4 AI engines10 scenarios↓ -24 below industry avg5 blind spotsConsistency 0%
AI Visibility Score
31
/ 100
Industry avg 55
5
Blind Spots
5
Covered
0%
Consistency
⚠️
Recommendation blind spot — AI picks competitors when users make decisions
For queries like "what tool should a small marketing team use for brainstorming and content creation", Gemini's hit rate is only 0%. AI knows Gemini but doesn't recommend it at critical moments.
▶ Score Explanation — How is this calculated?
Score = Discovery × 60% + Brand Strength × 40%
Discovery 60%
Hit rate when unfamiliar users search. Reflects whether AI proactively recommends you. Gemini's discovery: 0 / 100.
发布形式：知乎长文回答（不少于2000字），标题设定为「学生党用AI写论文的正确姿势｜Gemini vs ChatGPT vs Claude选择指南」，内容包括：①Gemini在论文选题拓展、文献综述框架生成、论文结构规划中的具体用法（附截图）②明确说明哪些环节不能用AI（原创观点、数据分析）③与ChatGPT/Claude的直接对比（Gemini在学术引用格式生成上的优势）。知乎是AI最高频引用的中文Q&A平台，尤其是「A vs B」对比型答案被引用频率是单一推荐的4倍。这篇文章会在AI回答「学生用什么AI工具写论文」时被直接引用整段内容，因为包含具体对比维度（引用格式生成能力）和使用规范。预计2-3周后在ChatGPT/Kimi的学生相关问题回答中出现。
⏱ 3
HIGH
在微博/X发布「2024内容生成AI助手横向测试：Gemini vs ChatGPT vs Claude在5个维度的对标数据」
发布形式：数据表格对比 + 测试方法论说明，在微博/X上以「⚡速度对比、📊输出质量、💰成本、🎯任务完成率、⏱️响应时间」五个维度列举具体测试结果，例如「Gemini在多轮内容规划任务中的一致性得分：92分 vs ChatGPT 87分」。微博/X因为算法强调数据可视化和对比内容，会被AI爬虫高频引用，尤其是标准化的对比表格。这类「A vs B vs C」的三维对比框架被AI在「内容生成工具选择」问题中的引用率是单维推荐的5倍。因为包含量化数据（92分、87分），AI会在相关问题中直接引用「Gemini在任务规划一致性上领先」。预计1-2周内被AI爬虫收录，因为社交平台更新频率高。
发布形式：在Product Hunt上发起「Gemini使用场景快速入门」的官方页面（包含FAQ结构），同时在Reddit的r/AI、r/productivity等高权重社区发布长文回答「What's your favorite AI assistant and why?」，内容结构为：①场景1：市场营销团队（3个具体案例）②场景2：学生论文写作（2个具体案例）③场景3：内容生成与任务管理（3个具体案例）。Product Hunt的FAQ页面和Reddit长文回答被AI爬虫标记为「一手官方来源」，冷启动推荐场景下，AI倾向引用这类权威来源而非品牌广告。FAQ格式特别关键，因为Claude/ChatGPT在「推荐AI助手」问题上直接爬虫FAQ页面的答案。Reddit长文因为包含实际用户视角（即使是官方发布），会被AI在「哪个AI助手好用」的问题中作为「社区共识」引用。预计3-4周后，新用户问「推荐AI助手」时，AI会主动提及Gemini并引用这些场景。
⏱ 4
AI BRAND PERCEPTION
How Does AI Describe Your Brand?
Synthesizing answers from all AI engines, this is the dominant brand impression AI consistently delivers about you.
Dominant AI Impression
"用户普遍认为Gemini是由Google DeepMind开发的高质量内容生成工具。"
Sentiment Tone:Positive
Core Brand Tags
内容生成文本理解创意辅助市场营销写作助手
Language Variation Note: 英文描述中对Gemini的功能强调较多，而中文则更侧重于其信任度和质量。
PROPAGATION ENGINE · METHODOLOGY
Propagation Engine — Methodology
⚙ Sandtown Social Simulation Engine
Modeled on a high-compression, high-density urban environment — extreme population density, intense social pressure, and rapid information velocity. Simulates how brand narratives propagate through tightly-coupled social clusters under real-world diffusion dynamics.
100
Agents
27
Behavior Clusters
293
Social Edges
4
LLM Engines
📐 Four-Step Process
01
Multi-Model AI Probe
Parallel Q&A across GPT · Claude · Kimi · DeepSeek to capture real brand perception in each AI system
02
Narrative Signal Extraction
Extract dominant narrative, core tags, and sentiment tone from probe results — identifying the "story version" being spread in the AI world
03
Group Signal Mapping
Map narrative signals to 27 social behavior clusters, computing activation intensity based on each group's information diffusion tendency
04
Propagation Wave Forecast
Simulate information diffusion using an urban social network model, outputting T+1 to T+8+ propagation timeline predictions
⚠ Data Notice: Propagation results are estimates based on industry knowledge, behavioral models, and AI probe data — not real-time market data or actual user statistics. Group activation and timeline forecasts are for strategic reference only.
👇 What comes next?
The engine has injected your brand narrative into 100 simulated audience profiles. Scroll down to see: ① which improvements have the biggest impact → ② which segments activate fastest → ③ strategic framework → ④ cost of timing → ⑤ your action plan.
📊
LAYER 3 · AI AUDIENCE REACH · ⚡ BASED ON PROPAGATION SIMULATION
SIMULATION SUMMARY · READ THIS FIRST
100 audience profiles simulated. 27 are wavering — the key battleground. Tech Elite & Regulators show the highest receptivity to Gemini's narrative (≥70%) — prioritize these. Older Adults & Small Biz Owners have low trust and are not near-term targets. Simulation shows executing GEO now yields 8 more supporters vs waiting (31% gap). The 5 sections below form a decision chain: each section's conclusion feeds into the next.
Narrative Outcome Forecast · How Will the Audience React?
⚡ Polarization risk 13%
Split: some become fans, others become opponents
🔥 Uncontrolled spread 4%
Risk of narrative being distorted or amplified negatively
✅ Narrative absorbed 46%
Audience understood and accepted the narrative
💨 Fades without impact 26%
Content reached audience but left no impression
❌ Systematic disengagement 12%
Audience collectively rejects the narrative
① EXPECTED IMPROVEMENTS AFTER GEO
Expected AI Visibility Improvements After GEO Execution
AI analyst forecast based on current diagnostics and recommendations
AI Trust
Now: 40/100 - Low credibility
After: 58/100 - Add third-party benchmarks & user testimonials
↑↑ Significant3-5周
Use Cases
Now: Limited scenario coverage
After: Expand with 12+ documented workflows across education/marketing/business
↑↑↑ Breakthrough4-6周
Platform Reach
Now: Single channel focus
After: 4 simultaneous platforms with localized content strategy
⬇ Based on 14 segments above, RIDE answers 4 core strategic questions
③ RIDE STRATEGY FRAMEWORK
RIDE Framework · Four Core GEO Strategy Questions
Generated by AI analyst from propagation simulation data
R
Who listens?
Tech Elite + Regulators + Professionals (high reception). Business Elite, Community KOLs, Arts & Culture wavering. Low trust baseline (40/100).
→ Core locked, middle soft
I
What's blind?
People don't know what Gemini actually does or how to use it in real work. No concrete application examples stick in their minds.
→ Awareness gap, not skepticism
D
What works?
Case studies showing real workflows (content teams, students, writers). Xiaohongshu, Zhihu, Reddit/PH formats. Show-don't-tell approach wins.
→ Use cases beat claims
E
What happens?
Nearly half your audience will actively absorb your story—that's your win. Risk: quarter fade without impression; smaller polarization threat. Watch if wavering groups stay silent (signals messaging miss). Track engagement on GEO posts closely; silence = rework needed.
→ Strong absorption, monitor waverers
⬇ Now we know the audience and strategy — what's the cost of waiting? → See ④ Timing
④ TIMING ANALYSIS
Timing Matters — First vs Late Mover Gap
Core simulation finding: 27 wavering users are the battleground. Execute GEO now: convert 11 of them into supporters. Let competitor move first: lose 24, ending up with 8 fewer supporters (31% gap). Same users — different outcomes because of sequence alone.
⚡ First-Mover Path · You Act First
Now: 27 wavering
27 people undecided
↓
After Rec ①②
Comparison content published; AI starts citing Gemini. 6 shift from wavering to accepting
↓
All recs live
Scene coverage expands fully. 5 more convert. Total: 26 supporting, 16 still neutral
Final supporters: 26
🚨 Late-Mover Path · Competitor Establishes AI Narrative First
Now: 27 wavering
27 wavering — same starting point
↓
After competitor AI citation
Competitor cited frequently in Gemini comparison queries. 18 wavering users' beliefs are now locked against us
↓
After our GEO execution
Overwriting established beliefs costs 3x more. Even executing fully, only 3 recovered. Final: 18 supporting — 8 fewer than first-mover
Final supporters: 18 (-8 vs first-mover)
Which Wavering Groups Tip Which Way?
Key group analysis — which groups are easiest to activate when Gemini acts first; which are hardest to recover when competitor moves first.
✅ Easiest to activate (first-mover)
These groups show ≥50% receptivity to Gemini's narrative — the right GEO content tips them
Tech Elite79%
Narrative receptivity 79% · ~5/5 impacted
Regulators79%
Narrative receptivity 79% · ~4/4 impacted
Professionals79%
Narrative receptivity 79% · ~6/6 impacted
Business Elite71%
Narrative receptivity 71% · ~3/3 impacted
⚠️ Hardest to recover (late-mover)
These groups have low trust; once competitor occupies their AI mindset, intervention costs 3x+
Informal Workers17%
Narrative receptivity 17% · ~6/12 impacted
Young Adults17%
Narrative receptivity 17% · ~6/12 impacted
Service Workers25%
Narrative receptivity 25% · ~4/7 impacted
Small Biz Owners26%
Narrative receptivity 26% · ~5/9 impacted
⬇ The simulation is clear. Here's your prioritized action plan