How to Scrape Instagram Followers and Following Lists: Complete Guide

Understanding the difference between who follows you and who you follow reveals growth opportunities, partnership potential, and audience quality signals that native Instagram analytics completely miss.

Followers vs. Following: Why Both Matter
What Each List Reveals
Legal and Safety Framework
Method 1: Manual Collection
Method 2: Browser-Based Tools
Method 3: API and Services
Step-by-Step Scraping Process
Comparing Followers vs. Following Lists
Analysis Techniques
Growth Strategies from Data
Account Safety Best Practices
Common Mistakes to Avoid
Real-World Use Cases
FAQ: Scraping Followers and Following
Implementation Checklist

Followers vs. Following: Why Both Matter {#followers-vs-following}

Many people focus only on their follower list, but the "following" list is equally valuable for different reasons:

Follower list analysis

What it shows: People who chose to follow you

Key insights:

Audience composition and demographics
Follower quality (bots vs. real accounts)
Influencer presence in your audience
Competitive overlap (who else follows you and competitors)
Growth patterns over time

Primary use cases:

Understand your audience
Identify engagement opportunities
Vet follower authenticity
Build lookalike audiences for ads

Following list analysis

What it shows: Accounts someone actively chose to follow

Key insights:

Content interests and preferences
Industry connections and relationships
Competitor research (who do competitors follow?)
Potential partnership targets
Content sources and inspiration

Primary use cases:

Discover relevant accounts in your niche
Map competitive relationships
Find collaboration opportunities
Understand content consumption patterns

The power of comparing both lists

When you analyze both followers and following together, you unlock deeper insights:

Follower/following ratio:

Ratio > 5: Strong influencer or brand (selective following)
Ratio 1-5: Typical engaged user
Ratio 0.2-1: Active networker or new account building audience
Ratio < 0.2: Potential follow-for-follow tactics or spam

Who follows back: Compare your followers list to your following list:

Follow back rate: Percentage of accounts you follow who follow you back
One-way followers: Follow you but you don't follow them (potential superfans)
One-way following: You follow but they don't follow back (reconsider if valuable)

Mutual connections: Find accounts that both you and a competitor follow—these are highly relevant to your niche.

What Each List Reveals {#what-lists-reveal}

Specific insights from each data source:

Follower list insights

Audience size distribution: Export followers and calculate how many are:

Nano (1K-10K followers): Likely consumers or micro-creators
Micro (10K-100K): Established creators, potential partners
Macro (100K-1M): Major influencers, rare but valuable
Mega (1M+): Celebrities or mega-brands

Example finding: If 80% of your followers are nano-tier, your content appeals to everyday users. If 30% are micro-tier, you're attracting fellow creators.

Geographic distribution: Analyze bio location mentions or language:

"Based in NYC," "London," "São Paulo"
Language patterns in bios
Timezone activity patterns (when they post)

Niche alignment: Search bio text for keywords:

Fitness brand: "health," "wellness," "training," "nutrition"
B2B SaaS: "CEO," "founder," "startup," "entrepreneur"
Fashion: "style," "fashion," "designer," "boutique"

Engagement potential: Identify followers most likely to engage:

Active accounts (post count > 50)
Reasonable follower ratios (0.5-5)
Complete profiles (bio, link, profile picture)
Recent activity indicators

Following list insights

Content interests: Accounts someone follows reveal their interests:

Following 50 fitness accounts → Fitness enthusiast
Following 30 marketing blogs → Marketing professional
Following 20 local restaurants → Foodie, location-specific

Industry connections: Who they follow shows their professional network:

Competitors they monitor
Potential partners or clients
Industry thought leaders
Complementary service providers

Content sources: Following list = their curated inspiration feed:

What content formats do they value? (Reels creators vs. photo-first accounts)
What topics matter enough to follow?
What posting frequency do they tolerate? (daily posters vs. weekly)

Strategic relationships: For competitors, following lists reveal:

Who they're learning from
Who they might partner with
Gaps in their network (your opportunity)
Accounts they engage with regularly

Data completeness comparison

Data Point	Follower List	Following List
Username	✅ Always	✅ Always
Bio text	✅ Yes	✅ Yes
Follower count	✅ Yes	✅ Yes
Following count	✅ Yes	✅ Yes
Post count	✅ Yes	✅ Yes
Follow date	Sometimes	Sometimes
Engagement with account	❌ No (needs separate scrape)	❌ No
Profile picture	✅ Yes (URL)	✅ Yes (URL)

Both lists provide similar data fields, but the context differs. A follower list shows "who chose me," while a following list shows "who I chose."

Legal and Safety Framework {#legal-safety}

Before scraping any data, understand the boundaries:

Instagram Terms of Service

Instagram's TOS prohibits:

Automated data collection without written permission
Collecting information for unauthorized purposes
Creating databases of user information
Circumventing technical protections

Gray area: Public data scraping for business intelligence is common practice, but technically violates TOS. Many businesses scrape despite this, accepting the risk of account restrictions.

Safest approaches:

Official Instagram Data Download (your own account only)
Manual collection of public information
Rate-limited browser tools that mimic human behavior
Using secondary accounts for research (protecting main account)

Privacy regulations

GDPR (EU users):

Document lawful basis (legitimate interest for business intelligence)
Implement data retention policies (delete after 30-90 days)
Honor deletion requests promptly
Secure data appropriately

CCPA (California users):

Disclose data collection practices
Provide opt-out mechanisms
Don't sell collected data
Honor deletion requests

Ethical guidelines

Do:

Focus on public Business/Creator accounts that expect visibility
Use data for legitimate business purposes (strategy, research, partnerships)
Secure collected data and limit access
Delete data when no longer needed
Honor user requests for deletion

Don't:

Scrape private accounts you don't have access to
Use data to spam, harass, or harm users
Sell scraped follower lists
Combine data from multiple sources to create invasive profiles
Ignore rate limits and platform protections

The test: If you wouldn't be comfortable explaining your data practices publicly, reconsider your approach.

Method 1: Manual Collection {#manual-collection}

The safest and most compliant approach:

When manual collection makes sense

Best for:

Small projects (20-100 accounts)
High-value accounts requiring contextual review
Learning about your niche
Maximum safety and compliance
Users without technical skills

Not ideal for:

Large-scale analysis (1,000+ accounts)
Time-sensitive projects
Ongoing automated tracking

Manual follower collection process

Step 1: Set up tracking spreadsheet

Create Excel/Google Sheet with columns:

Username
Full_Name
Follower_Count
Following_Count
Post_Count
Bio_Text
External_Link
Account_Type (Personal/Business/Creator)
Notes
Collection_Date

Step 2: Navigate to target account

Visit instagram.com/targetusername

Step 3: Open follower list

Click "X followers" link below bio

Step 4: Manually record data

For each follower (or a sample):

Click on follower username to open profile
Copy relevant fields into spreadsheet
Add qualitative notes (content quality, relevance, engagement signs)
Return to follower list and repeat

Pro tip: Use dual monitors—follower list on one screen, spreadsheet on the other.

Step 5: Sample strategically

For large accounts, sample intelligently:

Top 50 followers (by follower count) = influencers
Random 100 from middle = typical audience
Most recent 50 = growth patterns

Manual following collection process

Same process, but click "X following" instead of followers.

Additional analysis for following lists:

Categorize accounts: Competitors, Partners, Industry Leaders, Content Inspiration, Personal
Note mutual follows (accounts that follow back)
Identify clusters (e.g., "follows 10 productivity apps" = SaaS buyer signal)

Time investment

Per account analysis:

5-10 accounts: 30 minutes
50 accounts: 2-3 hours
100 accounts: 4-6 hours

For large accounts (10K+ followers):

Strategic sampling: 2-3 hours for meaningful insights
Full export: Manual collection impractical—use automated tools

When to graduate to automation

If you find yourself thinking "I wish I could do this for 500 accounts," it's time to explore browser tools or APIs.

Method 2: Browser-Based Tools {#browser-tools}

Automate the collection process while maintaining reasonable safety:

How browser tools work

Browser extensions install in Chrome, Firefox, or Edge and add functionality to Instagram:

Technical approach:

You visit Instagram and log in normally
Extension adds "Export" buttons or overlays
When clicked, extension programmatically scrolls through follower/following lists
Extracts visible data as profiles load
Compiles into CSV or JSON file
Downloads to your computer

Key advantage: Uses your existing authenticated session (no need to share credentials with third parties).

Recommended: Instracker.io

The most balanced option for most users:

For followers: Instagram Follower ExportFor following lists: Following Export

Why it's better:

Session-based (no credential sharing)
Rate-limited by design (safer)
Clean CSV/Excel output
Enriched profile data (bio, counts, verification status)
Pay-per-export (no subscription lock-in)
Works for your account and public competitors

What you can export:

Complete follower lists (your account or any public account)
Complete following lists
Filtered exports (by follower count, verification status, etc.)
Engagement data via Comments Export and Likes Export

Alternative browser extensions

If you prefer standalone extensions:

Selection criteria (green flags):

✅ Uses your browser session (doesn't ask for password)
✅ Mentions rate limiting or delays between actions
✅ Recently updated (within 6 months)
✅ Positive reviews about safety and reliability
✅ Transparent pricing ($20-100/month typical)
✅ Clear documentation and support

Red flags to avoid:

❌ Requests Instagram login credentials
❌ Promises "unlimited instant scraping"
❌ Free with no clear business model
❌ Many reviews mentioning account blocks
❌ No updates in 12+ months
❌ Excessive browser permissions

Best practices for browser tool use

1. Start with test account Create secondary Instagram account, age it 2-4 weeks with normal use, test tool with that account first.

2. Begin conservatively

First export: Account with 500-1,000 followers
Second export: Account with 5,000 followers
Third export: Your target account sizes
Progressively validate safety

3. Respect timing

Export during off-peak hours (2-6 AM your timezone)
Space exports by 3-4 hours minimum
Don't export 10 accounts back-to-back
Weekly or monthly frequency is safer than daily

4. Monitor for warnings Stop immediately if you see:

"Action Blocked" messages
"We restrict certain activity" warnings
Unusual errors or timeouts
Followers/following counts not loading properly

5. Use conservative settings If tool offers speed options:

Start with "Slow" or "Safe" mode
Only increase speed after confirming no issues for 1-2 weeks
Never use "Fast" or "Unlimited" modes

Workflow: Export both lists efficiently

Session 1 (Week 1, Day 1):

Export your own follower list
Wait 4 hours
Export your own following list

Session 2 (Week 1, Day 3):

Export Competitor A follower list
Wait 4 hours
Export Competitor A following list

Session 3 (Week 1, Day 5):

Export Competitor B follower list
Wait 4 hours
Export Competitor B following list

Analysis phase (Week 2): Clean, compare, and analyze all collected data before doing more exports.

Method 3: API and Services {#api-services}

For technical users and high-volume needs:

Instagram official APIs

Basic Display API:

Access your own profile and media
Very limited follower/following data (only accounts that granted explicit permission)
Best for: Displaying your own content on external sites

Graph API (Business accounts):

Insights for accounts you manage
Limited competitor data
Requires Facebook Developer app approval (2-6 weeks)
Best for: Agencies managing client accounts

Limitation: Neither API provides competitor follower/following lists. You need third-party services for that.

Third-party API services

How they work:

Sign up for service and get API key
Send HTTP request with target username
Service scrapes data and returns JSON
You parse JSON and import to Excel/database

Popular services:

Apify Instagram Scrapers:

Actor-based (modular scrapers you can customize)
Pay-per-use pricing (~$0.10-1.00 per 1,000 results)
Good for variable volume needs
Actors: Profile Scraper, Follower Scraper, Following Scraper

RapidAPI Instagram endpoints:

Multiple providers with varying quality
Subscription-based ($10-200/month)
Test different providers to find reliable one
Good for ongoing needs

Bright Data (Enterprise):

High reliability and compliance focus
Expensive ($500-5,000/month)
Requires contracts
Best for: Enterprise scale, mission-critical data

When API makes sense

Choose API services if:

You have programming skills (Python, JavaScript, etc.)
You need ongoing automated collection (weekly/monthly)
You're tracking 50+ accounts regularly
Budget allows ($100-500/month)
You're building a product that requires Instagram data

Stick with browser tools if:

Non-technical user
One-time or occasional needs
Budget under $100/month
Comfortable with more manual process

Basic API usage example (Python)

import requests
import pandas as pd

API_KEY = "your_api_key"
API_ENDPOINT = "https://api.service.com/instagram/followers"

def get_followers(username, max_results=1000):
    """Fetch follower list via API."""
    headers = {"Authorization": f"Bearer {API_KEY}"}
    params = {
        "username": username,
        "maxResults": max_results
    }
    
    response = requests.get(API_ENDPOINT, headers=headers, params=params)
    
    if response.status_code == 200:
        return response.json()['followers']
    else:
        print(f"Error: {response.status_code}")
        return []

# Usage
followers = get_followers("nike", max_results=5000)

# Convert to DataFrame and export
df = pd.DataFrame(followers)
df.to_excel("nike_followers.xlsx", index=False)
print(f"Exported {len(followers)} followers")

Step-by-Step Scraping Process {#step-by-step}

Detailed walkthrough for scraping both lists:

Phase 1: Planning (Day 1)

Define objectives:

What specific questions will this data answer?
Which accounts do you need to analyze?
What metrics matter for your goals?

Set up infrastructure:

Create master Excel tracking file
Set up folder structure for raw exports
Document your process for reproducibility

Choose method:

Manual (20-100 accounts, maximum safety)
Browser tools (100-1,000 accounts, balanced approach)
API (1,000+ accounts, ongoing automation)

Phase 2: Follower list collection (Days 2-3)

Step 1: Export your own followers

Using Instagram Follower Export:

Visit the tool page
Ensure you're logged into Instagram in same browser
Enter your username
Select export options (full export or sample size)
Click "Export Followers"
Wait for completion (10-30 minutes for 10K followers)
Download CSV file

Step 2: Export competitor followers

Repeat process for 2-3 key competitors:

Direct competitors in your niche
Aspirational accounts (where you want to be)
Potential partner accounts

Space exports: Wait 3-4 hours between each export.

Step 3: Organize files

Save with descriptive names:

your_account_followers_2025_11_08.csv
competitor_a_followers_2025_11_08.csv
competitor_b_followers_2025_11_08.csv

Phase 3: Following list collection (Days 4-5)

Step 1: Export your own following list

Using Following Export:

Visit the tool page
Enter your username
Export following list
Download CSV

Step 2: Export competitor following lists

Same competitors as Phase 2. Their following list shows:

Who they're learning from
Potential partnership targets
Content sources
Industry connections

Step 3: Save organized files

your_account_following_2025_11_08.csv
competitor_a_following_2025_11_08.csv
competitor_b_following_2025_11_08.csv

Phase 4: Data cleaning (Days 6-7)

Step 1: Import to Excel

For each CSV file:

Open Excel > Data > From Text/CSV
Select CSV file
Confirm delimiter (Comma) and encoding (UTF-8)
Load data

Step 2: Remove duplicates

Select all data (Ctrl+A)
Data > Remove Duplicates
Check "Username" column
Click OK

Step 3: Filter out bots

Create "Likely_Bot" column:

=IF(AND(Follower_Count<100, Following_Count>2000, Post_Count=0), "YES", "NO")

Filter to show only "NO" rows.

Step 4: Add calculated fields

Follower ratio:

=Follower_Count / (Following_Count + 1)

Influence tier:

=IF(Follower_Count<1000,"Nano",IF(Follower_Count<10000,"Micro",IF(Follower_Count<100000,"Mid",IF(Follower_Count<1000000,"Macro","Mega"))))

Profile completeness:

=IF(Username<>"",20,0)+IF(Bio<>"",40,0)+IF(Link<>"",20,0)+IF(Follower_Count>0,20,0)

Phase 5: Comparative analysis (Days 8-9)

Now the real insights come from comparing lists—see next section.

Comparing Followers vs. Following Lists {#comparing-lists}

The magic happens when you analyze both lists together:

Analysis 1: Your follower/following ratio

Calculate:

Total followers: (from follower list export)
Total following: (from following list export)
Ratio: Followers / Following

Interpretation:

Ratio > 5: Strong influencer or brand positioning (selective following)
Ratio 2-5: Healthy engaged account
Ratio 1-2: Active networker
Ratio 0.5-1: Building audience phase
Ratio < 0.5: Follow-for-follow tactics (not recommended long-term)

Action: If ratio < 1, consider unfollowing inactive accounts or those who don't follow back (use sparingly—mass unfollows can trigger restrictions).

Analysis 2: Who follows back

Goal: Identify mutual connections vs. one-way relationships

Process:

Open your Followers spreadsheet
Add column "Follows_Back"
Use VLOOKUP to check if each follower is in your Following list:

=IF(ISNUMBER(MATCH(A2,FollowingSheet!A:A,0)),"YES","NO")

Insights:

YES (Mutual): These are your core community—engage with them regularly
NO (They follow you, you don't follow them): Potential superfans—analyze their engagement potential

Calculate follow-back rate:

=COUNTIF(Follows_Back_Column,"YES") / COUNTA(Follower_List) * 100

Benchmarks:

40-60%: Healthy mutual engagement
60-80%: Very engaged community
20-40%: One-way influence (typical for established brands)
<20%: Review if you're following relevant accounts

Analysis 3: Accounts you follow who don't follow back

Goal: Identify accounts worth engaging with vs. accounts to unfollow

Process:

Open your Following spreadsheet
Add column "Follows_Me_Back"
Use VLOOKUP to check if each following is in your Followers list:

=IF(ISNUMBER(MATCH(A2,FollowersSheet!A:A,0)),"YES","NO")

Review "NO" accounts:

Keep if:

Industry leaders or major brands (educational value)
Active engagement potential (they reply to comments, engage with community)
Content inspiration sources
Potential partners you're building relationships with

Consider unfollowing if:

Inactive accounts (no posts in 6+ months)
No strategic value
You followed during follow-for-follow phase
They're not relevant to your current niche

Caution: Don't mass unfollow hundreds in one day—Instagram may flag this. Unfollow 20-50 per day maximum.

Analysis 4: Competitor follower overlap

Goal: See how much your audience overlaps with competitors

Process:

Open your Followers spreadsheet
Add column "Also_Follows_CompetitorA"
Use MATCH formula:

=IF(ISNUMBER(MATCH(A2,CompetitorA_Followers!A:A,0)),"YES","NO")

Repeat for each competitor.

Calculate overlap percentage:

=COUNTIF(Also_Follows_CompetitorA,"YES") / COUNTA(Your_Followers) * 100

Interpretation:

<10% overlap: Reaching different audiences—potential collaboration opportunity
10-30% overlap: Some shared audience—healthy competition
30-50% overlap: High similarity—direct competition or perfect partnership
>50% overlap: Very similar audiences—differentiation needed

Action: Accounts in competitor followers but NOT in your followers = growth opportunity targets.

Analysis 5: Who do competitors follow?

Goal: Discover partnership opportunities and industry connections

Process: Compare multiple competitors' following lists:

Find accounts that 2+ competitors follow:

=IF(AND(
  ISNUMBER(MATCH(A2,CompA_Following!A:A,0)),
  ISNUMBER(MATCH(A2,CompB_Following!A:A,0))
), "MULTIPLE", "ONE")

Filter for "MULTIPLE"

These accounts are:

Industry thought leaders
Potential partners (competitors are watching them)
Content inspiration sources
Service providers competitors use

Action: Follow these accounts, engage authentically, explore partnership opportunities.

Analysis 6: Content interest mapping

Goal: Understand what content your audience consumes

Process:

Export followers' bios into text analysis tool or Excel
Aggregate bio keywords across all followers
Identify top 20-30 most common terms

For more sophisticated analysis: Export followers' following lists (requires deeper scraping) and analyze:

What types of accounts do your followers follow?
What content formats (photo-first vs. Reel-focused accounts)?
What topics dominate their feeds?

Insight example: If 60% of your followers also follow productivity app accounts, create content about productivity and workflows.

Analysis Techniques {#analysis-techniques}

Advanced ways to extract insights from scraped lists:

Technique 1: Engagement potential scoring

Goal: Rank followers by likelihood to engage with your content

Scoring model:

=
(IF(Follower_Count<10000,30,IF(Follower_Count<50000,20,10))) +
(IF(Follower_Ratio>2,25,IF(Follower_Ratio>0.5,15,5))) +
(IF(Post_Count>50,25,IF(Post_Count>10,15,5))) +
(IF(Profile_Completeness>60,20,10))

Components:

Account size (30 pts): Smaller accounts more likely to engage
Follower ratio (25 pts): Higher ratio = more selective, valuable engagement
Post activity (25 pts): Active posters are active engagers
Profile completeness (20 pts): Complete profiles indicate real, engaged users

Total score: 0-100

Action: Sort by score descending. Top 100 = priority accounts for:

Following (if you haven't already)
Commenting on their posts
Sharing their content
DM outreach for partnerships

Technique 2: Follower quality audit

Goal: Assess what percentage of followers are real, engaged users vs. bots/inactive

Metrics:

Bot percentage:

=COUNTIF(Likely_Bot_Column,"YES") / COUNTA(Username_Column) * 100

Benchmarks:

<5%: Excellent quality
5-15%: Normal/acceptable
15-30%: Questionable (review growth tactics)
30%: Poor quality (likely purchased followers)

Active account percentage:

=COUNTIFS(Post_Count_Column,">10", Follower_Ratio_Column,">0.2") / COUNTA(Username_Column) * 100

Benchmarks:

70%: Excellent engaged audience
50-70%: Good quality
30-50%: Mixed quality
<30%: Poor quality audience

Action: If quality is low, adjust hashtag strategy, stop follow-for-follow tactics, focus on content that attracts genuine followers.

Technique 3: Growth source identification

Goal: Understand where new followers come from

Process (requires monthly exports):

Month 1: Export followers → Save as Followers_Nov.xlsx

Month 2: Export followers → Save as Followers_Dec.xlsx

Compare:

=IF(ISNA(VLOOKUP(A2,Nov_Sheet!A:A,1,FALSE)),"NEW_DEC","EXISTING")

Analyze new followers:

What's their follower size distribution?
What keywords appear in their bios?
What's the quality score?
Do they follow competitors too?

Correlate with content:

Which posts went viral in December?
What hashtags drove discovery?
Did any influencers share your content?
What collaborations happened?

Insight example: "In December, we gained 500 new followers after Reel about productivity went viral. 60% of new followers mention 'remote work' in bio → Create more remote work content."

Technique 4: Influencer partnership prioritization

Goal: Rank potential influencer partners from your follower list

Criteria:

Relevance score (30 points): Bio keyword match with your niche:

=IF(ISNUMBER(SEARCH("fitness",Bio)),30,IF(ISNUMBER(SEARCH("health",Bio)),20,0))

Reach score (25 points): Follower count in target range:

=IF(AND(Follower_Count>=10000,Follower_Count<=100000),25,IF(AND(Follower_Count>=5000,Follower_Count<10000),15,5))

Engagement score (25 points): High ratio and activity:

=IF(AND(Follower_Ratio>3,Post_Count>50),25,IF(Follower_Ratio>1,15,5))

Accessibility score (20 points): Has contact information:

=IF(OR(ISNUMBER(SEARCH("@",Bio)),ISNUMBER(SEARCH(".com",Link))),20,0)

Total partnership score: Sum all components (0-100)

Action: Sort by score, manually review top 20-30, reach out with partnership proposals.

Technique 5: Unfollow decision matrix

Goal: Systematically decide which accounts to unfollow

Decision tree:

Keep if ANY of these are true:

Follows you back (mutual connection)
Follower count > 100K (industry leader)
Posted in last 30 days (active)
You've engaged with their content recently
Strategic partnership potential

Consider unfollowing if ALL of these are true:

Doesn't follow you back
Follower count < 1K (unless personal connection)
No posts in 6+ months (inactive)
No engagement with your content
No strategic value

Implementation: Add "Unfollow_Decision" column:

=IF(AND(Follows_Me_Back="NO", Follower_Count<1000, Last_Post_Days>180), "UNFOLLOW", "KEEP")

Action: Filter for "UNFOLLOW", manually review, then unfollow 20-50 per day maximum.

Growth Strategies from Data {#growth-strategies}

Turn analysis into action:

Strategy 1: Targeted follow and engage

Process:

Export competitor followers
Filter for accounts NOT following you
Score by engagement potential
Select top 200

Engagement campaign:

Follow these 200 accounts
Comment meaningfully on 2-3 recent posts each
Share their content to your story (when relevant)
Track follow-back rate over 30 days

Expected results:

25-35% follow-back rate from quality accounts
5-10% ongoing engagement (likes, comments on your content)
1-3% partnership conversations

Strategy 2: Content theme optimization

Process:

Export your followers
Analyze bio keyword frequency
Identify top 5-10 interest clusters

Content action:

Create content series for each top interest cluster
Test engagement for 4 weeks
Double down on highest-performing themes
Phase out underperforming themes

Example:

Fitness account followers mention: yoga (40%), strength (30%), running (25%), CrossFit (15%)
Create content: 40% yoga, 30% strength, 25% running, 5% CrossFit
Measure: engagement rate by content theme
Adjust: If yoga content gets 2x engagement, shift to 50% yoga

Strategy 3: Partnership pipeline

Process:

Export your followers
Filter for micro-influencers (10K-50K followers, ratio > 3)
Check for contact information in bio/link
Manually review content alignment
Create partnership outreach list

Outreach sequence:

Follow and engage for 2 weeks (no ask)
Send genuine DM complimenting specific content
After positive response, propose collaboration
Offer value-first (product, promotion, revenue share)

Expected results: 20-30% response rate, 10-15% conversion to partnership.

Strategy 4: Follower quality improvement

Process:

Calculate current bot percentage and quality metrics
Identify which growth tactics correlate with low-quality followers

Common culprits:

Certain hashtags attract bots (massive, generic tags like #love, #followme)
Follow-for-follow strategies
Engagement pods or groups
Purchased followers (obvious but still happens)

Action plan:

Stop using bot-prone hashtags
Stop follow-for-follow tactics
Focus on niche-specific hashtags (#yogaforbeginners vs. #fitness)
Create highly targeted content that appeals to ideal followers
Engage authentically in niche communities

Track: Re-export monthly, calculate quality metrics, confirm improvement.

Strategy 5: Competitive positioning

Process:

Export followers from top 3 competitors
Calculate overlap with your followers
Identify competitor-exclusive followers (don't follow you)

High-overlap scenario (40%+):

You're reaching similar audiences
Differentiation needed
Partnership might be redundant (both reaching same people)

Action: Find sub-niche to own within broader space.

Low-overlap scenario (<20%):

Different audiences despite same niche
Partnership has high expansion potential
Their followers = your growth opportunity

Action: Export competitor-exclusive followers, engage with top prospects, partner with competitor for cross-promotion.

Account Safety Best Practices {#safety-practices}

Scraping carries risk—minimize it:

Rate limiting guidelines

Conservative (99% safe):

2-3 accounts per day
100-200 requests per hour
3-5 second delays between actions
Export during off-peak hours (2-6 AM)

Moderate (95% safe):

5-10 accounts per day
300-500 requests per hour
2-3 second delays
Weekly rather than daily exports

Aggressive (70-85% safe):

10+ accounts per day
500+ requests per hour
1-2 second delays
Daily exports

Recommendation: Start conservative, increase gradually only after confirming no issues for 2-4 weeks.

Warning signs you're flagged

Immediate red flags:

"Action Blocked" messages when liking, following, or scraping
"We restrict certain activity to protect our community"
Following/follower counts not loading
Unusual errors when exporting

If flagged:

Stop immediately (all scraping and automation)
Wait 24-48 hours minimum
Use Instagram normally on mobile app (browse, like, comment manually)
When resuming: Use 50% of previous volume with longer delays

Secondary account strategy

Setup:

Create new Instagram account (different email, not linked to main)
Add profile picture, bio, 5-10 posts
Follow 30-50 accounts in your niche
Use normally for 2-4 weeks (daily browsing, occasional likes/comments)
Only then use for research scraping

Benefits:

Protects main business account from blocks
Can test aggressive strategies safely
Replaceable if banned
Separate device/IP fingerprint

Limitations:

Can only view public accounts
Lower trust score as newer account
Requires maintenance (periodic authentic use)

Recovery protocol

If account gets action blocked:

Day 1:

Stop all automation
Use Instagram mobile app only
Browse normally (stories, feed)
Like 10-20 posts manually
Comment on 3-5 posts authentically

Days 2-3:

Continue normal mobile use
No scraping or automation attempts
Don't test limits

Day 4:

Very limited test (view 2-3 profiles manually)
If blocked again, wait another 5-7 days

Day 7+:

Gradually resume scraping at 50% volume
Longer delays between actions
Monitor closely for any warnings

If persistent blocks:

Account may be permanently flagged
Use different account for research
Stick to manual methods for main account

Common Mistakes to Avoid {#common-mistakes}

Learn from these frequent errors:

Mistake 1: Scraping without a plan

Problem: Exporting follower lists from 20 accounts "because it might be useful" without clear goals.

Why it's bad: Wasted time and risk with no actionable insights.

Solution: Before scraping, write down:

Specific question you're answering
Decision this data will inform
Who will use insights and how
Success metric for the project

Mistake 2: Ignoring follower quality

Problem: Celebrating 10K follower milestone without checking that 4K are bots.

Why it's bad: Inflated metrics hide poor growth tactics, low engagement rates, wasted partnership opportunities.

Solution:

Export and analyze follower quality quarterly
Calculate bot percentage and quality score
Adjust strategies to attract genuine followers
Remove obvious bots (Settings > Privacy > Remove Followers)

Mistake 3: Comparing only follower counts

Problem: Choosing influencer partnerships based solely on follower numbers.

Why it's bad: 100K fake followers < 10K engaged real followers. Engagement rate and audience quality matter more.

Solution:

Export potential partners' follower lists
Calculate bot percentage and engagement potential
Check audience overlap and niche relevance
Value quality over quantity

Mistake 4: Mass follow/unfollow tactics

Problem: Following 500 accounts per day from competitor follower lists, unfollowing non-followers after 48 hours.

Why it's bad: Violates Instagram's rate limits, damages account reputation, attracts low-quality followers, risks permanent ban.

Solution:

Follow 20-50 relevant accounts per day maximum
Unfollow 20-30 per day maximum
Wait weeks before unfollowing (not 48 hours)
Focus on accounts you genuinely want to engage with

Mistake 5: Neglecting the "following" list

Problem: Only analyzing follower list, ignoring what accounts you or competitors follow.

Why it's bad: Missing insights about content sources, partnership opportunities, and strategic relationships.

Solution:

Always export both followers AND following
Analyze who competitors follow (reveals their strategy)
Audit your own following list quarterly (are you following accounts that add value?)

Mistake 6: One-time analysis only

Problem: Exporting once, doing analysis, never revisiting.

Why it's bad: Audience composition changes, growth patterns emerge over time, single snapshot misses trends.

Solution:

Export monthly (set calendar reminder)
Compare month-over-month changes
Track follower quality trends
Use Instagram Followers Tracker for automated monitoring

Mistake 7: Not securing data

Problem: Storing follower exports in unsecured Google Drive folders, emailing CSV files without encryption.

Why it's bad: Privacy violations, GDPR/CCPA compliance issues, reputational damage if breached.

Solution:

Password-protect Excel files
Encrypt sensitive data
Limit access to need-to-know basis
Delete files after retention period (30-90 days)

Real-World Use Cases {#use-cases}

How businesses actually use both lists:

Case study 1: SaaS company competitive intelligence

Company: Project management tool for agencies

Goal: Understand competitive positioning and find partnership opportunities

Process:

Exported followers from 5 competing tools (20K-80K followers each)
Exported following lists from same 5 competitors
Calculated follower overlap between own account and competitors
Analyzed who competitors follow (potential partners, industry leaders)

Key findings:

25% follower overlap with Competitor A (direct competition)
Only 8% overlap with Competitor B (different sub-niche despite similar product)
All 5 competitors followed same 12 industry blogs (influencer targets)
Competitors' followers mentioned "freelance" (45%) and "agency" (35%) in bios

Actions taken:

Partnered with Competitor B for cross-promotion (low overlap = audience expansion)
Reached out to the 12 shared influencers competitors followed
Adjusted content strategy to address "freelance" and "agency" pain points specifically
Targeted competitor A's followers for paid ads (high relevance, some brand awareness)

Results: 35% follower growth in Q4, 12 new influencer partnerships, 18% increase in trial signups.

Case study 2: Fashion influencer partnership vetting

Company: Sustainable clothing brand

Goal: Vet 30 influencer candidates before committing $80K campaign budget

Process:

Exported follower lists from all 30 influencer candidates
Analyzed follower quality (bot percentage, engagement potential)
Exported candidates' following lists to understand their interests and partnerships
Calculated audience overlap between influencers (avoid paying for same audience repeatedly)

Key findings:

Tier	Influencers	Avg Followers	Bot %	Quality Score	Recommend
A	8	72K	7%	82/100	Yes
B	12	58K	15%	68/100	Maybe
C	7	91K	34%	45/100	No
D	3	125K	48%	32/100	Definitely No

Additional insights from following lists:

Tier A influencers followed authentic sustainable brands and environmental accounts
Tier C/D influencers followed "growth hacking" and "Instagram fame" accounts (red flag)
6 influencers had 50%+ follower overlap (would reach mostly same people)

Actions taken:

Selected 8 Tier-A influencers for campaign
Allocated budget: 50% to top 3, 50% distributed across remaining 5
Negotiated lower rates for 2 influencers based on bot data
Saved ~$28K by avoiding Tier C/D influencers

Results: Campaign reached 480K real, engaged users (vs. 900K total if all influencers used). Generated 12.5K website visits, 1,850 purchases ($315K revenue), 625% ROI (vs. projected 180% if original mix used).

Case study 3: Content creator niche pivot

Individual: Tech YouTuber pivoting from coding tutorials to productivity

Goal: Understand current audience vs. target audience for pivot

Process:

Exported own follower list (45K followers)
Analyzed bio keywords and follower types
Exported followers from 10 top productivity creators
Calculated overlap and identified "bridge audience"

Key findings:

Current followers: 70% mentioned "developer," "coding," "programming"
Target audience: 60% mentioned "productivity," "entrepreneur," "remote work"
Overlap: 18% of current followers also followed productivity accounts ("bridge")
Bridge audience had 2.5x higher engagement than non-bridge

Pivot strategy:

Created content series: "Productivity for Developers" (appeals to both)
Featured automation and coding productivity tools (leverages existing expertise)
Engaged heavily with the 18% bridge audience (commented, shared their content)
Gradually increased productivity content from 10% to 50% over 6 months

Results: Retained 85% of existing audience (vs. feared 50% loss), grew from 45K to 78K followers in 6 months, engagement rate increased from 3.2% to 5.1%, successfully pivoted niche.

FAQ: Scraping Followers and Following {#faq-scraping}

Q: What's the difference between scraping followers vs. following?

A: Followers list shows people who follow an account (their audience). Following list shows accounts someone actively chose to follow (their interests and connections). Both provide different insights—followers reveal audience composition, following reveals content consumption and relationships.

Q: Can I scrape followers from private accounts?

A: Only if you're an approved follower of that private account, and even then, most tools won't work on private accounts. Focus on public accounts for scraping. Never attempt to bypass privacy settings.

Q: How often can I scrape without getting blocked?

A: Conservative guideline: 2-3 accounts per day, with several hours between exports. Monthly scraping of the same accounts is safer than daily. Use off-peak hours (2-6 AM) and conservative speed settings.

Q: Will people know if I scrape their follower list?

A: No. Scraping is a read-only action that doesn't generate notifications or leave traces visible to the account owner.

Q: What's a good follower-to-following ratio?

A: Depends on account type:

Brands/influencers: 5:1 or higher (selective following)
Personal accounts: 1:1 to 3:1 (balanced)
New accounts building audience: 0.5:1 to 1:1 (active networking)
Avoid: Below 0.3:1 (appears desperate or spammy)

Q: Should I unfollow accounts that don't follow me back?

A: Depends on strategic value. Keep following:

Industry leaders and major brands (educational value)
Potential partnership targets (relationship building)
Content inspiration sources

Consider unfollowing:

Inactive accounts (no posts in 6+ months)
No strategic value
Follow-for-follow accounts from early growth phase

Unfollow gradually: 20-50 per day maximum to avoid restrictions.

Q: How do I export both lists at once?

A: Most tools require separate exports. Export followers first, wait 3-4 hours, then export following list. Using Instagram Follower Export and Following Export separately ensures clean, organized data.

Q: Can I automate monthly follower exports?

A: Some API services support scheduled exports, but requires technical setup. For most users, setting a monthly calendar reminder to manually export via Instagram Followers Tracker is simpler and safer.

Implementation Checklist {#implementation}

Your step-by-step action plan:

Week 1: Setup and learning

☐ Day 1: Define objectives

Write down 3 specific questions you want to answer
Identify 5-10 accounts to analyze (your own + competitors)
Choose scraping method (manual, browser tool, API)

☐ Day 2: Set up infrastructure

Create master Excel tracking file
Set up folder structure for exports
If using browser tools, test with small account first

☐ Day 3: First exports

Export your own follower list
Export your own following list
Import both to Excel and familiarize with data

☐ Day 4: Data cleaning practice

Remove duplicates
Add calculated fields (ratio, tier, completeness)
Filter out obvious bots

☐ Day 5: Basic analysis

Calculate your follower/following ratio
Identify top 20 followers by engagement potential
Analyze bio keywords from your followers

Week 2: Competitive analysis

☐ Day 8: Export competitor followers

Export follower lists from 2-3 competitors
Space exports by 3-4 hours

☐ Day 9: Export competitor following

Export following lists from same competitors
Organize files clearly

☐ Day 10-11: Clean and standardize

Apply same cleaning process to all files
Ensure consistent formatting across datasets

☐ Day 12: Comparative analysis

Calculate audience overlap with competitors
Identify accounts in competitor followers but not yours
Analyze who competitors follow (partnership opportunities)

☐ Day 13-14: Strategic insights

Document top 5-10 findings
Create prioritized action list
Present insights to team/stakeholders

Week 3: Action and implementation

☐ Day 15-17: Engagement campaign

Select top 100-200 accounts to engage with
Follow and comment meaningfully
Share relevant content

☐ Day 18-19: Content strategy adjustments

Based on bio keyword analysis, adjust content themes
Create content calendar reflecting audience interests
Test new formats or topics

☐ Day 20-21: Partnership outreach

Compile list of 20-30 potential influencer/brand partners
Research contact information
Draft personalized outreach messages

Week 4: Optimization and tracking

☐ Day 22-24: Follower quality improvement

If quality is low, adjust hashtag strategy
Stop any follow-for-follow tactics
Focus on niche-specific content that attracts ideal followers

☐ Day 25-26: Following list audit

Review accounts you follow—are they adding value?
Identify 50-100 accounts to unfollow (inactive, no strategic value)
Unfollow gradually (20-30 per day)

☐ Day 27-28: Set up ongoing tracking

Schedule monthly export reminder
Use Instagram Followers Tracker
Create dashboard to track key metrics month-over-month

Monthly ongoing:

☐ First week of month:

Re-export your follower and following lists
Compare to previous month (new, lost, changes)

☐ Second week:

Update analysis (quality scores, engagement potential, overlap)
Identify trends and shifts

☐ Third week:

Adjust strategies based on data
Test new tactics

☐ Fourth week:

Document learnings
Prepare for next month's export

Call to Action

Ready to understand your audience beyond surface metrics? Start by exporting your own follower and following lists:

Essential tools:

Instagram Follower Export — Export any public account's followers
Following Export — Export following lists
Instagram Followers Tracker — Monitor changes over time
Comments Export — Identify most engaged users
Likes Export — Find accounts interested in your content

Start simple:

Export your own follower list
Calculate basic metrics (quality score, engagement potential)
Identify top 20 followers to engage with
Take action this week

Related guides:

Instagram Scraping Complete Guide — Comprehensive scraping overview
Scrape Instagram Followers Guide — Advanced techniques
Export Instagram Followers to Excel — Excel workflow details

Visit Instracker.io for compliant, user-friendly Instagram data export and analysis tools.

Compliance reminder: Only scrape public accounts. Respect Instagram's rate limits. Secure collected data with encryption. Implement retention policies (delete after 30-90 days). Honor user privacy requests. Review Instagram TOS and privacy regulations (GDPR, CCPA) regularly.