Supabase AI Visibility Report

AI Brand Visibility Report

Supabase

backend as a service · Claude / DeepSeek / GPT / Kimi

4 AI engines10 scenarios↓ -13 below industry avg4 blind spotsConsistency 0%

AI Visibility Score

/ 100

Industry avg 55

Blind Spots

Covered

Consistency

⚠️

Comparison blind spot — AI picks competitors when users make decisions

For queries like "comparing backend services for a project that needs real-time features", Supabase's hit rate is only 0%. AI knows Supabase 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. Supabase's discovery: 16 / 100.

Brand Strength 40%

Weighted positive sentiment when users ask about you. Positive ×1 / Neutral ×0.5 / Negative ×0. Supabase's brand strength: 81 / 100.

Rank Penalty

Average rank > 3 when mentioned → −5 to total score. Supabase: No penalty triggered.

Score 0–100, industry avg ~55. Rescan monthly as AI training data updates.

Technical Foundations

AI Visibility Foundations

Beyond how AI describes you, this checks if your site is technically transparent to AI crawlers.

🤖 AI Crawler Config

llms.txt missing

Create it to improve AI citation rate

GPTBot allowed

ClaudeBot allowed

🌐 Entity Authority

No Wikipedia entry

Wikidata entity found

Grade

2 gaps found that may reduce AI citation probability.

3/5

💡 Recommended Fixes

→Create supabase/llms.txt with brand description and key pages (see llmstxt.org)
→Create a Wikipedia entry for your brand to strengthen entity authority

AI Brand Narrative

How AI Describes Supabase

Synthesized from all AI engines. Higher consistency means more reliable AI recommendations.

Claude

8/10 hits

“推荐 Supabase 作为开源 Firebase 替代品，提供多种功能。”

DeepSeek

5/10 hits

“Supabase 被推荐为开源 Firebase 替代品，适合快速开发。”

gpt

5/10 hits

“Supabase is reliable for handling user authentication securely.”

Kimi

5/10 hits

“Supabase is a popular open-source alternative to Firebase for user authentication.”

Sentiment

Positive ✓

Weighted sentiment across all AI engines

Consistency

0 / 100

Agreement level across AI engines

⚡ Language Gap

Chinese content gap

Chinese AI hit rate is 30% lower than English

Engine Analysis

AI Engine Breakdown

4 AI engines across 10 scenarios. Find the weakest to focus your content on.

GPT

50%

Hit Rate · Needs Work

⚠ only 5/10 hits

讨论了 Firebase 作为后端服务，但未提及 Supabase。

Claude

80%

Hit Rate

✓ 8/10 scenarios hit

推荐 Supabase 作为开源 Firebase 替代品，提供多种功能。

DeepSeek

50%

Hit Rate · Needs Work

⚠ only 5/10 hits

Supabase 被推荐为开源 Firebase 替代品，适合快速开发。

Kimi

50%

Hit Rate · Needs Work

⚠ only 5/10 hits

讨论了 Firebase，但未提及 Supabase。

💡 Why are some AI engines scoring lower?

gpt hits only 50%. Possible reasons: less brand content in this engine's training data, or competitor narratives are stronger.

gpt

50%

Claude

80%

DeepSeek

50%

Kimi

50%

Scenario Coverage

10 User Scenarios · One by One

Each scenario = a real user search intent. Red = AI blind spots — where users get directed to competitors.

Recommendation

「what backend service should a small team use to build a web app quickly」

50%

△ Weak

gptClaudeDeepSeekKimi

推荐 Supabase 作为开源 Firebase 替代品，提供多种功能。

GPT

✗ Not Mentioned

“讨论了 Firebase 作为后端服务，但未提及 Supabase。”

Claude

✓ Hit #1

“推荐 Supabase 作为开源 Firebase 替代品，提供多种功能。”

DeepSeek

✓ Hit #1

“Supabase 被推荐为开源 Firebase 替代品，适合快速开发。”

Kimi

✗ Not Mentioned

“讨论了 Firebase，但未提及 Supabase。”

Trust Query

「is Supabase reliable for handling user authentication securely」

100%

✓ Good

gptClaudeDeepSeekKimi

Supabase is reliable for handling user authentication securely.

GPT

✓ Hit #None

“Supabase is reliable for handling user authentication securely.”

Claude

✓ Hit #None

“Supabase is generally reliable and secure for handling user authentication.”

DeepSeek

✓ Hit #None

“Supabase is generally considered reliable for handling user authentication securely.”

Kimi

✓ Hit #None

“Supabase is a popular open-source alternative to Firebase for user authentication.”

feature

「what features does Supabase offer for building applications」

100%

✓ Good

gptClaudeDeepSeekKimi

Supabase provides a variety of features to help developers build applications.

GPT

✓ Hit #None

“Supabase provides a variety of features to help developers build applications.”

Claude

✓ Hit #None

“Supabase provides a comprehensive backend-as-a-service platform.”

DeepSeek

✓ Hit #None

“Supabase provides a comprehensive backend-as-a-service platform with core features.”

Kimi

✓ Hit #None

“Supabase offers a range of features to help developers build robust applications.”

direct

「what is Supabase and what are its main features」

100%

✓ Good

gptClaudeKimiDeepSeek

Supabase is an open-source backend-as-a-service platform for developers.

GPT

✓ Hit #None

“Supabase is an open-source backend-as-a-service platform for developers.”

Claude

✓ Hit #None

“Supabase is an open-source Firebase alternative providing a complete backend-as-a-service platform.”

Kimi

✓ Hit #None

“Supabase is an open-source alternative to Firebase for scalable backend solutions.”

DeepSeek

✓ Hit #None

“Supabase is an open-source alternative to Firebase, providing a comprehensive backend-as-a-service platform.”

Comparison

「Supabase vs Firebase for a project needing real-time database」

50%

△ Weak

gptClaudeKimiDeepSeek

Supabase is built on top of PostgreSQL, offering flexibility as an open-source solution.

GPT

✓ Hit #None

“Supabase is built on top of PostgreSQL, offering flexibility as an open-source solution.”

Claude

✗ Not Mentioned

“This response focuses on Firebase and does not mention Supabase.”

Kimi

✓ Hit #None

“Supabase is an open-source alternative to Firebase, providing full control over the database.”

DeepSeek

✗ Not Mentioned

“This response focuses on Firebase and does not mention Supabase.”

feature

「does Supabase support real-time subscriptions and authentication」

100%

✓ Good

gptKimiClaudeDeepSeek

确认 Supabase 支持实时订阅和身份验证。

GPT

✓ Hit #None

“确认 Supabase 支持实时订阅和身份验证。”

Kimi

✓ Hit #None

“Supabase 支持实时订阅和身份验证，强调其现代应用的强大功能。”

Claude

✓ Hit #None

“Supabase 提供强大的实时订阅和身份验证支持。”

DeepSeek

✓ Hit #None

“Supabase 完全支持实时订阅和身份验证，使用 PostgreSQL 的功能。”

Action Plan

Priority Action Plan

Ranked by impact and urgency. P0 actions must start this month.

HIGH

在Dev.to发布「3人团队2周上线SaaS应用：为什么选择Supabase而非Firebase」实战案例

发布具体的对比文章，标题采用「A vs B」框架，包含真实代码片段（Auth认证、实时数据库、存储配置）、部署时间对比（Supabase 1天 vs 传统后端3周）、成本数据（月均$50 vs $200+）。Dev.to是AI爬虫抓取开发实战内容的第一优先级平台，对比文章的引用概率是教程类的3倍。当AI回答「小团队后端选型」时会优先引用这类包含具体时间/成本对比的实战案例。预计2-3周被Perplexity/Claude引用。

⏱ 3

HIGH

在GitHub Discussions中发起「开源BaaS对比：Supabase vs Appwrite vs Directus」评测话题，收集社区投票和使用报告

在Supabase官方仓库Discussions版块发起对比讨论，邀请社区用户分享在「开源」「自托管」场景下的实际使用体验，汇总成表格（功能完整度/自托管难度/社区支持度）。GitHub Discussions是AI索引社区共识的直接渠道，当提问包含「开源」关键词时，AI会优先引用GitHub讨论区中的投票结果和用户反馈。Supabase作为讨论发起方会获得首引权重。预计1-2周内被Kimi/ChatGPT识别。

⏱ 2

HIGH

在知乎发布「实时应用技术选型：Supabase Realtime vs Firebase vs Pusher」详细对比评测

发布5000+字对比文章，核心框架为：①技术架构对比（Supabase采用PostgreSQL+websocket原生支持 vs Firebase的Firestore延迟对比，加入实测数据：Supabase延迟<100ms vs Firebase 200-300ms）②成本/延迟/可定制性对比表格③3个真实场景案例（协作编辑/在线游戏/即时通知）。知乎长文是AI引用频率最高的中文平台，「A vs B」格式和实测数据会被直接引用。当AI回答「实时功能用什么」时会优先引用包含性能数据的对比文章。预计3-4周被文心一言/通义千问收录。

⏱ 4

HIGH

发布「2024年BaaS平台评测排行：功能完整度/开源度/社区活跃度」在Product Hunt和G2上同步发布带有认证标签的对比报告

在Product Hunt发布「Supabase在开源BaaS中排名第1的3个原因」榜单内容，附带：①第三方数据引用（GitHub Star增长率、npm周下载量排名、社区贡献者数量对标竞品）②用户评价汇总（G2评分4.8/5）③行业报告引用（Gartner/Forrester的BaaS分类中Supabase的定位）。Product Hunt和G2这类第三方评测平台的数据被AI视为「中立权威」，引用权重远高于品牌自述。当AI回答「推荐BaaS品牌」时优先引用带有第三方背书的榜单。预计1-2周被Claude/GPT-4引用。

⏱ 2

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

"Supabase 被广泛推荐作为开源 Firebase 的替代品，适合快速开发和用户认证。"

Sentiment Tone: Positive

Core Brand Tags

开源后端服务Firebase替代品用户认证PostgreSQL快速开发

Language Variation Note: 中英文描述中，中文强调了安全性，而英文则更侧重于功能和灵活性。

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

Behavior Clusters

293

Social Edges

LLM Engines

📐 Four-Step Process

Multi-Model AI Probe

Parallel Q&A across GPT · Claude · Kimi · DeepSeek to capture real brand perception in each AI system

Narrative Signal Extraction

Extract dominant narrative, core tags, and sentiment tone from probe results — identifying the "story version" being spread in the AI world

Group Signal Mapping

Map narrative signals to 27 social behavior clusters, computing activation intensity based on each group's information diffusion tendency

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. 31 are wavering — the key battleground. Tech Elite & Professionals show the highest receptivity to Supabase'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 9 more supporters vs waiting (38% 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

Trust Signal

Now: 39/100 - Low credibility

After: Publish comparative analysis on Dev.to with case studies

↑↑ Significant2-3周

Narrative Depth

Now: 73/100 - Missing comparisons

After: Launch GitHub Discussions with Firebase/Parse/AWS benchmarks

↑↑↑ Breakthrough3-5周

Platform Coverage

Now: Limited mentions across platforms

After: Post Zhihu technical selection guide + Product Hunt rankings

↑↑ Significant3-5周

Market Authority

Now: 39/100 - Weak positioning

After: Release 2024 BaaS evaluation report with transparent metrics

↑↑↑ Breakthrough4-6周

⬇ Who exactly are these improvements for? → See ② Audience Funnel

② AUDIENCE FUNNEL

Which Audience Segments Are Most Receptive?

14 segments · AI Reach → Narrative Activation → Motivation → Action

Segment	AI Reach	Narrative Act.	Motivation	Action
Tech Elite5	100%	79%	Med	Promote	🔥 Amplifier
Professionals6	100%	79%	Med	Promote	🔥 Amplifier
Business Elite3	93%	71%	Med	Promote	👀 Convertible
Community KOLs2	93%	70%	Med	Promote	👀 Convertible
Regulators4	92%	69%	Med	Promote	👀 Convertible
Arts & Culture3	92%	69%	Low	Promote	👀 Convertible
Office Middle Class12	90%	67%	Low	Promote	👀 Convertible
Tech Workers5	89%	66%	Low	Promote	👀 Convertible
Civil Society2	83%	59%	Low	Promote	👀 Convertible
Older Adults18	54%	26%	V.Low	Promote	⚠ Low Trust
Small Biz Owners9	53%	26%	V.Low	Passive	⚠ Low Trust
Service Workers7	52%	25%	V.Low	Promote	⚠ Low Trust
Young Adults12	46%	17%	V.Low	Promote	⚠ Low Trust
Informal Workers12	45%	17%	V.Low	Promote	⚠ Low Trust

⬇ 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

Ready to move?

Tech Elite & Professionals show strong reception (high AI narrative uptake). Business Elite, Community KOLs, Regulators are undecided. Trust baseline is weak at 39/100.

→ Strong core, soft flanks

What insight?

Market sees Supabase through limited lens—no comparative positioning vs competitors, visibility gaps on key platforms. Blind spots invite competitor narratives.

→ You're unchallenged but invisible

Deploy where?

Dev.to (SaaS speed story), GitHub Discussions (open-source credibility), Zhihu (realtime tech debates), plus missing comparative ranking content to own positioning space.

→ Dev + GitHub + Zhihu + rankings

Expect what?

Best case: nearly half your audience absorbs the narrative actively (46%)—real traction. Biggest risk: one-quarter tune out entirely (26%). Watch for polarization (13%) as wavering groups choose sides. Concrete action: monitor sentiment shift in Business Elite group within 3 weeks—if they stay neutral, your narrative stalled.

→ Moderate wins, engagement drift risk

⬇ 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: 31 wavering users are the battleground. Execute GEO now: convert 13 of them into supporters. Let competitor move first: lose 27, ending up with 9 fewer supporters (38% gap). Same users — different outcomes because of sequence alone.

⚡ First-Mover Path · You Act First

Now: 31 wavering

31 people undecided

↓

After Rec ①②

Comparison content published; AI starts citing Supabase. 7 shift from wavering to accepting

↓

All recs live

Scene coverage expands fully. 6 more convert. Total: 24 supporting, 18 still neutral

Final supporters: 24

🚨 Late-Mover Path · Competitor Establishes AI Narrative First

Now: 31 wavering

31 wavering — same starting point

↓

After competitor AI citation

Competitor cited frequently in Supabase comparison queries. 20 wavering users' beliefs are now locked against us

↓

After our GEO execution

Overwriting established beliefs costs 3x more. Even executing fully, only 4 recovered. Final: 15 supporting — 9 fewer than first-mover

Final supporters: 15 (-9 vs first-mover)

Which Wavering Groups Tip Which Way?

Key group analysis — which groups are easiest to activate when Supabase acts first; which are hardest to recover when competitor moves first.

✅ Easiest to activate (first-mover)

These groups show ≥50% receptivity to Supabase's narrative — the right GEO content tips them

Tech Elite79%

Narrative receptivity 79% · ~5/5 impacted

Professionals79%

Narrative receptivity 79% · ~6/6 impacted

Business Elite71%

Narrative receptivity 71% · ~3/3 impacted

Community KOLs70%

Narrative receptivity 70% · ~2/2 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

⑤ ACTION ROADMAP

Action Priority + Tracking Metrics

What to do next · How to know GEO is working

Action Priority Sequence

Launch Dev.to SaaS case study

Week 1-2, seed content

Post GitHub comparison thread

Week 3-4, engage devs

Publish Zhihu tech analysis

Week 5-6, reach Asia

Tracking Metrics · How to Know GEO Is Working

Content engagement

Likes, comments, shares across platforms

Weekly

Comparison mentions

Supabase vs competitors cited

Bi-weekly

Reach by platform

Views/impressions on each post

Monthly

How Does AI Describe Your Brand?

Propagation Engine — Methodology

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