D A V I D
confidence is key 👑 [email protected] 📩
56,334
Followers
45
Following
5,395
Tweets
327.9
Avg Engagement
21
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @davidpottsx'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: Mid-Tier (10K+)
- Account Age:2015-03-28
- Verification:No
- Location:Bolton, England
Data Summary
- Tweets Analyzed:3,105
- Avg Likes per Tweet:80.6
- Avg Retweets per Tweet:247.3
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,105 tweetsHis tweets typically receive a high number of likes and retweets, indicating strong audience interaction. The engagement is consistent across his posts.
80.6
Avg Likes/Tweet
247.3
Avg Retweets/Tweet
250,416
Total Likes
767,729
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
12
Median Likes
1
Median Retweets
64
75th Percentile
271,938
Top Tweet
5.82
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Commentator
Adds perspective to others content
33.5%
Original
12.2%
Replies
23.0%
Retweets
31.3%
Quotes
0.0%
Threads
0.1%
With Media
48.0%
With Links
23.1%
With #Tags
49.7%
With @Mentions
49.4%
With Emojis
82
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.37
Reply/Original Ratio
1.36
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
65.5%
Weekday Posts
34.5%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,105 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 713 retweets (23% 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 3,105 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 10,000 followersHis audience appears to be interested in personal development, lifestyle, and motivational content. They engage with his tweets through likes and retweets.
Below Average
Audience Quality
37.5%
Suspicion Index
100.0%
Low-Quality %
44
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
100.0%
Empty Bio
100.0%
<10 Tweets
0.0%
Mass Following (>2K)
0.0%
New (<90 days)
0.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
93.0%
No URL
100.0%
<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.
7,119,085
Total Potential Reach
44
Median Follower Reach
172
75th Percentile Reach
4.0%
>1K followers
0.5%
>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).
0.0%
Creators
0 accounts
0.0%
Consumers
0 accounts
100.0%
Dormant
10,000 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):
0
Verified Followers
0.0% of total
1,893
Protected Accounts
18.93% of total
7 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 |
|---|---|---|---|
| @HollyHaganBlyth | 1,513,646 | Reality TV Star | Geordie Shore, Makeup, Booking |
| @courtneyact | 386,780 | Author | Author, DWTSau, DragRace |
| @zammit_marc | 384,794 | Filmmaker | Film, Acting, Producing |
| @Dylan_Bostic | 347,170 | Wrestler | Pro Wrestling, Boxing, Acting |
| @STU_ACTOR | 339,259 | Actor | Acting, British, TV |
| @joeldommett | 256,649 | Comedian | Comedy, Touring, Book |
| @Brettmorseoly | 147,233 | - | - |
| @charliewernham | 129,897 | Actor | Actor, British, Comedy |
| @rosentweets | 125,605 | Gardener | Football, Gardening, Cooking |
| @CherylHoleQueen | 117,834 | Drag Queen | Drag, Essex, RuPaul |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
4,992
Followers With Bio
5,008
Followers Without Bio
49.92%
% With Bio
50.08%
% 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 3,105 analyzed766,507
Combined Engagement
23,193
Total Likes
743,314
Total Retweets
153,301
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
80%
With @Mentions
80%
With Links
Topical Analysis:
RT @bradan: This is a double banana. RT for 5 years of good luck. Ignore for 10 years of bad luck. Wouldn't risk it https://t.co/eeAF33av6W
RT @skxters: rt or badluck all 2018 https://t.co/nvJGcN9CNv
RT @coleyculture: this horse is so damn happy, imma have to rt for good luck https://t.co/xr3hWlMyJM
Just a little message to all the men and women who comment VILE things on my pictures. Yes I am fat and yes I am gay. Grow up and get over it, you’re boring. I’m not going to change so deal with it and stop searching for my name just to troll me because you’re embarrassing. LOL
RT @daniellebushh: Help a gal out guys? @MarcKinchen https://t.co/YW76ApUIVl
Key Insights & Takeaways
He openly discusses personal challenges and body image, which resonates with his audience. He uses humor and confidence in his messaging to connect with followers. He shares personal milestones, such as passing a driving test, to highlight progress and motivation.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 56,334
- + 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 @davidpottsx reveals an well-established Twitter presence with 56,334 followers. The account demonstrates a content-creator strategy, averaging 327.9 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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