second.

Funnel

Page view → play → 25/50/75% → end → sale.

Sources

Which traffic actually pays.

Quality

Whether the player is losing you sales.

Embed

Your embed snippets.

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Retention

The curve of who is still watching, and when they left. Two things make it more than a pretty chart: Buyers vs non-buyers. Overlay the two curves. If your buyers watched past 4:10 and your non-buyers did not, you have found the moment your video sells. That is the moment to protect. Markers. Your CTAs and conversion density are drawn onto the timeline, so you can see whether the drop-off lands before or after the ask.
The flat answer to “what should I cut?” is the cliff on this chart. Find the second where the line falls off, watch it, and cut what you find.

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Funnel

Where the viewer stopped, at every stage from page view to sale: a rate at each step, and one overall. A high play rate and a low 50% rate is a hook problem. A high 75% rate and a low conversion rate is an offer problem. The funnel tells you which one you have.

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Sources

Which traffic pays. Broken out by affiliate, by referring domain, and by traffic source.
ROAS is null (not zero) when no payout was captured for that source. A zero would read as “this source lost money”, which is a different claim from “we do not know what it cost”.
You can also break any metric down by campaign, ad set, ad, and creative, so a winning creative is visible as a creative and not only as a spike in the total.

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Quality

A slow player kills the sale before the hook lands. This tab tells you if that is happening.
Time to first frame and startup time, at the median and the 95th percentile. The p95 is the one that matters. It is the experience of your worst-served viewers, and they are the ones who leave.
Rebuffer rate, rebuffer ratio, dropped-frame rate.
Playback failure rate, exits before start, and a breakdown of the errors behind them.
How often autoplay actually started, and how often viewers unmuted.
A KPI with no samples reads “No data”, never 0%. A zero would be a lie: it would say “nothing went wrong” when the truth is “nothing was measured”. Errors are classified so the tab shows genuine failures, not noise. Auto-recovered events (a buffer nudge, a stall the player fixed by itself) are collected under Diagnostics rather than counted against you.

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Traffic quality

How much of your traffic is human. On the video’s General tab and on the workspace dashboard: the split between human, bot, datacenter and VPN sessions, with a country breakdown.
Bot and datacenter detection is reliable. VPN detection usually is not: it needs an IP-reputation add-on, and without it most VPN traffic shows up as datacenter or human. The card says so where you read it.

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Audience and hot leads

Audience in the sidebar lists identified viewers. Click one for a full profile: lifetime watch time, every video they touched, their events, their conversions, their revenue. Hot leads scores viewers 0-100 on watch behaviour: did they reach the offer, did they unmute, did they come back, did they click. Cold, warm, or hot.
The score is a transparent heuristic, not a black box. It is built from signals you can see on the viewer’s own profile, so you can always check its work.

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Export it

Your data is yours.
  • Webhooks push events to you as they happen.
  • The Analytics Export API pulls summaries, retention curves, raw events and conversions, with a token carrying analytics:read.
  • Bulk exports run as a job and hand back a download URL.