1,645,463
Followers
405
Following
2,507
Tweets
1,024.3
Avg Engagement
2,521
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @p_lanzani'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:2010-10-11
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:2,463
- Avg Likes per Tweet:414.2
- Avg Retweets per Tweet:610.1
- Followers Analyzed:50,000
Engagement Analysis
Based on 2,463 tweetsTheir tweets receive high engagement, with an average of 13,000 likes and 7,700 retweets per post.
414.2
Avg Likes/Tweet
610.1
Avg Retweets/Tweet
1,020,140
Total Likes
1,502,793
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
127
Median Likes
389
Median Retweets
1,125
75th Percentile
65,655
Top Tweet
0.62
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
53.1%
Original
21.0%
Replies
24.4%
Retweets
1.5%
Quotes
0.0%
Threads
0.0%
With Media
29.9%
With Links
30.6%
With #Tags
70.6%
With @Mentions
2.7%
With Emojis
82
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.4
Reply/Original Ratio
0.06
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
76.4%
Weekday Posts
23.6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 2,463 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 601 retweets (24% 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 2,463 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 fans of teen dramas and nostalgic content, likely aged 18-35.
Average
Audience Quality
28.5%
Suspicion Index
36.0%
Low-Quality %
7
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
40.0%
Empty Bio
44.1%
<10 Tweets
3.0%
Mass Following (>2K)
0.0%
New (<90 days)
62.8%
Low Ratio (<0.1)
0.0%
New (<180 days)
93.5%
No URL
32.0%
<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.
16,159,218
Total Potential Reach
7
Median Follower Reach
53
75th Percentile Reach
2.3%
>1K followers
0.3%
>10K followers
0.1%
>50K followers
0.0%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
36.3%
Creators
18,131 accounts
19.7%
Consumers
9,842 accounts
44.1%
Dormant
22,027 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):
86
Verified Followers
0.09% of total
10,514
Protected Accounts
10.51% of total
4 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 |
|---|---|---|---|
| @MicaSuarez12 | 1,753,946 | Actress | Acting, Film, Argentina |
| @SinghLions | 1,335,214 | Restaurateur | Food, Travel, Influencer |
| @nico_riera | 1,019,309 | Actor | music, acting, travel |
| @grisici | 1,000,000 | - | - |
| @porliniers | 751,856 | Cartoonist | Dibujante, Editor, Conejo |
| @benjaminamadeo | 725,987 | Musician | Music, Acting, Argentina |
| @metroadelantado | 651,172 | Youtuber | YouTube, Metro, Adelantado |
| @ngmagaldi | 611,651 | Journalist | Journalism, Hosting, Entrepreneurship |
| @PrimeVideoLat | 476,119 | Streaming Service | Movies, TV shows, Entertainment |
| @DaliaGutmann | 370,928 | Comedian | comedy, Argentina, shows |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
61,412
Followers With Bio
38,588
Followers Without Bio
61.41%
% With Bio
38.59%
% 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 2,463 analyzed177,543
Combined Engagement
99,506
Total Likes
78,037
Total Retweets
35,509
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
40%
With @Mentions
20%
With Links
Topical Analysis:
Tremendo el capitulo de casi ángeles! Muchos recuerdos!!!
Fuimos, somos, y siempre seremos #TEENANGELS
RT @InfoManu: 1 RT = 1 VOTO Últimos días de votación para que Manu Ginobili #NBAVote pueda estar en el Juego de las Estrellas NBA! VAMOOO…
8 años?! Como pasa el tiempo jajaj saludos! https://t.co/jsDKqXSDJr
RT @InfoManu: 1 RT = 1 voto Asi de simple votas para que @manuginobili pueda ir al Juego de Estrellas NBA. Hay chances!!!!! Manu Ginobili…
Key Insights & Takeaways
They leverage nostalgia to connect with followers Their content is highly personal and emotional They maintain a consistent and warm tone in interactions
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 1,645,463
- + 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 @p_lanzani reveals an exceptionally influential Twitter presence with 1,645,463 followers. The account demonstrates a content-creator strategy, averaging 1,024.3 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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