Guillermo Marin
Empresario. Creador de #PepsiFútbol #TalentosFederales
211,199
Followers
519
Following
18,571
Tweets
119.2
Avg Engagement
47
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Marin1966Marin's Twitter/X presence across multiple dimensions. We analyze tweet content, engagement patterns, audience demographics, posting habits, and network connections to provide actionable insights about this account's social media strategy and influence.
Account Classification
- Account Size: Macro Influencer (100K+)
- Account Age:2015-03-24
- Verification:No
- Location:Buenos Aires, Argentina
Data Summary
- Tweets Analyzed:3,163
- Avg Likes per Tweet:11.6
- Avg Retweets per Tweet:107.6
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,163 tweetsThe account has a moderate to high engagement rate, with an average of 582 likes and 276 retweets per tweet. Their content is well-received and often shared by followers.
11.6
Avg Likes/Tweet
107.6
Avg Retweets/Tweet
36,598
Total Likes
340,462
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
1
Median Retweets
24
75th Percentile
71,520
Top Tweet
0.56
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Conversationalist
Highly engaged in discussions
14.9%
Original
58.9%
Replies
25.3%
Retweets
1.0%
Quotes
0.0%
Threads
0.0%
With Media
20.1%
With Links
20.8%
With #Tags
87.0%
With @Mentions
11.3%
With Emojis
71
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
3.96
Reply/Original Ratio
0.04
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
77.2%
Weekday Posts
22.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,163 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This account prioritizes community engagement over content broadcasting. With replies making up the majority of their activity, they invest significant time in conversations, building relationships with followers and participating in discussions. This approach typically leads to higher loyalty and more authentic connections.
The 800 retweets (25% of activity) show they also amplify content from others, which helps build relationships with other accounts and provides value to followers by surfacing relevant content.
Posting Patterns & Optimal Timing
Based on 3,163 tweetsEngagement by Hour (UTC)
Posting Frequency Over Time
Timing Insights
Understanding when an account posts and when their audience is most responsive provides valuable competitive intelligence. The charts above show when this account's content receives the most engagement, which often correlates with when their specific audience is most active on the platform.
Peak posting times vary significantly based on an account's audience demographics, timezone distribution, and content type. Accounts with global audiences often see engagement spread across multiple time windows, while those with regional focus may have more concentrated peaks.
Audience Demographics
Based on 50,000 followersThe audience likely includes fans of football, entertainment enthusiasts, and followers of public figures. They are interested in events, collaborations, and socially impactful stories.
Below Average
Audience Quality
39.4%
Suspicion Index
48.0%
Low-Quality %
9
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
61.4%
Empty Bio
51.1%
<10 Tweets
14.9%
Mass Following (>2K)
0.0%
New (<90 days)
81.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
91.2%
No URL
34.7%
<3 Tweets
Free Mode Analysis: These quality metrics use heuristic signals (empty bios, low tweets, suspicious ratios). For ML-powered bot detection with 95%+ accuracy, use our dedicated tool.
Try Bot DetectorFollower Reach & Influence
This account's followers have their own audiences, creating potential for secondary amplification.
286,329,160
Total Potential Reach
9
Median Follower Reach
35
75th Percentile Reach
3.1%
>1K followers
1.0%
>10K followers
0.6%
>50K followers
0.5%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
26.1%
Creators
13,064 accounts
22.8%
Consumers
11,398 accounts
51.1%
Dormant
25,538 accounts
Follower Influence Distribution
How many followers do their followers have?
Follower Account Age
How long have followers been on Twitter?
Geographic Distribution
Top locations where followers are based (from those who share location data):
126
Verified Followers
0.12% of total
9,130
Protected Accounts
9.04% of total
10 years
Avg Account Age
of their followers
Notable Followers (By Influence)
Top accounts following this user, sorted by their follower count:
| Username | Followers | Profession | Interests |
|---|---|---|---|
| @JohnCena | 14,100,397 | Wrestler | Wrestling, Motivation, Self-promotion |
| @LuisitoComunica | 8,938,279 | Influencer | Travel, Vlogs, Adventure |
| @AustinMahone | 8,846,803 | Singer | music, fashion, travel |
| @werevertumorro | 8,716,022 | Influencer | Gaming, Comedy, Email Marketing |
| @GraysonDolan | 8,061,734 | Influencer | comedy, fitness, travel |
| @JuanpaZurita | 8,008,321 | Influencer | Gratitud, humor, locuras |
| @TheGrefg | 7,788,635 | Content Creator | Gaming, Content Creation, Esports |
| @GordonRamsay | 7,696,436 | Chef | Cooking, Food, Restaurants |
| @LoganPaul | 6,809,950 | Influencer | Vlogging, Comedy, Fitness |
| @elcosodelapizza | 6,651,555 | Pizza Box Stand | pizza, queso, caja |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
31,680
Followers With Bio
69,315
Followers Without Bio
31.37%
% With Bio
68.63%
% Without Bio
Why Audience Demographics Matter
Understanding who follows an account reveals the type of influence they hold. Accounts followed primarily by users with few followers indicate broad, mainstream appeal. Those with many high-follower followers have greater potential for content amplification through secondary sharing.
Account age distribution also tells a story: a follower base with many new accounts might indicate recent viral growth, while established followers suggest long-term, stable influence. Geographic data helps understand the cultural context and timezone spread of the audience.
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Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,163 analyzed135,446
Combined Engagement
0
Total Likes
135,446
Total Retweets
27,089
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
60%
With Hashtags
100%
With @Mentions
40%
With Links
Topical Analysis:
RT @RafaelNadal: #CHAMP10N
RT @manuginobili: 🇦🇷Seguiré vistiendo la #20 un tiempito más!! #sigaelbaile #elpibede40 🇺🇸Back with the @Spurs for another season #thrille…
RT @aarbeloa17: ¿¿¿De que planeta viniste @marcoasensio10???
RT @rogerfederer: ☁️9⃣🏆 https://t.co/5oaW0jGcCo
RT @sabatinigabyok: Como duele tu dolor! 😢 #Messi sos el más grande y un orgullo para mí ❤️ #messiporsiempre https://t.co/b4Hcc8sJMH
Key Insights & Takeaways
The user frequently collaborates with influencers and media outlets, which boosts visibility. They share both entertainment and socially relevant content, appealing to a broad audience. Their tweets often include links to events or stories, encouraging further interaction.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 211,199
- + High community engagement through conversations
- + Active presence with consistent posting
Opportunities
- ~ Optimize posting times for peak engagement windows
- ~ Analyze top-performing content for replicable patterns
- ~ Leverage geographic concentration for targeted content
- ~ Explore collaboration potential with followed accounts
Summary
This analysis of @Marin1966Marin reveals an well-established Twitter presence with 211,199 followers. The account demonstrates a conversation-first approach, averaging 119.2 engagements per tweet. Key strengths include consistent posting and an engaged audience, with opportunities to further optimize timing and content strategy based on the patterns identified in this report.
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