Video Performance Estimator
Forecast a video's reach before you publish.
This is a rough planning estimate based on observed YouTube ratios — not a guarantee.
The Video Performance Estimator forecasts a video's likely view range before you publish. Input your channel size, niche, content format, and assumed CTR and retention, and the tool returns a 30-day, 90-day, and 1-year view projection plus the confidence interval. The model uses the standard YouTube growth math — subscriber reach × CTR × retention multiplier × discovery surface — calibrated to per-niche averages.
What is the Video Performance Estimator?
A YouTube performance estimator is a model that combines channel-level baselines (subscriber count, average impressions per video) with video-level assumptions (CTR, average view duration, click-through to recommendations) to project a view range. It is not a crystal ball — but it gives you a defensible baseline against which to measure surprises.
Why this tool matters in 2026
Without a baseline, every video result feels random. With a baseline, you can spot which videos over- or under-deliver and dig into why. This is the foundation of structured channel improvement.
How to use the Video Performance Estimator
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Enter your subscriber count
Approximate is fine.
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Enter your average views per video
Use the median of your last 10 videos.
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Pick your niche
For niche-adjusted multipliers.
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Set assumed CTR and retention
Use your channel averages or aspirational targets.
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Generate the forecast
30-day, 90-day, and 1-year view ranges.
Best practices that actually move the needle
- Use median, not average, view counts. Averages are skewed by viral outliers. Median gives a fairer baseline.
- Run two scenarios per video. A conservative case and an upside case. Helps set expectations and catch surprises.
- Compare against actuals at day 7. Day-7 views vs forecast tells you whether the algorithm is expanding the video or holding it.
- Refine the model with your own data. After 10–15 videos, your channel-specific multipliers will diverge from niche averages.
Quick comparison
| Channel Size | Typical CTR | Typical Retention | Avg Views/Video |
|---|---|---|---|
| Under 1K | 2–4% | 20–35% | 50–500 |
| 1K–10K | 4–6% | 30–45% | 500–5K |
| 10K–100K | 5–7% | 35–50% | 5K–50K |
| 100K–1M | 6–8% | 40–55% | 50K–500K |
Common mistakes to avoid
- Forecasting based on viral outliers. A single 1M-view video does not become your new baseline.
- Ignoring video format. A 60-second Short and a 25-minute deep-dive have completely different performance distributions.
- Confusing forecast with promise. The estimator gives a probability range, not a guarantee. Use it for planning, not promising.
Frequently asked questions
How accurate is the forecast?
Within ±40% of actuals for most videos. Viral outliers and complete flops fall outside the predicted range, which is expected.
Should I publish a video forecasted to underperform?
Yes — the forecast is a planning tool, not a gatekeeper. Some forecasted underperformers become surprise hits.
Why does my Shorts forecast look different?
Shorts use a different reach model with much higher impression ceilings. Pick the Short option in the format dropdown for accurate numbers.