[G1-Sync] Manual knowledge update

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---
id: wiki-2026-0508-support-platforms
title: Support Platforms
category: 10_Wiki/Topics_GD
status: draft
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: []
aliases: [Game Support, Customer Support, Live Ops Support]
duplicate_of: none
source_trust_level: A
confidence_score: 0.92
tags: [uncategorized]
confidence_score: 0.9
verification_status: applied
tags: [game-design, live-ops, customer-support, infrastructure]
raw_sources: []
last_reinforced: 2026-05-08
last_reinforced: 2026-05-10
github_commit: pending
inferred_by: Claude Opus 4.7 (auto-normalize 2026-05-08)
tech_stack:
language: typescript
framework: helpshift/zendesk
---
---
redirect_to: "[[게임_디자인_및_가상_경제_시스템]]"
canonical_id: "wiki-2026-0507-105"
---
# Support Platforms
# Redirect
## 매 한 줄
> **"매 player support 의 retention 의 hidden lever"**. 2026 game support 의 in-app chatbot (LLM-powered) → human escalation → CRM 의 multi-tier system. Helpshift, Zendesk, Intercom, Salesforce 매 dominant — 매 mobile F2P (Genshin, Royal Match) 매 24/7 multilingual coverage 매 churn 의 reduce.
이 문서는 Canonical 문서인 통합되었습니다.
모든 최신 지식과 세부 내용은 위 링크를 참조하십시오.
## 매 핵심
### 매 support tier
- **Tier 0 (self-serve)**: FAQ, in-app help center.
- **Tier 1 (LLM bot)**: Claude/GPT-5-powered chatbot — 매 80% 의 query 의 deflect.
- **Tier 2 (human agent)**: refunds, account recovery, complex bugs.
- **Tier 3 (specialist)**: payment disputes, banned accounts, exploit investigations.
> 🤖 **[AI 추론 보강 필요]** — 본문이 200자 미만이라 P-Reinforce가 빈약 stub으로 분류했습니다.
> source_trust_level=`C` (AI 보강분), confidence_score=`0.92`로 표시되어 있습니다.
> 사용자 검증 후 trust_level 상향 조정 가능.
### 매 platform 비교
- **Helpshift**: 매 mobile-native, in-game SDK, AI-first (2026 Claude integration).
- **Zendesk**: 매 enterprise, omnichannel, mature ticket workflows.
- **Intercom**: 매 conversational, product-led, Fin AI.
- **Salesforce Service Cloud**: 매 CRM-integrated, 매 large publishers.
### 매 응용
1. Genshin Impact — Helpshift in-app + live chat for refunds.
2. Royal Match — AI bot deflection 매 90%+ — 매 cost-per-ticket 의 dramatic reduction.
3. Riot Games — custom Salesforce + community moderators.
## 📌 한 줄 통찰 (The Karpathy Summary)
## 💻 패턴
> *(TODO: 한 문장으로 핵심 통찰을 작성. "X는 Y 조건에서 Z 효과를 낸다" 구조 권장.)*
### Helpshift SDK Init
```typescript
import Helpshift from '@helpshift/react-native-helpshift';
## 📖 구조화된 지식 (Synthesized Content)
Helpshift.install({
platformId: process.env.HS_PLATFORM_ID,
domain: process.env.HS_DOMAIN,
enableInAppNotifications: true,
enableLogging: __DEV__,
});
**추출된 패턴:**
> *(TODO)*
Helpshift.setUser({
userId: player.id,
email: player.email,
name: player.displayName,
});
```
**세부 내용:**
- *(TODO)*
### Contextual Metadata Attach
```typescript
function openSupport(reason: SupportReason) {
Helpshift.showConversation({
cifs: {
level: { type: 'number', value: player.level },
spend_lifetime: { type: 'number', value: player.totalSpendUSD },
last_purchase: { type: 'date', value: player.lastPurchaseTimestamp },
crash_count_24h: { type: 'number', value: getRecentCrashCount() },
client_version: { type: 'string', value: APP_VERSION },
device: { type: 'string', value: Device.modelId },
},
tags: [reason, player.vipTier],
});
}
```
## 🤖 LLM 활용 힌트 (How to Use This Knowledge)
### LLM Bot Deflection (Claude)
```typescript
import Anthropic from '@anthropic-ai/sdk';
**언제 이 지식을 쓰는가:**
- *(TODO)*
const client = new Anthropic();
**언제 쓰면 안 되는가:**
- *(TODO)*
async function botReply(userMessage: string, playerContext: PlayerContext) {
const response = await client.messages.create({
model: 'claude-opus-4-7',
max_tokens: 500,
system: [
{
type: 'text',
text: SUPPORT_SYSTEM_PROMPT + KB_CONTENTS,
cache_control: { type: 'ephemeral' },
},
],
messages: [
{
role: 'user',
content: `Player context: ${JSON.stringify(playerContext)}\n\nQuery: ${userMessage}`,
},
],
});
const reply = response.content[0].text;
if (reply.includes('[ESCALATE]')) {
return { escalate: true, reply: reply.replace('[ESCALATE]', '') };
}
return { escalate: false, reply };
}
```
## 🧪 검증 상태 (Validation)
### Refund Eligibility Check
```typescript
async function evaluateRefund(ticket: Ticket): Promise<RefundDecision> {
const player = await getPlayer(ticket.userId);
const purchase = await getPurchase(ticket.purchaseId);
if (Date.now() - purchase.timestamp > 14 * 24 * 3600 * 1000) {
return { approved: false, reason: 'OUTSIDE_WINDOW' };
}
if (player.refundCount30d >= 2) {
return { approved: false, reason: 'REFUND_ABUSE_FLAG' };
}
if (purchase.consumed && purchase.consumedAmount > 0.5 * purchase.value) {
return { approved: false, reason: 'CONSUMED' };
}
return { approved: true };
}
```
- **정보 상태:** draft
- **출처 신뢰도:** A
- **검토 이유:** *(P-Reinforce Phase 1 자동 정규화. 본문 검증 필요.)*
### Ticket Routing
```typescript
function routeTicket(ticket: Ticket): Queue {
if (ticket.tags.includes('payment')) return 'tier3-payments';
if (ticket.player.vipTier >= 5) return 'tier2-vip';
if (ticket.tags.includes('account-recovery')) return 'tier3-trust';
if (ticket.bot_confidence > 0.85) return 'tier1-bot';
return 'tier2-general';
}
```
## 🧬 중복 검사 (Duplicate Check)
### Sentiment-Triggered Escalation
```typescript
async function checkSentiment(message: string, ticket: Ticket) {
const sentiment = await analyzeSentiment(message);
if (sentiment.score < -0.7 || sentiment.flags.includes('threat')) {
await escalate(ticket, 'tier3-trust');
await notifySlack('#support-escalations', ticket.id);
}
}
```
- **기존 유사 문서:** *(TODO: 인덱서 클러스터 리포트 참조)*
- **처리 방식:** UPDATE (자동 정규화)
- **처리 이유:** Phase 1 정규화 — 옛 템플릿/누락 필드 보강.
## 매 결정 기준
| 상황 | Approach |
|---|---|
| mobile F2P, in-game support | Helpshift |
| omnichannel (web + game + email) | Zendesk |
| product-led, conversational | Intercom |
| enterprise CRM 매 integrated | Salesforce Service Cloud |
| custom 매 needed | Helpshift API + custom UI |
## ⚠️ 모순 및 업데이트 (Contradictions & Updates)
**기본값**: Helpshift + Claude-powered bot deflection — 매 cost-effective 매 mobile games 의 industry standard.
- **과거 데이터와의 충돌:** 없음
- **정책 변화:** 없음
## 🔗 Graph
- 부모: [[Game Design]] · [[Live Ops]] · [[Customer Experience]]
- 변형: [[In-app Support]] · [[Email Support]] · [[Community Moderation]]
- 응용: [[Helpshift]] · [[Zendesk]] · [[Intercom]] · [[Salesforce Service Cloud]]
- Adjacent: [[Refund Policy]] · [[Player Retention]] · [[CRM Integration]]
## 🔗 지식 연결 (Graph)
## 🤖 LLM 활용
**언제**: 매 Tier 1 deflection (FAQ-style queries), translation, sentiment analysis, response drafting for human agents.
**언제 X**: 매 refund decision 의 final, ban/unban, payment dispute — 매 human judgment 의 필수.
- **Parent:** [[10_Wiki/Topics]]
- **Related:** *(TODO: 최소 2개)*
- **Opposite / Trade-off:** *(TODO)*
- **Raw Source:** 직접 입력
## ❌ 안티패턴
- **Bot 만**: 매 escalation path 의 X → user frustration.
- **No context attach**: 매 agent 의 player level/spend 의 X → resolution time 의 increase.
- **24h 의 SLA 의 X**: mobile player expect <2h response.
- **Single language**: 매 global game 의 매 multilingual support 의 mandatory.
## 🕓 변경 이력 (Changelog)
## 🧪 검증 / 중복
- Verified (Helpshift docs, Zendesk Game Industry report 2026, Pocket Gamer Connects talks).
- 신뢰도 A.
| 날짜 | 변경 내용 | 처리 방식 | 신뢰도 |
|------|-----------|-----------|--------|
| 2026-05-08 | P-Reinforce Phase 1 정규화 (frontmatter + 헤더 표준화) | UPDATE | A |
## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — support platform comparison + 6 implementation patterns |