Balancer
Build Better. Build On Balancer. Join the community: https://discord.balancer.fi/
148,854
Followers
265
Following
3,531
Tweets
22.7
Avg Engagement
2,360
Listed
Yes
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Balancer'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:2019-08-18
- Verification:Yes
- Location:Ballerverse
Data Summary
- Tweets Analyzed:597
- Avg Likes per Tweet:14.5
- Avg Retweets per Tweet:8.2
- Followers Analyzed:50,000
Engagement Analysis
Based on 597 tweetsBalancer's tweets receive an average of 131 likes and 37 retweets, indicating moderate to high engagement. The content is often shared and discussed, especially around new developments and milestones.
14.5
Avg Likes/Tweet
8.2
Avg Retweets/Tweet
8,657
Total Likes
4,889
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
6
Median Likes
2
Median Retweets
26
75th Percentile
618
Top Tweet
0.15
Engagement per 1K Followers
Normalized influence metric
Long Tail
Engagement Pattern
Mix of hits and regular posts
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
24.3%
Original
48.4%
Replies
18.3%
Retweets
9.0%
Quotes
0.0%
Threads
0.0%
With Media
52.4%
With Links
8.9%
With #Tags
60.5%
With @Mentions
42.4%
With Emojis
160
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.99
Reply/Original Ratio
0.5
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
96.5%
Weekday Posts
3.5%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 597 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 109 retweets (18% 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 597 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 primarily consists of DeFi enthusiasts, investors, and developers interested in decentralized finance and blockchain technology. They are likely active in the crypto space and engaged with community-driven projects.
Average
Audience Quality
22.9%
Suspicion Index
24.0%
Low-Quality %
43
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
34.7%
Empty Bio
22.1%
<10 Tweets
12.9%
Mass Following (>2K)
0.0%
New (<90 days)
52.3%
Low Ratio (<0.1)
0.0%
New (<180 days)
82.0%
No URL
13.4%
<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.
60,109,830
Total Potential Reach
43
Median Follower Reach
168
75th Percentile Reach
6.4%
>1K followers
1.1%
>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).
51.1%
Creators
25,530 accounts
26.8%
Consumers
13,403 accounts
22.1%
Dormant
11,067 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):
2,024
Verified Followers
2.0% of total
5,411
Protected Accounts
5.36% 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 | 14,105,730 | Wrestler | Wrestling, Motivation, Self-promotion |
| @CryptoWeb3_NFT | 4,362,974 | - | - |
| @WhaleCartel | 2,730,525 | - | - |
| @gate_io | 1,706,768 | - | - |
| @KalaniBallFree | 1,245,429 | Athlete | Email Marketing, Entrepreneurship, Social Media |
| @LeBronJames | 1,006,024 | - | - |
| @TheCryptoKidsX | 983,046 | Adult Entertainment | Adult content, Spanish, Casting |
| @ZachBoychuk | 830,514 | Hockey Player | Hockey, Meme/NFT Trading, Ethereum |
| @WipeHomophobia | 697,407 | - | - |
| @GinoAssereto | 695,000 | Marketing Strategy Advisor | Crypto, Marketing, NFT |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
64,879
Followers With Bio
36,120
Followers Without Bio
64.24%
% With Bio
35.76%
% 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 $15Viral Tweets
Top 5 by likes+RTs from 597 analyzed1,712
Combined Engagement
947
Total Likes
765
Total Retweets
342
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
60%
With @Mentions
80%
With Links
Topical Analysis:
IMPORTANT: Because of a related issue, LPs of the following pools should remove their liquidity ASAP as the issue cannot be mitigated by the emergency DAO. https://t.co/WcBeBvjdY2
RT @ankrstaking: 📣 @ankrstaking X @balancer Galxe Campaign 150$ BUSD split by 3 lucky winners 🍀 How can you become eligible? 🤔 🐦 Follow @…
Monday 👀 https://t.co/aW8vlLoBwn
Joined the Balancer #buildermafia at ETHDenver 2023 @EthereumDenver Powered by @Galxe https://t.co/rI0INYq52q
.@RDNTCapital's new pool has taken the #1 spot on Arbitrum Arb season is just getting started https://t.co/nBXZLgNFv8
Key Insights & Takeaways
The account frequently highlights new developments and milestones, such as new pools and chain expansions. It leverages partnerships and collaborations to drive visibility and credibility. Engagement is driven by timely updates and community interaction.
Strengths
- + Established follower base of 148,854
- + 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 @Balancer reveals an growing Twitter presence with 148,854 followers. The account demonstrates a conversation-first approach, averaging 22.7 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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