Instagram Related Hashtag Stats Scraper By Keyword Search

Instagram Hashtag Scraper — Post Counts, Difficulty and Niche Stats

Instagram Related Hashtag Stats Scraper By Keyword Search turns a broad niche keyword — not just a literal hashtag — into real Instagram hashtag candidates via Instagram's own search, then runs a full post-count and difficulty stats pipeline on each one. It also accepts literal hashtags directly when you already know the exact tag. It's built for hashtag research, content strategists picking a niche to target, and SEO/social teams who need real post-count data rather than a guessed hashtag list.

What is Instagram Related Hashtag Stats Scraper By Keyword Search?

Instagram Related Hashtag Stats Scraper By Keyword Search is an Apify Actor that resolves a seed keyword into real candidate hashtags via Instagram's own search/topsearch endpoint, then computes post-count and difficulty statistics for each one. A valid Instagram sessionid cookie is required — Instagram only returns hashtag/search data to logged-in traffic. Key capabilities:

• Discover real hashtag candidates from a broad niche keyword, ranked by Instagram's own media count
• Or analyze literal hashtags/tag URLs directly when you already know the exact tag
• Get each hashtag's real postsCount, a difficulty tier, and a related-hashtag breakdown (frequent/average/rare)
• Filter discovered and literal hashtags to a "goldilocks" post-count band — not too small, not too saturated
• A free, uncharged diagnostic row on failure, and a free discovery-summary row showing exactly which candidates were found and kept

What data can I extract with Instagram Related Hashtag Stats Scraper By Keyword Search?

Field	Example Value	Use Case
hashtag / url	"sustainablefashion" / hashtag explore link	Identify and link to the analyzed hashtag
sourceKeyword	"sustainable fashion"	Trace which seed keyword surfaced this hashtag
postsCount / posts	4200000 / "4.2M"	Real total post count, raw and human-formatted
postsPerDay	1150	Estimated posting velocity (see honest caveat below)
difficulty	"medium"	Tier bucket based on total post volume
section	"main"	Distinguish the primary hashtag row from its related/frequent/average/rare rows
hashtags	[{"hashtag": "ecofashion", "postsCount": 890000}]	Related hashtags discovered alongside the main one
candidatesFound / candidatesKept / keptHashtags	12 / 5 / ["sustainablefashion", "ecofashion", ...]	See exactly which discovery candidates survived your filters (discovery-summary rows only)

Post-count, difficulty, and the postsPerDay estimate

postsCount is Instagram's own real total post count for the hashtag, retrieved directly from the hashtag's info payload — not estimated. difficulty buckets that count into tiers (very_low through very_high) purely by volume. postsPerDay is an estimate with an honest limitation you should know about: Instagram doesn't expose a hashtag's actual creation date, so this Actor assumes every hashtag is approximately 10 years old (postsCount ÷ 3650 days) to derive a rough per-day rate. This systematically understates the true posting velocity of newer or rapidly-trending hashtags, and overstates it for genuinely old, slow-moving ones — treat it as a rough order-of-magnitude signal, not a precise rate.

Related hashtags: frequent, average, and rare

The related-hashtag list Instagram returns alongside your main hashtag is split into three roughly-equal-sized groups by post-count rank — frequent (the top third), average (the middle third), and rare (the bottom third). This is a relative ranking within that specific related-hashtag set, not an absolute significance threshold — a "rare" hashtag in one niche's related list could still have more posts than a "frequent" one in a smaller niche.

Why not build this yourself?

Instagram's hashtag search and info data is only served to logged-in traffic — there is no public, unauthenticated API for keyword-to-hashtag discovery or hashtag statistics at all, and no official developer API exposes this data to third parties. Building an equivalent tool yourself means maintaining a session-cookie-based authentication flow, correctly parsing Instagram's topsearch and hashtag-info payloads, and building the frequent/average/rare related-hashtag categorization logic from scratch. All of that is already implemented in this Actor's source.

How to use data extracted from Instagram?

Hashtag research and content strategy

Feed a broad niche keyword into discoveryKeywords and use minPostsCount/maxPostsCount to find the "goldilocks" hashtags — big enough to have an active audience, small enough that your content won't disappear instantly, using difficulty as a quick sanity check.

SEO and social media agencies

Run a client's core niche keywords through discovery mode and export keptHashtags/postsCount directly into a client's hashtag strategy document, comparing multiple niches side by side.

Market and niche-saturation research

Compare postsCount/difficulty across related hashtags in the same niche to understand how saturated a content category is before committing a content calendar to it.

AI agents and automated pipelines

An agent can call this Actor to pre-screen hashtag candidates before generating a content brief, filtering on difficulty and the goldilocks post-count band to avoid recommending hashtags that are dead or hopelessly saturated.

🔼 Input sample

Parameter	Required	Type	Description	Example Value
discoveryKeywords	No	array	Niche keywords to resolve into real candidate hashtags	["sustainable fashion"]
maxCandidatesPerKeyword	No	integer (1-20)	Discovered candidates run through the full stats pipeline, per keyword	5 (default)
minPostsCount	No	integer (min 0)	Skip hashtags below this post count; 0 = no minimum	0 (default)
maxPostsCount	No	integer (min 0)	Skip hashtags above this post count; 0 = no maximum	0 (default)
literalHashtags	No	array	Direct hashtags, #tags, or tag URLs to analyze exactly as typed	["#ecofashion"]
ig_sessionid	No (functionally required)	string (secret)	Instagram sessionid cookie; required — Instagram only serves this data to logged-in traffic	"(your session cookie)"
delay_between_requests	No	integer (min 0)	Seconds paused between each hashtag/keyword processed	2 (default)
proxy_configuration	No	object	Proxy settings for reliability	{"useApifyProxy": true}

{
  "discoveryKeywords": ["sustainable fashion", "home workout"],
  "maxCandidatesPerKeyword": 5,
  "minPostsCount": 50000,
  "maxPostsCount": 5000000,
  "ig_sessionid": "(your session cookie)"
}

Common pitfall: the schema marks ig_sessionid as optional, but Instagram's hashtag search and stats data is only served to logged-in traffic — without a valid cookie, the run produces diagnostic rows explaining why no data was collected instead of real hashtag stats.

🔽 Output sample

Output is typed, normalized JSON with multiple row types per hashtag (main, related, frequent, average, rare) plus a free discovery-summary row per seed keyword (exportable as JSON, CSV, or Excel).

{
  "section": "main",
  "hashtag": "sustainablefashion",
  "sourceKeyword": "sustainable fashion",
  "url": "https://www.instagram.com/explore/tags/sustainablefashion/",
  "id": "17843215",
  "postsCount": 4200000,
  "posts": "4.2M",
  "postsPerDay": 1150,
  "difficulty": "medium",
  "scrapedAt": "2026-07-26T14:02:11Z"
}

Discovery-summary rows (section: "discoverySummary") carry candidatesFound, candidatesKept, keptHashtags, and candidates (the full real list Instagram's search returned) — pushed free, not charged. Failed hashtags produce a section: "error" row, also pushed free. All 17 fields shown across row types are the Actor's real dataset columns.

How do you filter and target specific hashtags?

discoveryKeywords versus literalHashtags is the category-vs-exact-query axis: use discovery mode when you want Instagram's own search to surface candidates for a broad niche, or literal mode when you already know the exact tag. minPostsCount/maxPostsCount are the real quality thresholds — the "goldilocks band" filter that excludes hashtags too small to have an active audience or too saturated to stand out in. Volume is controlled by maxCandidatesPerKeyword, capping how many discovered candidates get the full stats pipeline per seed keyword.

{ "discoveryKeywords": ["home workout"], "minPostsCount": 100000, "maxPostsCount": 10000000, "maxCandidatesPerKeyword": 10 }

{ "literalHashtags": ["#sustainablefashion", "#slowfashion"], "ig_sessionid": "(session)" }

{ "discoveryKeywords": ["vegan recipes"], "minPostsCount": 0, "maxPostsCount": 0, "maxCandidatesPerKeyword": 3 }

▶️ Want to try other Instagram scrapers?

Scraper Name	What it extracts
Instagram Hashtag Scraper: Content Planner	Hashtag posts plus best-time and content-topic planning
Instagram Mentions Scraper & Sentiment Analysis	Inbound brand mentions with sentiment scoring
Instagram Reels Scraper With Engagement Analytics	Reel-specific collaboration and engagement analytics
Instagram Profile Scraper & Account Privacy Checker	Full profile details plus privacy-status checking
TikTok Trending Hashtags With Momentum Analytics Scraper	Comparable hashtag research data for TikTok
Google Trends Scraper: Rising & Breakout Keywords	Comparable keyword-research and spike data for Google Trends

How to extract Instagram data programmatically

Every run is a standard Apify Actor call — one API request with your token, JSON input, JSON results back.

Python example

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_API_TOKEN>")

run_input = {
    "discoveryKeywords": ["sustainable fashion"],
    "ig_sessionid": "(your session cookie)",
    "minPostsCount": 50000,
}

run = client.actor("<YOUR_USERNAME>/instagram-related-hashtag-stats-scraper-by-keyword-search").call(run_input=run_input)

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row.get("section") == "main":
        print(row["hashtag"], row["postsCount"], row["difficulty"])

Export to spreadsheets or CRM

Export the dataset directly as CSV or Excel, then map hashtag/postsCount to a hashtag-research spreadsheet template and difficulty to a prioritization column for content planning.

Is it legal to scrape Instagram hashtag statistics?

Hashtag post counts and related-hashtag lists are aggregate content statistics, not personal data tied to individual users, so this is closer to public content/business data than personal data in most contexts. Public Instagram hashtag pages are visible to any logged-in visitor. Consult legal counsel for commercial applications involving bulk automated querying of Instagram's services.

❓ FAQ

How accurate is postsPerDay?

It's a rough estimate, not a precise rate — Instagram doesn't expose a hashtag's real creation date, so the Actor assumes every hashtag is approximately 10 years old to derive a per-day figure. This understates newer, rapidly-trending hashtags and overstates old, slow ones. Treat it as an order-of-magnitude signal, not an exact number.

What does frequent/average/rare actually mean?

It's a relative ranking split of the related-hashtag list Instagram returns alongside your main hashtag — the top third by post count is "frequent," the middle third "average," and the bottom third "rare." It's not an absolute significance threshold across different niches.

Do I need to be logged into Instagram to use this?

Yes — Instagram only serves hashtag search and stats data to logged-in traffic, so a valid ig_sessionid cookie is required for the run to return real results.

Does the discovery-summary row cost extra?

No — it's pushed free, alongside the free error/diagnostic row on failure. Only the actual per-hashtag stats rows (section other than discoverySummary/error) are charged under row_result.

How many candidate hashtags can I discover per keyword?

maxCandidatesPerKeyword (1-20, default 5) caps this.

Does Instagram Related Hashtag Stats Scraper By Keyword Search work with Claude, ChatGPT, and AI agent frameworks?

It has no dedicated MCP server registration in this Actor's current setup, but it is callable as a standard Apify API endpoint by any agent framework that can make an authenticated HTTP request and parse JSON.

How does this compare to other Instagram hashtag research scrapers?

No independently verifiable competitor listing could be confirmed at the time of writing, so no specific comparison is made here. This Actor's distinguishing feature is turning a broad niche keyword into real, ranked hashtag candidates via Instagram's own search, rather than requiring you to already know the exact tag.

Can I search without knowing any hashtags in advance?

Yes — that's the purpose of discoveryKeywords: supply a broad niche phrase and Instagram's own search resolves it into real candidate hashtags for you.

Conclusion

Instagram Related Hashtag Stats Scraper By Keyword Search turns a broad niche keyword into real, ranked hashtag candidates with genuine post-count and difficulty stats — honest about where its estimates (like postsPerDay) are approximations rather than precise figures. It's built for hashtag research, content strategists, and SEO teams who need real Instagram data to pick the right niche hashtags. Start a run with your seed keywords and a valid session cookie to get hashtag stats back in one pass.