Instagram Hashtag Analytics

See how Reel-heavy an Instagram hashtag is and who actually posts in it. Each hashtag gets Reel analytics, creator analytics and median engagement from a sample of up to 500 public posts and Reels, exported as one clean analytics report per hashtag in JSON, CSV or Excel.

What this actor does

Instagram Hashtag Analytics takes one or more hashtags and returns one report row per hashtag, not thousands of raw posts:

• 🎬 Reels: Reel share of the sample, plus Reel likes, comments, views, plays, length and original-audio share, so you can tell a Reel-driven hashtag from a photo one
• 👥 Creators: unique creators, verified creators and their share, the share of the sample posted by the 10 busiest creators, and the top 10 creators with their post counts and average engagement
• 📊 Engagement: average and median likes, comments, video views and plays, totals, and an observed engagement rate for Reels/videos
• 🔬 Deep samples: 10 to 500 posts per hashtag, from the Top feed, the Recent feed or both
• 🧮 Honest denominators: every metric says how many sampled posts it was computed from (likesAvailableFor, playsAvailableFor, …)
• 🙈 No fake zeros: hidden likes and missing views are left out of the math, never counted as 0
• 🖼️ Content mix: Reels, images, carousels and other videos with their shares
• 📈 Volume: the post count Instagram displays for the hashtag
• #️⃣ Co-occurring hashtags: which other hashtags appear alongside it in the sampled captions, and how often
• 🏆 Top posts: compact examples of the best-performing sampled posts
• 🔎 Coverage metadata: sample mode, how many posts were requested and returned, Top/Recent overlap, oldest and newest sampled post, and a coverage status

Several hashtags in one run give you directly comparable rows, so you can sort them side by side in a spreadsheet. The run summary also names the leaders: largest hashtag, highest average likes, highest Reel share, most diverse creators.

How it works

1. Normalize hashtags. fitness, #Fitness and https://www.instagram.com/explore/tags/fitness/ all become fitness. Duplicates are removed. Invalid entries get a free INVALID_HASHTAG row.
2. Sample. For each hashtag the actor reads Instagram's Top feed, its Recent feed, or both (the default), until it has the sample size you asked for.
3. Deduplicate. A post that appears in both Top and Recent is counted once. Its appearedInTop / appearedInRecent flags are kept, and the Recent feed tops the sample back up so the overlap doesn't shrink it.
4. Analyze. Averages, medians, mixes, creator stats and co-occurring hashtags are computed from the sample, using only the values Instagram actually shows.
5. Report. One row per hashtag, plus free status rows for hashtags that couldn't be analyzed.

It runs without a browser, and needs no Instagram login and no cookies of yours.

FAQ

What does this actor analyze? Public Instagram hashtags. For each one you get volume, engagement, content mix, Reel, creator and co-occurring-hashtag analytics built from a sample of its public posts and Reels.

How is it different from Instagram Hashtag Scraper? Instagram Hashtag Scraper returns the raw posts, one row per post. This actor uses the same extraction code but returns one summary report per hashtag. Use the scraper when you need every post, and this actor when you need the answer: which hashtag is bigger, more engaged, more Reel-heavy or dominated by a few creators.

Is this complete historical hashtag data? No. Instagram does not expose a complete public history for a hashtag. Every metric is an observed sample metric built from the posts that were sampled, and every report says exactly what that sample was: mode, size, time range and coverage. The one exception is availablePostsCount, which is the count Instagram itself displays. It is never derived from the sample, and it is null when the feed doesn't return it.

What does sample size mean? sampleSizePerHashtag is the total number of unique posts and Reels to analyze per hashtag (10–500, default 100). In TOP_AND_RECENT mode it is split about 50/50 between the two feeds. Small or niche hashtags may return fewer. The report shows sampleRequested and sampleReturned, and coverageStatus explains any gap.

What is TOP vs RECENT? They are Instagram's two hashtag tabs. TOP is ranked by Instagram and gives a quality, high-engagement snapshot. RECENT is the newest posts and shows current activity. TOP_AND_RECENT (the default) combines them for a balanced research view.

Are averages based on visible values only? Yes. Each average and median uses only the posts where Instagram shows that number, and the …AvailableFor field next to it gives the count. For example, avgLikes: 1851 with likesAvailableFor: 36 means 36 sampled posts had visible likes.

Are hidden likes treated as zero? Never. A post with hidden likes is left out of the like metrics and counted in likesHiddenCount. Missing views and plays are handled the same way.

Are Reels included? Yes. Reels are identified from Instagram's own labelling, and reelShare tells you how Reel-heavy a hashtag is. A video Instagram doesn't mark as a Reel is counted as videosNonReel, not guessed.

Are views and plays included? Yes, separately, because Instagram reports them as different metrics: avgPlays / medianPlays and avgViews / medianViews, plus Reel-only versions. engagementRateObserved = (likes + comments) ÷ plays over Reels and videos where all three are visible. It is a Coregent-derived sample metric, not an Instagram-native rate, and it is null when fewer than 5 videos qualify.

Are creator analytics included? Yes: uniqueCreators, verifiedCreators, verifiedCreatorShare, top10CreatorShare (the share of sampled posts made by the 10 most frequent creators) and up to 10 topCreators with their post counts and average engagement. They are computed from the sampled posts only. The actor does no extra profile lookups.

What are co-occurring hashtags? The other hashtags used in the sampled captions, with how many sampled posts used each (count) and the share of the sample (sampleShare). They are case-normalized and exclude the hashtag you're analyzing.

Are related hashtags platform-provided or sample-derived? Sample-derived. cooccurringHashtags comes from the captions of the posts in this sample. The actor does not mix in any Instagram-provided "related hashtags" list.

How many hashtags can I analyze? Up to 100 per run, analyzed in parallel (maxConcurrency, default 5).

How does pricing work? You pay per completed hashtag report, not per sampled post: one charge per started 100 sampled posts, so a standard 100-post report is one charge and a 500-post report is five. Invalid hashtags, hashtags with no public posts, partial samples cut short by an upstream error, and error rows are free. The rate can differ by Apify plan; see the Pricing tab for the current rate on yours. This README deliberately doesn't quote figures.

Can I use the API or MCP? Yes. Like every Apify Actor it can be run through the Apify API, the JavaScript and Python clients, integrations (Make, Zapier, n8n…) and the Apify MCP server, so AI agents can call it as a tool.

Can I schedule recurring reports? Yes. Create an Apify Schedule (for example daily or weekly) with your hashtag list and compare the reports over time. Each run is an independent snapshot.

Input

Field	Type	Default	Description
hashtags	string[]	["fitness"]	Hashtags, with or without #, or /explore/tags/<tag>/ URLs. Up to 100
sampleMode	enum	TOP_AND_RECENT	TOP, RECENT or TOP_AND_RECENT (split ~50/50)
sampleSizePerHashtag	integer	100	Total unique posts to analyze per hashtag, 10–500 (common: 25, 50, 100, 250, 500)
minPostDate	string	empty	Only sample posts from this date on: ISO date (2026-09-01) or a period (7 days)
includeMediaMix	boolean	true	Reels / images / carousels / other videos and their shares
includeReelAnalytics	boolean	true	Reel likes, comments, plays, views, length, original-audio share
includeCreatorAnalytics	boolean	true	Unique / verified creators, top-10 share, top creators
includeCooccurringHashtags	boolean	true	Hashtags used alongside the analyzed one
maxRelatedHashtags	integer	25	Co-occurring hashtags listed per report (0–100)
includeTopExamples	boolean	true	Best-performing sampled posts
maxTopExamples	integer	10	Top posts per report (0–50)
includeRawSample	boolean	false	Attach every sampled post (compact form) to its report as samplePosts
maxConcurrency	integer	5	Hashtags analyzed in parallel (1–8)
debugMode	boolean	false	Verbose logging

Engagement and coverage are always included. Turning a section off leaves its columns null, so every row keeps the same columns.

Tip: if you paste JSON into the Console's JSON editor, include the five include… switches as in Example 2. Switches missing from pasted JSON can be saved as off, which leaves those report sections empty. Through the API, missing switches default to on.

Example 1: One hashtag

{
  "hashtags": ["fitness"],
  "sampleMode": "TOP_AND_RECENT",
  "sampleSizePerHashtag": 100
}

Example 2: Compare 20 hashtags

The run behind the comparison table under Output: one report per hashtag.

{
  "hashtags": [
    "fitness", "travel", "food", "photography", "fashion",
    "art", "nature", "music", "beauty", "gym",
    "yoga", "skincare", "coffee", "dogsofinstagram", "catsofinstagram",
    "makeup", "streetstyle", "foodie", "wanderlust", "interiordesign"
  ],
  "sampleMode": "TOP_AND_RECENT",
  "sampleSizePerHashtag": 50,
  "includeMediaMix": true,
  "includeReelAnalytics": true,
  "includeCreatorAnalytics": true,
  "includeCooccurringHashtags": true,
  "includeTopExamples": true,
  "maxConcurrency": 5
}

Example 3: Recent campaign analysis

{
  "hashtags": ["brandcampaign2026"],
  "sampleMode": "RECENT",
  "sampleSizePerHashtag": 250,
  "minPostDate": "30 days",
  "includeTopExamples": true
}

Example 4: Deep research on one hashtag

{
  "hashtags": ["skincare"],
  "sampleMode": "TOP_AND_RECENT",
  "sampleSizePerHashtag": 500,
  "maxRelatedHashtags": 50,
  "maxTopExamples": 20
}

Output

One row per hashtag. Report rows have rowType: "hashtag_analytics"; hashtags that couldn't be analyzed get a free row with rowType: "error". Every row has the same keys, and a section you turn off leaves its columns null, so CSV and Excel exports keep stable columns. Top-level metrics are flat for easy comparison; creators, co-occurring hashtags and examples are nested arrays.

The dataset has six tabs:

Tab	What it shows
Hashtag reports	The headline comparison: volume, sample size, likes, comments, plays, Reel share, creators
Engagement	Averages, medians, totals and denominators for likes, comments, views and plays
Content mix & Reels	Reels / images / carousels / other videos, shares and Reel metrics
Creators	Unique and verified creators, top-10 share, top creators
Co-occurring hashtags & top posts	Hashtags used alongside and the best-performing sampled posts
Sample coverage & status	Mode, requested/returned, Top/Recent split, time range, coverage status, errors

The samples below are real rows from runs with sampleSizePerHashtag: 50 on October 16, 2026. Nested arrays are shortened to their first entries.

Engagement table view: 20 hashtags in one run

Comparing hashtags

The same 20-hashtag run, sorted by observed engagement rate. Medians far below averages show where a few viral posts carry a hashtag: #fitness averages 338.2 likes but its median post has 3.

Hashtag	Avg likes	Median likes	Hidden likes	Avg plays	Median plays	Engagement rate (videos)
#travel	1,063.8	287	7	21,766.5	9,336	9.4% (14)
#catsofinstagram	626.8	134	3	13,255	10,648.5	9.0% (10)
#makeup	657.4	309	12	16,027.7	7,164.5	8.3% (14)
#nature	363	5.5	4	11,293.7	10,293.5	7.5% (15)
#music	1,430.3	8	6	57,197	6,338.5	5.8% (14)
#wanderlust	859.8	2	10	57,926	14,314	5.8% (5)
#fitness	338.2	3	4	10,899.7	7,189	5.8% (14)
#yoga	526.8	3	9	29,888.4	14,974	5.5% (14)
#skincare	559	1	1	24,691.1	11,807	5.5% (18)
#art	241.3	1	8	9,753.2	3,626	5.2% (11)
#dogsofinstagram	330.2	3	4	17,783	17,831	4.2% (18)
#coffee	757	267.5	4	41,796.4	47,279.5	4.2% (14)
#gym	1,318.8	142.5	6	96,886	8,153	3.8% (13)
#interiordesign	671.4	4	1	53,549.8	18,568.5	3.5% (12)
#food	350	3	3	24,936.3	16,745	3.3% (19)
#photography	300.7	150	8	16,034.4	10,507	2.9% (8)
#foodie	330.5	144	2	27,883.6	20,435	2.9% (18)
#streetstyle	495.9	5	15	48,857.7	10,344	2.3% (5)
#beauty	538.9	391.5	6	52,708.8	24,669.5	2.3% (15)
#fashion	382.1	23	9	21,263.4	13,933	2.2% (9)

Engagement rate = (likes + comments) ÷ plays, over the Reels and videos in the bracketed count.

Full record: #fitness (a separate one-hashtag run with every section on)

{
  "rowType": "hashtag_analytics",
  "status": "SUCCESS",
  "errorMessage": null,
  "hashtag": "fitness",
  "url": "https://www.instagram.com/explore/tags/fitness/",
  "input": "fitness",
  "queryIndex": 0,
  "availablePostsCount": null,
  "sampleMode": "TOP_AND_RECENT",
  "sampleRequested": 50,
  "sampleReturned": 50,
  "topReturned": 25,
  "recentReturned": 25,
  "duplicatesRemoved": 0,
  "oldestObservedAt": "2026-10-15T16:34:28.000Z",
  "newestObservedAt": "2026-10-16T13:45:41.000Z",
  "coverageStatus": "FULL_REQUESTED_SAMPLE",
  "coverageNote": null,
  "avgLikes": 331.6,
  "medianLikes": 37,
  "likesAvailableFor": 45,
  "likesHiddenCount": 4,
  "totalVisibleLikes": 14924,
  "avgComments": 14.2,
  "medianComments": 1,
  "commentsAvailableFor": 49,
  "totalComments": 695,
  "avgViews": null,
  "medianViews": null,
  "viewsAvailableFor": 0,
  "avgPlays": 15408.4,
  "medianPlays": 13879,
  "playsAvailableFor": 17,
  "engagementRateObserved": 0.0485,
  "engagementRateAvailableFor": 17,
  "reels": 17,
  "images": 15,
  "carousels": 18,
  "videosNonReel": 0,
  "reelShare": 0.34,
  "imageShare": 0.3,
  "carouselShare": 0.36,
  "videoNonReelShare": 0,
  "reelCount": 17,
  "avgReelLikes": 720.7,
  "medianReelLikes": 495,
  "avgReelComments": 26.9,
  "avgReelViews": null,
  "medianReelViews": null,
  "avgReelPlays": 15408.4,
  "medianReelPlays": 13879,
  "avgReelDurationSeconds": 41.3,
  "reelDurationAvailableFor": 17,
  "originalAudioShare": 0.625,
  "reelAudioAvailableFor": 16,
  "uniqueCreators": 49,
  "creatorsAvailableFor": 50,
  "verifiedCreators": 15,
  "verifiedCreatorShare": 0.3061,
  "top10CreatorShare": 0.22,
  "topCreators": [
    {
      "username": "msk_fitness_coach",
      "userId": "2296923244",
      "profileUrl": "https://www.instagram.com/msk_fitness_coach/",
      "postsInSample": 2,
      "reelsInSample": 0,
      "avgLikes": 8,
      "avgComments": 0,
      "avgPlays": null,
      "avgViews": null,
      "isVerified": false
    },
    {
      "username": "jaquelineoliv",
      "userId": "361363753",
      "profileUrl": "https://www.instagram.com/jaquelineoliv/",
      "postsInSample": 1,
      "reelsInSample": 1,
      "avgLikes": 2110,
      "avgComments": 35,
      "avgPlays": 63849,
      "avgViews": null,
      "isVerified": true
    }
  ],
  "cooccurringHashtags": [
    {
      "hashtag": "gym",
      "count": 12,
      "sampleShare": 0.24
    },
    {
      "hashtag": "motivation",
      "count": 6,
      "sampleShare": 0.12
    }
  ],
  "cooccurringHashtagsDistinct": 127,
  "recentSampleObservedHours": 0.07,
  "recentSamplePostsPerDay": 8674.7,
  "topExamples": [
    {
      "id": "4009224371956556526",
      "shortCode": "DejoFMTTyLu",
      "url": "https://www.instagram.com/reel/DejoFMTTyLu/",
      "contentType": "REEL",
      "mediaType": "VIDEO",
      "captionPreview": "Apaga agora 😭😂 @fernandaferraz.nutrologa @brunosetenta @fauvalentenutri Vocês fazem parte disso, obrigada! . . . #fitness #meme #humor #w…",
      "creatorUsername": "jaquelineoliv",
      "likesCount": 2110,
      "likesHidden": false,
      "commentsCount": 35,
      "videoPlayCount": 63849,
      "videoViewCount": null,
      "timestamp": "2026-10-16T13:21:52.000Z",
      "appearedInTop": true,
      "appearedInRecent": false
    },
    {
      "id": "4008626304747787586",
      "shortCode": "DehgGKzx1VC",
      "url": "https://www.instagram.com/reel/DehgGKzx1VC/",
      "contentType": "REEL",
      "mediaType": "VIDEO",
      "captionPreview": "Imagine being more bothered by a woman’s gym outfit than your own lack of discipline. 😘 #explorepage #fyp #fitnessmotivation #fitness #wom…",
      "creatorUsername": "ttheasiawilliams",
      "likesCount": 1837,
      "likesHidden": false,
      "commentsCount": 31,
      "videoPlayCount": 17435,
      "videoViewCount": null,
      "timestamp": "2026-10-15T17:33:36.000Z",
      "appearedInTop": true,
      "appearedInRecent": false
    }
  ],
  "samplePosts": null,
  "scrapedAt": "2026-10-16T13:46:01.010Z"
}

Hashtag reports tab

{
  "hashtag": "fitness",
  "availablePostsCount": null,
  "sampleReturned": 50,
  "coverageStatus": "FULL_REQUESTED_SAMPLE",
  "avgLikes": 331.6,
  "medianLikes": 37,
  "avgComments": 14.2,
  "medianPlays": 13879,
  "reelShare": 0.34,
  "uniqueCreators": 49,
  "top10CreatorShare": 0.22,
  "engagementRateObserved": 0.0485,
  "url": "https://www.instagram.com/explore/tags/fitness/",
  "status": "SUCCESS"
}

Engagement tab: hidden likes left out of the math

Seven of the 50 sampled #travel posts hide their likes, so the like metrics use the other 43 (likesAvailableFor). No sampled post exposed a view count, so views are null rather than 0.

{
  "hashtag": "travel",
  "sampleReturned": 50,
  "avgLikes": 1063.8,
  "medianLikes": 287,
  "likesAvailableFor": 43,
  "likesHiddenCount": 7,
  "totalVisibleLikes": 45742,
  "avgComments": 11.9,
  "medianComments": 0.5,
  "commentsAvailableFor": 50,
  "totalComments": 595,
  "avgViews": null,
  "medianViews": null,
  "viewsAvailableFor": 0,
  "avgPlays": 21766.5,
  "medianPlays": 9336,
  "playsAvailableFor": 15,
  "engagementRateObserved": 0.0936,
  "engagementRateAvailableFor": 14
}

Content mix & Reels tab

{
  "hashtag": "fitness",
  "sampleReturned": 50,
  "reels": 17,
  "images": 15,
  "carousels": 18,
  "videosNonReel": 0,
  "reelShare": 0.34,
  "imageShare": 0.3,
  "carouselShare": 0.36,
  "avgReelLikes": 720.7,
  "avgReelPlays": 15408.4,
  "medianReelPlays": 13879,
  "avgReelDurationSeconds": 41.3,
  "originalAudioShare": 0.625
}

Creators tab

{
  "hashtag": "fitness",
  "sampleReturned": 50,
  "uniqueCreators": 49,
  "creatorsAvailableFor": 50,
  "verifiedCreators": 15,
  "verifiedCreatorShare": 0.3061,
  "top10CreatorShare": 0.22,
  "topCreators": [
    {
      "username": "msk_fitness_coach",
      "userId": "2296923244",
      "profileUrl": "https://www.instagram.com/msk_fitness_coach/",
      "postsInSample": 2,
      "reelsInSample": 0,
      "avgLikes": 8,
      "avgComments": 0,
      "avgPlays": null,
      "avgViews": null,
      "isVerified": false
    },
    {
      "username": "jaquelineoliv",
      "userId": "361363753",
      "profileUrl": "https://www.instagram.com/jaquelineoliv/",
      "postsInSample": 1,
      "reelsInSample": 1,
      "avgLikes": 2110,
      "avgComments": 35,
      "avgPlays": 63849,
      "avgViews": null,
      "isVerified": true
    }
  ]
}

Co-occurring hashtags & top posts tab

{
  "hashtag": "fitness",
  "sampleReturned": 50,
  "cooccurringHashtagsDistinct": 127,
  "cooccurringHashtags": [
    {
      "hashtag": "gym",
      "count": 12,
      "sampleShare": 0.24
    },
    {
      "hashtag": "motivation",
      "count": 6,
      "sampleShare": 0.12
    }
  ],
  "topExamples": [
    {
      "id": "4009224371956556526",
      "shortCode": "DejoFMTTyLu",
      "url": "https://www.instagram.com/reel/DejoFMTTyLu/",
      "contentType": "REEL",
      "mediaType": "VIDEO",
      "captionPreview": "Apaga agora 😭😂 @fernandaferraz.nutrologa @brunosetenta @fauvalentenutri Vocês fazem parte disso, obrigada! . . . #fitness #meme #humor #w…",
      "creatorUsername": "jaquelineoliv",
      "likesCount": 2110,
      "likesHidden": false,
      "commentsCount": 35,
      "videoPlayCount": 63849,
      "videoViewCount": null,
      "timestamp": "2026-10-16T13:21:52.000Z",
      "appearedInTop": true,
      "appearedInRecent": false
    },
    {
      "id": "4008626304747787586",
      "shortCode": "DehgGKzx1VC",
      "url": "https://www.instagram.com/reel/DehgGKzx1VC/",
      "contentType": "REEL",
      "mediaType": "VIDEO",
      "captionPreview": "Imagine being more bothered by a woman’s gym outfit than your own lack of discipline. 😘 #explorepage #fyp #fitnessmotivation #fitness #wom…",
      "creatorUsername": "ttheasiawilliams",
      "likesCount": 1837,
      "likesHidden": false,
      "commentsCount": 31,
      "videoPlayCount": 17435,
      "videoViewCount": null,
      "timestamp": "2026-10-15T17:33:36.000Z",
      "appearedInTop": true,
      "appearedInRecent": false
    }
  ]
}

Sample coverage & status tab

recentSamplePostsPerDay extrapolates from the time span the Recent sample covers. On a very busy hashtag 25 Recent posts can cover only a few minutes (recentSampleObservedHours: 0.05 here), so treat it as an order of magnitude; larger samples give a steadier figure.

{
  "hashtag": "travel",
  "status": "SUCCESS",
  "errorMessage": null,
  "sampleMode": "TOP_AND_RECENT",
  "sampleRequested": 50,
  "sampleReturned": 50,
  "topReturned": 25,
  "recentReturned": 25,
  "duplicatesRemoved": 0,
  "oldestObservedAt": "2026-10-15T17:39:46.000Z",
  "newestObservedAt": "2026-10-16T16:40:39.000Z",
  "recentSampleObservedHours": 0.05,
  "recentSamplePostsPerDay": 11020.41,
  "coverageStatus": "FULL_REQUESTED_SAMPLE",
  "coverageNote": null,
  "input": "travel",
  "scrapedAt": "2026-10-16T16:40:54.676Z"
}

Coverage status

Value	Meaning
FULL_REQUESTED_SAMPLE	The requested sample size was reached
LOW_RESULT_HASHTAG	Instagram returned fewer public posts than requested
BOUNDED_SAMPLE	The minPostDate window ended the sample early
PARTIAL_SAMPLE	An upstream error cut the sample short. The report is delivered free
NO_RESULTS	No public posts were found

Status values

Status	Meaning	Charged
SUCCESS	Report built	Yes, one charge per started 100 sampled posts
PARTIAL_SAMPLE	Report built from an interrupted sample	No
NO_RESULTS	The hashtag has no public posts (in the date window)	No
INVALID_HASHTAG	Not a valid hashtag	No
HASHTAG_UNAVAILABLE	Instagram has no public hashtag by that name (hidden or restricted)	No
RATE_LIMITED / BLOCKED / PROVIDER_ERROR	Temporary upstream problem, safe to retry	No
ANALYTICS_ERROR	The sample could not be analyzed	No

One failed hashtag never fails the run.

Run summary and retry input

The key-value store record RUN_SUMMARY holds the run totals (hashtags requested, succeeded, failed, reports saved, sampled posts processed, Top/Recent duplicates removed), metric availability rates, and a comparison of the hashtags in the run (largest hashtag, highest average and median likes, highest Reel share, most diverse creators, highest observed engagement rate). Hashtags that failed for a temporary reason are saved in RETRY_INPUT, ready to re-run.

Use it from code (API)

The actor works with the Apify API and the official clients. Get your API token in Apify Console under Settings → API & Integrations. Results are the same rows as in the dataset tabs above.

JavaScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });
const run = await client.actor('coregent/instagram-hashtag-analytics').call({
  hashtags: ['fitness', 'workout', 'gym'],
  sampleSizePerHashtag: 100,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
const reports = items.filter((row) => row.rowType === 'hashtag_analytics'); // status rows have rowType "error"
reports.sort((a, b) => (b.medianLikes ?? 0) - (a.medianLikes ?? 0));

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("coregent/instagram-hashtag-analytics").call(run_input={
    "hashtags": ["fitness", "workout", "gym"],
    "sampleSizePerHashtag": 100,
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
reports = [row for row in items if row["rowType"] == "hashtag_analytics"]  # status rows have rowType "error"

HTTP (one call that runs the actor and returns its rows; suits small runs that finish within the API's 5-minute synchronous limit):

curl -X POST "https://api.apify.com/v2/acts/coregent~instagram-hashtag-analytics/run-sync-get-dataset-items" \
  -H "Authorization: Bearer <YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"hashtags": ["fitness", "travel"], "sampleSizePerHashtag": 50}'

For larger runs, start the actor asynchronously (POST /v2/acts/coregent~instagram-hashtag-analytics/runs) and read the dataset when it finishes, or use the client libraries above, which wait for you. The run's RUN_SUMMARY record (key-value store) holds the cross-hashtag comparison.

Pricing

Pay per event: completed hashtag reports are charged once per started 100 sampled posts. Deeper samples need more upstream work, so a 100-post report is one charge, a 250-post report three and a 500-post report five. A hashtag with fewer posts than requested is charged for the posts actually sampled. Sampled posts are never charged individually, and free rows (see the status table) cost nothing. The run only starts a hashtag your spending limit can cover at its full sample size, and stops cleanly when the limit is reached. The rate can differ by Apify plan; see the Pricing tab for the current rate on yours. This README deliberately doesn't quote figures.

Limitations

• Metrics describe the sample, not every post that ever used the hashtag. Engagement counts also change over time.
• Instagram decides what its Top and Recent tabs show. Small, new or restricted hashtags may return fewer posts than requested.
• availablePostsCount is Instagram's displayed count where it is exposed, not an independently verified total.
• Some sampled posts may show no creator username when Instagram's fallback feed only names the creator's numeric id. Creator metrics still count them by id, and creatorsAvailableFor shows the coverage.
• The actor reports what Instagram shows and does not invent scores. There is no proprietary "difficulty" or trend prediction.

Related actors

• Instagram Hashtag Scraper: the raw posts and Reels behind each hashtag
• Instagram Search Scraper: discover hashtags to analyze
• Instagram Profile Scraper: deep profiles of the top creators you find

Legal and privacy

This is an unofficial product and is not affiliated with Instagram or Meta. It processes public content only, and analytics are based on available public samples, not guaranteed platform-wide totals. Public creator data can still be personal data: you are responsible for lawful use of the results, including GDPR/CCPA where they apply.

Local development

cd actor
npm install
npm test     # unit tests
npm start    # runs INPUT.json; needs TIKHUB_API_KEY or the local "tikhub-config" key-value store

For an offline smoke test that spends no upstream balance, point TIKHUB_BASE_URL at a local mock server and set TIKHUB_API_KEY=fake.