Marcus Butler
2,733,585
Followers
758
Following
12,043
Tweets
2,715.1
Avg Engagement
3,594
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @MarcusButler'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: Mega Influencer (1M+)
- Account Age:2009-10-12
- Verification:No
- Location:ANTE BERLIN
Data Summary
- Tweets Analyzed:3,154
- Avg Likes per Tweet:2,235.7
- Avg Retweets per Tweet:479.4
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,154 tweetsThe account shows strong engagement with its followers, as evidenced by the high average likes and retweets. The content seems to resonate well with the audience, encouraging interaction.
2,235.7
Avg Likes/Tweet
479.4
Avg Retweets/Tweet
7,051,250
Total Likes
1,512,103
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
2,159
Median Likes
349
Median Retweets
3,804
75th Percentile
51,469
Top Tweet
0.99
Engagement per 1K Followers
Normalized influence metric
Consistent
Engagement Pattern
Steady engagement across posts
Posting Behavior
Content style and format preferences
Broadcaster
Primarily shares original content
71.7%
Original
23.3%
Replies
4.8%
Retweets
0.3%
Quotes
0.0%
Threads
0.4%
With Media
29.3%
With Links
5.0%
With #Tags
34.8%
With @Mentions
21.8%
With Emojis
58
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.33
Reply/Original Ratio
0.05
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
67.2%
Weekday Posts
32.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,154 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This is a content-creator focused account that primarily shares original thoughts, ideas, and media. With original content dominating their feed, they position themselves as a source of new information rather than a curator. This strategy works well for establishing thought leadership.
The 150 retweets (5% 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 3,154 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 appears to be interested in personal interactions and entertainment, as seen in the top tweets involving friends and romantic references. The content is likely appealing to a younger, socially engaged demographic.
Average
Audience Quality
31.4%
Suspicion Index
34.2%
Low-Quality %
8
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
40.0%
Empty Bio
42.8%
<10 Tweets
8.1%
Mass Following (>2K)
0.0%
New (<90 days)
73.1%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.3%
No URL
28.4%
<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.
50,349,579
Total Potential Reach
8
Median Follower Reach
43
75th Percentile Reach
2.5%
>1K followers
0.4%
>10K followers
0.2%
>50K followers
0.1%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
31.4%
Creators
15,713 accounts
25.8%
Consumers
12,880 accounts
42.8%
Dormant
21,407 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):
269
Verified Followers
0.27% of total
10,051
Protected Accounts
9.95% of total
5 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 | 14,105,999 | Wrestler | Wrestling, Motivation, Self-promotion |
| @jamescharles | 7,093,683 | Makeup Artist | Makeup, Beauty, Art |
| @Ninja | 6,681,043 | Gamer | video games, business |
| @bunnydelphine | 2,067,103 | Influencer | cats, cosplay, gaming |
| @KameronBennett | 1,809,142 | DJ | Music, DJing, Booking |
| @gregjames | 1,584,021 | Radio Host | Radio, author, cricket |
| @JDaIey | 1,226,905 | - | - |
| @peta | 1,075,245 | Animal rights | Animal rights, Veganism, Activism |
| @OliWhiteTV | 1,066,011 | YouTuber | Travel, Adventure, Cryptocurrency |
| @IOHK_Charles | 975,946 | CEO | Blockchain, Cryptocurrency, Technology |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
57,185
Followers With Bio
43,814
Followers Without Bio
56.62%
% With Bio
43.38%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,154 analyzed121,979
Combined Engagement
48,410
Total Likes
73,569
Total Retweets
24,396
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
80%
With @Mentions
40%
With Links
Topical Analysis:
RT @HKane: Three lads who were brilliant all summer had the courage to step up & take a pen when the stakes were high. They deserve support…
We look like a cute couple @tyleroakley http://t.co/txvl63dw9d
RT for a follow #MarcusFollowSpree
Happy times with this one @niomismart ☺️ http://t.co/4BiI0RNfAd
Very proud of you right now @ConnorFranta. Everything's gonna be all good for you and the other boys <3
Key Insights & Takeaways
The user frequently interacts with other public figures, suggesting a focus on social media relationships and networking. The content is lighthearted and personal, indicating a casual and relatable public persona. The use of links in tweets may suggest a strategy to drive traffic or promote other content.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 2,733,585
- + Strong original content creation
- + 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 @MarcusButler reveals an exceptionally influential Twitter presence with 2,733,585 followers. The account demonstrates a content-creator strategy, averaging 2,715.1 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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