YouTube Shorts Competitor & Viral Trend Radar

Find competitor YouTube Shorts that are gaining views between your checks, then decide which videos deserve a closer look. Monitor channel URLs or search topics, export public metrics, and build a history of rising, accelerating and declining view velocity.

Built for creators, content strategists and agencies reviewing a niche or a competitor watchlist. No YouTube API key or sign-in is required.

What you will get

• One row per observed Short with its title, channel, source link, exact public views and available engagement metrics.
• Measured views gained, the comparison window and average views per hour between saved observations.
• A clear monitoring state, including BASELINE, RISING or ACCELERATING when supported by history.
• A ranked dataset, a JSON report and an HTML dashboard linking back to the videos.

Use the results for a daily competitor review, a shortlist of videos to study, or recurring content-research exports. The sample is bounded by your source and request limits.

Example: views gained versus total views

The following values are an illustrative calculation, not captured YouTube data. They follow one hypothetical Short using the default 100 views/hour rising threshold and 1.5 acceleration factor:

Check	Public views	Gained since prior check	Measured views/hour	State
09:00	10,000	—	—	BASELINE
12:00	16,000	6,000	2,000	RISING
15:00	25,000	9,000	3,000	ACCELERATING

The last interval is 1.5 times faster than the previous one. A first run cannot measure growth. Two sufficiently spaced observations can measure velocity; acceleration requires three. This is observed public-counter movement, not a forecast of future virality.

Start with five Shorts

1. Paste one channel's Shorts URL, or enter one specific search topic.
2. Run the input below and inspect the dataset plus OUTPUT coverage.
3. Save the input as a Task. Rerun at least 60 minutes later with the same sources, country and history profile; daily checks are also useful.

{
  "channelUrls": ["https://www.youtube.com/@NASA/shorts"],
  "searchQueries": [],
  "country": "US",
  "maxAgeDays": 0,
  "maxShorts": 5,
  "maxDetailRequests": 15,
  "saveHistory": true,
  "historyProfile": "competitor-shorts-watch"
}

NASA is a demonstration source, not a guaranteed current result. Replace it with your competitor channels. For topic discovery, set channelUrls to [] and use searchQueries, for example ["hiking gear"]. You can combine channels and queries, up to ten of each.

Use 512 MB memory and a 300-second platform timeout for the initial run. maxAgeDays: 0 disables publication-age filtering, including when a publication date is unknown. A positive age limit excludes unknown dates. Country localizes discovery; it does not filter creator residence or audience geography.

Pricing

$0.002 per delivered Shorts observation ($2 per 1,000), plus $0.01 per started GB for the run start, minimum one.

At 512 MB, five emitted observations cost $0.02 in event fees; 25 cost $0.06. These examples assume one start charge and the stated row count. Repeated observations of the same Short are billable results because each run collects a new observation. A zero-result run still incurs the start fee. Check the active Pricing tab for current rates and any separately applicable platform or proxy charges.

Set a maximum run charge, maxShorts, maxDetailRequests and maxRunSeconds to keep research bounded. Filters can reduce output without avoiding the collection work. Optional proxy traffic can add cost.

API and your research workflow

Export JSON, CSV or Excel, or call Actor ID mpbOhdxwg50EARNme through the Apify API. The same input can be used through Apify MCP. Save Tasks and configure schedules or completion webhooks in your own Apify account.

POST https://api.apify.com/v2/actors/mpbOhdxwg50EARNme/runs
Authorization: Bearer YOUR_APIFY_TOKEN
Content-Type: application/json

Send the input above as JSON. After the run completes, retrieve its default dataset. The default key-value store also contains OUTPUT, REPORT and DASHBOARD.

When to use this Actor

• Track your selected competitor channels and compare new observations over time.
• Recheck topic-discovered Shorts after a meaningful interval.
• Export rising-video evidence into a content planning table.

For broader topic research spanning Shorts and long-form videos, see YouTube Viral & Trend Radar.

The reference below explains fields, states and coverage so you can interpret results correctly.

Output fields and states

Fields	Meaning
videoId, url, title, channel	Video identity, source link and public metadata
views, likes, comments, subscribers	Exact views and available public counters; subscriber rounding is flagged
viewsDelta, comparisonHours, baselineAt	Evidence behind the measured comparison
measuredViewsPerHour	Exact view-counter change divided by elapsed observation hours
priorMeasuredViewsPerHour, velocityRatio	Previous interval rate and current/previous ratio
averageViewsPerHourSincePublished	Lifetime average, requiring timestamp precision and age of at least one hour; not recent measured growth
publishedAt, publishedAtPrecision, ageHours	Available publication time and its precision
viralScore, hookSignals, metricWarnings	Research signals and their limitations

BASELINE is the first observation. NEW means first seen after this profile began, not necessarily newly published. INSUFFICIENT_INTERVAL and STALE_BASELINE mean a usable comparison is unavailable.

RISING meets the configured hourly threshold. ACCELERATING requires a current rate at least accelerationFactor times the prior measured rate, with the rising threshold also met. DECLINING describes a slower rate, even while total views keep growing. A negative counter correction restarts the series; it is not reported as negative growth.

Intervals must fall between minIntervalMinutes and maxComparisonHours (defaults: 60 minutes and 72 hours). Rates are calculated using each interval's own duration. A zero prior rate leaves the ratio undefined.

The deterministic score weights measured pace, available like rate and acceleration. It is absent until velocity is measurable and is not a probability of virality. Missing engagement can reduce the score; inspect metric warnings. Hook flags use English title-text rules, not the video's audio or visual opening.

Coverage, history and troubleshooting

Discovery reads public channel Shorts tabs and Shorts-filtered searches. Default discovery is up to 30 candidates and two pages per source. maxShorts caps delivered rows; maxDetailRequests includes detail requests, comment enrichment, retries and filtered or failed candidates. Defaults include comments and up to two retries within the existing budgets.

Exact public views are required for a usable observation. Missing likes or comments remain null; rounded comment labels are kept separately and excluded from exact engagement rates. Publication dates may have day-only precision. Shares, retention, watch time, audience geography and media downloads are not provided.

History is private to a named key-value store scoped by Actor ID, history profile, normalized sources and country. Keep these settings consistent and avoid overlapping runs. Failed requests do not erase a valid baseline. Missing discovery results do not establish deletion or takedown. History is bounded rather than a permanent archive.

The Actor combines previously tracked candidates with newly discovered ones, but the result remains a sample. Search rankings, site changes, filters and request limits can reduce coverage. If datacenter requests are blocked, configure proxyConfiguration and review the resulting costs and coverage.

Check OUTPUT.status, historySaved, source diagnostics, applied filters and emptyResultReason. The platform run can succeed with PARTIAL output when some usable rows were collected. A valid zero-match scan differs from an access or extraction failure. REPORT and DASHBOARD describe the same collected sample, not every Short in the niche.

Independent NexaScout tool; not affiliated with YouTube or Google. For support, include the run URL, source channel or query, history profile and the expected comparison.