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analyzing-competitor-instagram-content-strategy

analyzing-competitor-instagram-content-strategy

github.com/apidojo-ioMarketing & growth1824 installsUpdated 24w ago
Repository

About analyzing-competitor-instagram-content-strategy

A marketing skill for examining a competitor's Instagram content strategy from recent posts. It groups formats and themes, measures engagement, and summarizes posting patterns for marketers.

Key features

  1. 01Scrape competitor posts
  2. 02Classify content types and formats
  3. 03Compare engagement by content type
  4. 04Measure posting cadence and timing
  5. 05Generate a strategy report

Use cases

  1. 01Review a competitor's content mix
  2. 02Find high-engagement post formats
  3. 03Compare posting frequency and timing

MCP support

Can run the Instagram scraper through the Apify MCP server; REST API and a helper script are also documented.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/apidojo-io/apidojo-skills --skill analyzing-competitor-instagram-content-strategy

After installing, type/analyzing-competitor-instagram-content-strategyin Claude Code to confirm it loaded.

Details

From the project README

Analyzing Competitor Instagram Content Strategy

Reverse-engineers a competitor's Instagram content strategy by analyzing their last 50+ posts. Identifies what content formats, themes, and posting patterns drive their highest engagement.

Prerequisites

  • APIFY_TOKEN environment variable set
  • Optional: Apify MCP server installed

Inputs

ParameterTypeRequiredDefaultNotes
startUrlsarray✅[]Instagram URLs — profiles, hashtags, locations, audio pages, reels
untilstringOptional—Scrape posts until this date (YYYY-MM-DD)
maxItemsnumberOptionalUnlimitedMaximum posts to return
customMapFunctionstringOptional—JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Scrape competitor's recent posts
- [ ] Step 2: Classify content types
- [ ] Step 3: Calculate engagement metrics per content type
- [ ] Step 4: Analyze posting patterns
- [ ] Step 5: (Optional) Compare to your account
- [ ] Step 6: Deliver strategy report
Step 1: Scrape Competitor Profile

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~instagram-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~instagram-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~instagram-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~instagram-scraper"
Input:
{
  "usernames": ["[COMPETITOR_HANDLE]"],
  "maxItems": 50
}

REST API fallback:

curl -X POST   "https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"usernames": ["competitor_handle"], "maxItems": 50}'
Step 2: Content Classification

For each post, classify:

content_type:
  PRODUCT = post primarily shows product
  LIFESTYLE = product in context / aspirational
  EDUCATIONAL = tips, how-to, facts (carousel with text)
  SOCIAL_PROOF = testimonial, user tag, press feature
  ENTERTAINMENT = meme, trending audio, humor
  PROMOTIONAL = sale, discount, CTA-heavy
  BEHIND_SCENES = team, office, process

Format: IMAGE | VIDEO | CAROUSEL

Step 3: Calculate Metrics
engagement_rate = (likes + comments) / follower_count * 100

per_type_avg_engagement = avg(engagement_rate for all posts of that type)

content_type_share = count(posts of type) / total_posts * 100

Top performing post: highest (likes + comments * 3) — comments weighted higher as active signal.

Posting cadence:

posts_per_week = total_posts / (date_range_days / 7)
best_day = day_of_week with highest avg engagement
best_hour = hour_of_day with highest avg engagement (use post `timestamp`)
Step 4: Edge Cases
  • Competitor has very few posts (< 20): Report available data; note low sample size; extend to 180-day window
  • Engagement rate << 1%: Account may have bot followers or inactive audience; note this as "audience quality concern"
  • All posts are product/promo: This competitor is over-indexed on promotional content — opportunity for content that educates or entertains
  • Carousel shows as single image: Some scrapers return first image only; note when type = CAROUSEL for accurate content type count

Output Format

# Competitor Instagram Strategy: @[COMPETITOR_HANDLE]
Posts analyzed: [N] | Followers: [N] | Overall Eng Rate: [X%] | Date: [DATE]

## Content Mix
| Type | % of Posts | Avg Eng Rate | Best Post Example |
|------|-----------|-------------|------------------|
| Product | [X%] | [X%] | [post excerpt] |
| Lifestyle | [X%] | [X%] | |
| Educational | [X%] | [X%] | |

## Format Distribution
Images: [X%] | Carousels: [X%] | Videos/Reels: [X%]
Best format by engagement: [FORMAT] ([X%] eng rate)

## Top 5 Posts (by Engagement)
| # | Type | Format | Likes | Comments | Eng Rate | Caption Preview |
|---|------|--------|-------|----------|----------|----------------|

## Posting Cadence
Frequency: [X] posts/week | Best day: [Day] | Best hour: [HH:00]

## Key Observations
1. [Pattern observation — e.g. "Carousel educational posts get 2× engagement of product posts"]
2. [Observation]
3. [Opportunity gap]

Troubleshooting

Scraper returns only recent 12 posts: Instagram limits API access to recent posts. For 50-post analysis, run scraper and note actual count returned. Engagement rate seems wrong: Verify follower_count is current — scraper may return the follower count at time of scrape, which could differ from post-date count for historical posts. Competitor has very high engagement: Distinguish between genuine engagement and pods/bought engagement — genuine engagement shows variety in commenters; pod engagement shows the same accounts commenting repeatedly.

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