Follower Analytics Report
Founder at #ozzo_events: host better virtual business-social events. Passionate about #futureofwork Also tweet about crypto, ethereum & social media
Executive Summary
The follower base of @Leo_Glisic presents a highly engaged and professionally relevant audience, with 95.4% identified as active posters and a lead potential score of 58/100. Although only 35.0% of the 3,400 total followers are currently DM, able and none have open direct messages, the demographic profile is strongly aligned with high, value sectors, as evidenced by top bio keywords such as crypto, web, founder, and ethereum alongside interests in AI & ML and Business & Startups. The audience composition reflects a concentrated professional network where 21.9% are verified accounts and 55.6% are assessed as likely genuine, primarily located in San Francisco, CA with professions ranging from Engineer / Developer to Founder / CEO. While the absence of email addresses or phone numbers in bios limits immediate contact options, the high percentage of followers with website links (25.9%) and a strong database match rate of 74.5% suggest significant potential for targeted outreach through alternative channels.
At a Glance
Summary metrics computed from all 3,400 follower profiles in the downloaded data for @Leo_Glisic.
Lead Generation & Outreach
Reachability metrics from profile data (bios, URLs, DM settings) enriched with contact info from our 1.1B profile database.
With a lead potential score of 58/100 and 95.4% of users actively posting, @Leo_Glisic's audience presents moderate engagement opportunities despite only 35.0% (1,189 accounts) being DM, able. The presence of website links on 25.9% of profiles (879 accounts), predominantly utilizing linktr.ee, suggests a reliance on external traffic rather than direct email capture, as zero matched profiles currently display open emails or DMs. Partnerships should prioritize content collaboration over direct sales outreach given the lack of accessible contact information and the high volume of active but potentially unreachable followers.
Potential
Reachability
Computed from DM settings, bio URLs, and posting activity in the follower data.
Contact Channels
Emails, phone numbers, and DM settings sourced from our database of 1.1B profiles. 2,534 of 3,400 followers were matched.
Cross-Platform Presence
Social links found in follower bios and our database records.
Where They Link
Domains extracted from website URLs in follower profiles.
Audience Authenticity & Trust
Bot risk scored from account age, activity, and follower/following ratios. Verification status from X's API data.
While @Leo_Glisic's 3,400 followers show a strong historical foundation with 34.4% of accounts aged over a decade and only 1.3% under one year, the overall risk profile is mixed due to 30.4% being flagged as high risk and 14.0% appearing suspicious. The verified status covers just 21.9% of the audience (736 blue checks and 7 business accounts), suggesting that a significant portion of the follower base may be inflated or inactive despite the account's median age distribution favoring long, term stability. Partnerships should proceed with caution, requiring rigorous vetting to ensure the high, risk segment does not undermine campaign performance or brand reputation.
Bot Risk Assessment
ML ModelScored using account age, tweet count, follower/following ratios, and bio completeness.
Likely Genuine: Real users with normal activity patterns, established accounts, and healthy engagement ratios.
Suspicious: Accounts showing some unusual signals like low activity relative to their age, or atypical follower/following ratios. Not necessarily bots, but worth a closer look.
High Risk: Accounts with multiple bot-like signals such as very new accounts with no posts, or extreme follower/following imbalances. May include inactive or spam accounts.
2,657 non-verified accounts analyzed by ML model. 743 verified accounts were automatically classified as genuine.
We flagged 475 suspicious and 1,034 high-risk accounts. Run these through our Advanced Bot Detector to get a per-account AI verdict based on their actual posts and behavior.
Account Age Distribution
Based on account creation dates from X's API.
Verification Breakdown
Verification tiers from X's verified status field.
Accounts with older creation dates and verified status are stronger indicators of authentic, engaged followers.
Audience Profile & Interests
Interests and professions classified from follower bios. Geographic data from self-reported locations. Keywords, hashtags, and mentions extracted from bio text.
This highly concentrated audience of 3,400 followers consists primarily of engineers, founders, and investors based in San Francisco who are deeply engaged with crypto, Web3, and AI sectors. With 73.3% maintaining bios that explicitly highlight keywords like "founder" and "ethereum," this group represents a high, value target for B2B partnerships or product launches within the blockchain ecosystem. Their strong alignment with technology and startup interests suggests they are ideal prospects for outreach campaigns focused on early, stage funding, developer tools, or strategic collaborations in the Web3 space.
Audience Interests
Derived from 1,578 bios (46.4% of 3,400 followers)
Profession / Industry
Identified from 1,578 profiles with classifiable bios
Geographic Distribution
Based on self-reported locations in follower profiles. 48.4% of 3,400 followers have a location set.
What They Talk About
Top keywords extracted from follower bios. Larger words appear more frequently across profiles.
Popular Hashtags
Hashtags in follower bios showing community affiliations
Mentioned Accounts
Accounts frequently referenced in follower bios
Network Composition
Follower size, engagement ratios, and activity levels computed from each account's public profile metrics.
With 78.4% of followers falling into the Nano tier and 75.3% classified as Consumers, @Leo_Glisic's network prioritizes broad reach over concentrated influencer leverage, suggesting that partnership strategies should focus on mass, market messaging rather than elite co, branding. The audience's heavy concentration in Crypto, AI, and Engineering professions indicates high relevance for B2B tech solutions, yet the low average follower count per account (4,757) implies that engagement metrics will likely reflect authentic community interaction rather than viral amplification from macro, accounts. Evaluators should leverage this demographic to test product, market fit within the Web3 sector while managing expectations regarding rapid scalability through existing follower connections.
Influence Tiers
Followers grouped by their own follower count (Nano: under 1K, Micro: 1K-10K, Mid: 10K-100K, Macro: 100K+).
Account Type Distribution
Classified by follower-to-following ratio. Influencers have high ratios, mass followers have low ratios.
Activity Level
Tweet count distribution. Median: 632 tweets. 4.6% have never tweeted.
Influencer Types
Classification based on our database of 1.1B profiles
@Leo_Glisic Across twtData
News mentions pulled from our article database. Related tools for deeper analysis.
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Notable Followers
Top 10 accounts ranked by followers, tweet count, and list appearances from the CSV data.
Evaluating @Leo_Glisic's audience reveals a high, value network anchored by influential figures like Vitalik Buterin and Andre Cronje, whose combined reach of over 6.3 million followers signals significant potential for brand amplification within the crypto ecosystem. With nearly 22% of the total following verified and 149 accounts exceeding 10K followers across top tiers, this demographic offers a concentrated pool of industry leaders and early adopters ideal for strategic partnerships or targeted outreach. Leveraging these specific metrics allows you to prioritize engagement with verified power users who drive disproportionate influence compared to the broader follower base.
| Account | Followers | Tweets |
|---|---|---|
| @VitalikButerin | 5,908,706 | 21,615 |
| @tobi | 450,551 | 8,341 |
| @AndreCronjeTech | 438,656 | 136 |
| @HerbertRSim | 373,096 | 34,179 |
| @imTokenOfficial | 286,861 | 5,685 |
| @DegenSpartan | 271,905 | 966 |
| @whiterabbitb0t | 257,845 | 86,583 |
| @juanblanco76 | 252,804 | 225,778 |
| @robtswthrayguns | 238,449 | 101,286 |
| @ether_fi | 197,407 | 6,656 |
| Account | Tweets | Followers |
|---|---|---|
| @BillMoore20 | 441,775 | 152,377 |
| @gohsuket | 296,268 | 2,963 |
| @DanielleFong | 283,086 | 60,925 |
| @antiprosynth | 248,691 | 82,722 |
| @MonchitoPelu | 245,387 | 3,067 |
| @juanblanco76 | 225,778 | 252,804 |
| @PawlowskiMario | 216,659 | 100,668 |
| @Ricardo__Cabral | 204,984 | 65 |
| @SanUvacha | 195,345 | 9,773 |
| @mvollmer1 | 193,762 | 93,385 |
| Account | Listed | Followers |
|---|---|---|
| @VitalikButerin | 39,788 | 5,908,706 |
| @AndreCronjeTech | 5,647 | 438,656 |
| @DegenSpartan | 5,081 | 271,905 |
| @tobi | 4,334 | 450,551 |
| @juanblanco76 | 3,974 | 252,804 |
| @SmallCapScience | 3,788 | 111,887 |
| @peteskomoroch | 2,587 | 50,974 |
| @Cryptoyieldinfo | 2,281 | 112,684 |
| @IamCryptoWolf | 1,678 | 112,925 |
| @lex_node | 1,603 | 77,008 |
Key Takeaways
6 data-driven insights automatically generated from the metrics above.
Top industries among @Leo_Glisic's followers: "AI", "Ethereum", "Crypto" (based on 2,534 profiles matched in our database).
Lead potential score of 58/100. 35.0% accept DMs, 25.9% have a website link.
Top bio keywords: "crypto", "web", "building" -- revealing what @Leo_Glisic's audience talks about.
21.9% verified is well above average, signaling engaged, invested users.
San Francisco, CA is the top location among @Leo_Glisic's followers.
78.4% are nano-influencers (<1K followers), but 149 accounts have 10K+ followers.
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