Apify to Google Sheets, qualified Instagram leads

Manual Instagram lead research is a time sink. You copy usernames from hashtag posts, open profiles one-by-one, guess who’s relevant, and still end up with a messy list you don’t trust.

This Instagram lead automation hits growth marketers first, but founders and agency operators feel it too. When you’re doing outreach, you need a clean, qualified sheet, not a pile of “maybe” profiles.

This workflow pulls hashtags from Google Sheets, uses Apify to collect real profiles from Instagram hashtag posts, then filters, dedupes, and qualifies leads by language and follower range. You’ll see how it works, what you need, and where teams usually get stuck.

How This Automation Works

Here’s the complete workflow you’ll be setting up:

n8n Workflow Template: Apify to Google Sheets, qualified Instagram leads

Click to explore

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Why This Matters: Hashtag leads get messy fast

Hashtag research sounds simple until you do it at scale. You check a hashtag, skim posts, click into profiles, then try to remember which ones looked promising. Ten minutes here, ten minutes there, and suddenly you’ve burned an afternoon without a usable list. Worse, manual research makes you inconsistent. Some days you’re strict about follower count, other days you’re tired and add “close enough” accounts. Then outreach performance drops and you don’t know if the offer is the issue, or the targeting.

The friction compounds. Here’s where it usually breaks down.

You lose time jumping between hashtag feeds, posts, and profile pages for every single candidate.
Your list fills with duplicates because the same creator appears under multiple hashtags.
Language mismatch sneaks in, so outreach gets ignored because the audience isn’t actually your market.
Follower counts get checked “later,” which means they often never get checked at all.

What You’ll Build: Hashtags in, qualified leads out

This workflow turns a simple hashtag list into a structured lead database you can actually use. It starts by reading hashtags from a Google Sheet, then automatically generates the right Instagram explore URLs for each tag. From there, it calls Apify (via HTTP Request) to scrape posts for each hashtag and pulls key data like captions and usernames. Next comes the “cleanup” part: captions are normalized to remove links and hashtags, then the workflow checks that the post isn’t just hashtag spam and validates the language (English is built in, and the workflow description notes French and Spanish can be supported too). Finally, usernames are merged, duplicates are removed, each profile is scraped for details like follower count, and only profiles inside your target range are kept as qualified leads.

The workflow begins with your existing Google Sheet. Apify collects post and profile data at speed, while n8n handles the filtering logic so you don’t have to second-guess every lead. Your output is a deduped set of profiles that match your language and follower criteria, ready for outreach or analysis.

What You’re Building

What Gets Automated

What You’ll Achieve

Pulling your hashtag queue directly from Google Sheets.
Scraping Instagram hashtag posts through Apify without manual browsing.
Cleaning captions and filtering out low-signal “hashtag only” posts.
Fetching profile details and validating follower count automatically.

Turn an hour of manual clicking into about 10 minutes of setup and review.
A single lead list that stays consistent week after week.
Fewer duplicates, so you don’t message the same account twice.
Better targeting because language and content get screened early.
A Google Sheet you can hand off to a VA or SDR confidently.

Expected Results

Say you research 20 hashtags per week and grab 15 profiles per hashtag. Manually, if you spend maybe 2 minutes per profile to open the page, check language cues, and eyeball follower count, that’s about 10 hours of work. With this workflow, you can trigger the run from your hashtag sheet, let Apify collect posts and profiles in the background, then review the qualified output in one pass. Most teams get that weekly job down to about an hour of oversight.

Before You Start

n8n instance (try n8n Cloud free)
Self-hosting option if you prefer (Hostinger works well)
Apify for scraping hashtag posts and profiles.
Google Sheets to store hashtags and lead output.
Apify API key (get it from your Apify account settings).

Skill level: Beginner. You’ll connect accounts, paste an API key, and edit a couple of filter values like min/max followers.

Want someone to build this for you? Talk to an automation expert (free 15-minute consultation).

Step by Step

Hashtags are pulled from Google Sheets. The workflow reads your hashtag column so you can keep everything in one place and update it anytime without touching n8n.

Instagram tag URLs are generated automatically. A small code step formats each hashtag into the correct explore/feed URLs so the scraper has a consistent input.

Apify scrapes hashtag posts, then captions get cleaned and checked. HTTP Request nodes call Apify actors, then n8n normalizes caption text, removes hashtags/links, filters “hashtag-only” posts, and runs language validation so you keep the right market.

Usernames are merged, deduped, and enriched with profile details. The workflow compiles unique usernames, scrapes each profile for follower count and other fields, then keeps only accounts inside your min/max follower range (your definition of “qualified”).

You can easily modify the follower range and language checks to match your niche. See the full implementation guide below for customization options.

Step-by-Step Implementation Guide

Step 1: Configure the Manual Trigger

Set up the workflow to run on demand so you can test and iterate before scheduling or deploying.

Add the Manual Execution Start node as the trigger.
Leave all fields in Manual Execution Start at their defaults.
Optionally keep Flowpast Branding as a visual reference note; it does not affect execution.

Step 2: Connect Google Sheets

Load your hashtag list from Google Sheets so the workflow can build tag URLs dynamically.

Add Retrieve Tag Sheet and set Document to the spreadsheet ID in SPREADSHEET_ID.
Set Sheet to the sheet ID in SHEET_ID.
Credential Required: Connect your googleSheetsOAuth2Api credentials.
Connect Manual Execution Start → Retrieve Tag Sheet.

If the sheet contains a column named Hashtag, Collect Tag List will aggregate it automatically.

Step 3: Set Up Tag Processing and Feed Retrieval

Aggregate tags, generate URLs, call the hashtag feed API, and normalize caption data for filtering.

Add Collect Tag List and set Fields to Aggregate to Hashtag.
Connect Retrieve Tag Sheet → Collect Tag List → Generate Tag URLs.
In Generate Tag URLs, keep the provided JavaScript that builds startUrls from $input.first().json.Hashtag.
Configure Hashtag Feed API Call with Method set to POST and URL set to https://api.apify.com/v2/acts/culc72xb7MP3EbaeX/run-sync-get-dataset-items.
Set JSON Body to ={ "maxItems": 300, "startUrls": [ {{ $json.startUrls }} ], "until": "2025-06-20" } and keep Send Headers enabled.
Update the Authorization header to replace Bearer [CONFIGURE_YOUR_TOKEN] with your Apify token.
Connect Generate Tag URLs → Hashtag Feed API Call → Normalize Caption Data.
Keep the JavaScript in Normalize Caption Data to enrich each item with textNoTags, language hit counts, and flags.

⚠️ Common Pitfall: If the Apify token is missing or invalid, Hashtag Feed API Call will return authorization errors and downstream nodes will not receive items.

Step 4: Configure Filtering, Deduplication, and Profile Enrichment

Filter for hashtag-only or English captions, remove duplicates, and enrich usernames with follower data.

In Check Hashtag Only, set the condition to {{ $json.hasHashtags && ($json.textNoTags || '').trim() === '' }}.
Connect Normalize Caption Data → Check Hashtag Only. The true output goes to Eliminate Duplicate Users, and the false output goes to Validate English Text.
In Validate English Text, set the condition to {{ $json.enHits > 0 && $json.frHits === 0 && $json.esHits === 0 }}.
Connect Validate English Text → Eliminate Duplicate Users.
Configure Eliminate Duplicate Users with Compare set to selectedFields and Fields to Compare set to owner.username.
Connect Eliminate Duplicate Users → Merge Username Sets, and set Fields to Aggregate to owner.username.
Configure Profile Details API Call with URL https://api.apify.com/v2/acts/dSCLg0C3YEZ83HzYX/run-sync-get-dataset-items and JSON Body set to ={ "usernames": [ {{ $json.username.map(u => `\"${u}\"`).join(", ") }} ] }.
Replace the Authorization header value Bearer [CONFIGURE_YOUR_TOKEN] with your Apify token.
Connect Merge Username Sets → Profile Details API Call → Validate Follower Range.
In Validate Follower Range, set conditions to {{ $json.followersCount }} gte 10000 and {{ $json.followersCount }} lte 100000.

The follower range filter in Validate Follower Range ensures you only keep mid-sized audiences—adjust the min/max values to match your campaign goals.

Step 5: Test and Activate Your Workflow

Run a manual test to verify tag ingestion, API calls, and filtering before enabling the workflow for production use.

Click Execute Workflow in n8n to trigger Manual Execution Start.
Confirm Retrieve Tag Sheet outputs a list of hashtags and Hashtag Feed API Call returns items.
Verify that Eliminate Duplicate Users reduces repeated owner.username values and Validate Follower Range keeps only accounts within your target range.
When results look correct, save the workflow and keep it ready for manual execution as needed.

⚠️ Common Pitfall: If the sheet column is not named Hashtag, Collect Tag List will output empty values and the API call will fail to find tags.

🔒

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Troubleshooting Tips

Apify credentials can expire or the actor may require access. If things break, check your Apify token and actor permissions in your Apify console first.
If you’re using Wait nodes or external scraping, processing times vary. Bump up the wait duration if downstream nodes fail on empty responses.
Google Sheets nodes often fail because the spreadsheet, tab name, or header column changed. Confirm the Sheet name and hashtag column still match what the “Retrieve Tag Sheet” node expects.

Quick Answers

What’s the setup time for this Instagram lead automation automation?

About 30 minutes once your Apify and Google credentials are ready.

Is coding required for this lead qualification outcome?

No. You’ll mostly pick accounts, paste an API key, and tweak a couple of filters.

Is n8n free to use for this Instagram lead automation workflow?

Yes. n8n has a free self-hosted option and a free trial on n8n Cloud. Cloud plans start at $20/month for higher volume. You’ll also need to factor in Apify usage costs based on how many hashtags and profiles you scrape.

Where can I host n8n to run this automation?

Two options: n8n Cloud (managed, easiest setup) or self-hosting on a VPS. For self-hosting, Hostinger VPS is affordable and handles n8n well. Self-hosting gives you unlimited executions but requires basic server management.

Can I modify this Instagram lead automation workflow for different use cases?

Yes, and you should. The fastest wins are swapping the language logic in the “Validate English Text” checks, adjusting the min/max values in “Validate Follower Range,” and changing what gets written back to your sheet (add email guessers, niche tags, or “do-not-contact” flags). If you want different data entirely, replace the “Profile Details API Call” Apify actor with another actor that returns the fields you care about. Same workflow shape, different output.

Why is my Apify connection failing in this workflow?

Most of the time it’s an invalid or expired Apify API token, so regenerate it and update the credential in n8n. Also check that you have access to the specific Instagram Scraper actor you selected, because some actors require enabling or a paid plan. If the run starts and then fails mid-way, you may be hitting rate limits or pulling too many items at once; reduce hashtag volume per run or add batching with Split in Batches.

What volume can this Instagram lead automation workflow process?

On n8n Cloud Starter, you’re typically fine for small weekly runs; bigger prospecting teams usually move up a plan or self-host to avoid execution limits. If you self-host, there’s no execution cap, but your server and Apify limits will still matter. Practically, this workflow can churn through hashtags quickly, but profile enrichment is the slower part because it’s one profile per username. Start with 10–20 hashtags per run, then increase once you’re confident it’s stable.

Is this Instagram lead automation automation better than using Zapier or Make?

Often, yes, because this kind of lead qualification needs branching logic, deduping, and multi-step enrichment. n8n makes that easier to manage without paying extra for every filter and path. It also plays nicely with HTTP Request calls to tools like Apify, which is the core of this workflow. Zapier or Make can still work if you keep it very simple, but you’ll usually hit limitations once you add “clean caption, detect language, merge sets, dedupe, then enrich.” If you want help choosing, Talk to an automation expert and describe your volume and targeting rules.

Once this is running, hashtag research stops being a weekly chore and becomes a repeatable system. Let the workflow do the sorting so you can focus on the outreach that actually moves revenue.

Apify to Google Sheets, qualified Instagram leads

How This Automation Works

n8n Workflow Template: Apify to Google Sheets, qualified Instagram leads

Why This Matters: Hashtag leads get messy fast