2nd/10_Wiki/Topic_General/Game_Design/Dynamic Offers.md

---
id: wiki-2026-0508-dynamic-offers
title: Dynamic Offers
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [dynamic-offer, contextual-offer, personalized-offer]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [monetization, mobile, offers, personalization, live-ops]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: typescript
  framework: live-ops-offer
---

# Dynamic Offers

## 매 한 줄
> **"매 player state 에 매 따라 매 individually-tailored 의 매 IAP bundle"**. 매 static catalog 의 evolution — 매 trigger event + 매 player feature + 매 ML scoring. 매 2026 mobile 의 매 default monetization surface — 매 LTV uplift 매 15-40%.

## 매 핵심

### 매 trigger 종류
- **Lifecycle**: 매 install D1, 매 first-defeat, 매 churn-risk.
- **Progression**: 매 level-up, 매 stage-clear, 매 stuck (3 fails).
- **Event**: 매 holiday, 매 weekend, 매 anniversary.
- **Contextual**: 매 low-resource, 매 PvP loss-streak.

### 매 offer 구성 요소
- **Price tier**: 매 $0.99 / $4.99 / $19.99 / $99.99.
- **Contents**: 매 currency + items + cosmetic.
- **Value display**: 매 "300% value" / "Best deal".
- **Urgency**: 매 timer, 매 limited inventory.
- **Eligibility**: 매 player feature gated.

### 매 응용
1. 매 starter pack (D1 high-conversion).
2. 매 stuck-pack (frustration relief).
3. 매 win-back (churned player 복귀).

## 💻 패턴

### Offer eligibility engine
```typescript
type OfferRule = {
  id: string;
  predicate: (p: PlayerState) => boolean;
  weight: number;
  cooldown_hours: number;
};

const RULES: OfferRule[] = [
  {
    id: "starter_pack",
    predicate: p => p.spend_total === 0 && p.session_count > 5,
    weight: 100,
    cooldown_hours: 24 * 7,
  },
  {
    id: "stuck_pack",
    predicate: p => p.consecutive_losses >= 3,
    weight: 50,
    cooldown_hours: 6,
  },
  {
    id: "winback",
    predicate: p => p.days_since_last_session >= 7 && p.spend_total > 0,
    weight: 80,
    cooldown_hours: 24 * 14,
  },
];

function selectOffer(p: PlayerState, now: number): OfferRule | null {
  const eligible = RULES
    .filter(r => r.predicate(p))
    .filter(r => !inCooldown(p, r.id, now, r.cooldown_hours));
  if (!eligible.length) return null;
  return weightedPick(eligible);
}
```

### Price-tier model (player-specific)
```typescript
function suggestPriceTier(p: PlayerState): number {
  const tiers = [0.99, 4.99, 9.99, 19.99, 49.99, 99.99];
  if (p.spend_total === 0) return 4.99; // starter
  const avg = p.spend_total / Math.max(1, p.purchase_count);
  // Pick tier near player's typical spend
  let best = tiers[0];
  for (const t of tiers) {
    if (Math.abs(t - avg) < Math.abs(best - avg)) best = t;
  }
  return best;
}
```

### Bundle value calculator
```typescript
type BundleItem = { id: string; quantity: number; reference_price: number };

function bundleValueRatio(items: BundleItem[], price: number): number {
  const total_ref = items.reduce((s, i) => s + i.quantity * i.reference_price, 0);
  return total_ref / price;
}

function valueLabel(ratio: number): string {
  if (ratio >= 5) return "BEST DEAL";
  if (ratio >= 3) return "GREAT VALUE";
  if (ratio >= 2) return "GOOD VALUE";
  return "";
}
```

### Urgency timer rendering
```typescript
class OfferTimer {
  expires_at: number;

  remainingLabel(now: number): string {
    const sec = Math.max(0, Math.floor((this.expires_at - now) / 1000));
    if (sec > 3600) return `${Math.floor(sec / 3600)}h ${Math.floor((sec % 3600) / 60)}m`;
    if (sec > 60) return `${Math.floor(sec / 60)}m ${sec % 60}s`;
    return `${sec}s`;
  }

  isExpired(now: number) {
    return now >= this.expires_at;
  }
}
```

### Conversion-rate A/B harness
```typescript
async function logOfferEvent(player_id: string, offer_id: string, event: "shown" | "clicked" | "purchased") {
  await analytics.track({
    user_id: player_id,
    event: `offer_${event}`,
    properties: { offer_id, ts: Date.now() },
  });
}

async function offerConversionRate(offer_id: string, since_ms: number) {
  const shown = await analytics.count({ event: "offer_shown", offer_id, since: since_ms });
  const purchased = await analytics.count({ event: "offer_purchased", offer_id, since: since_ms });
  return shown > 0 ? purchased / shown : 0;
}
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| 매 D0-1 player | Starter pack ($4.99, high value) |
| 매 stuck player | Stuck-pack (resource focus) |
| 매 churning | Winback (deep discount) |
| 매 whale | Limited cosmetic + currency bundle |

**기본값**: 매 trigger + eligibility + cooldown + 매 explainable rules first, ML overlay second.

## 🔗 Graph
- 부모: [[Game_Monetization_Strategy]] · [[LiveOps]]
- 응용: [[Capybara GO!]] · [[Data-Driven Personalization]]
- Adjacent: [[CPI (Cost Per Install)]]

## 🤖 LLM 활용
**언제**: 매 offer design, conversion analysis, rule engine setup.
**언제 X**: 매 cosmetic-only product — 매 dynamic 의 over-engineering.

## ❌ 안티패턴
- **Predatory targeting**: 매 frustrated whale 의 매 immediate offer.
- **Cooldown 무시**: 매 spam → 매 desensitization.
- **Fake urgency**: 매 reset timer → 매 trust loss.
- **Value 거짓 라벨**: 매 reference price inflation → 매 regulator risk.

## 🧪 검증 / 중복
- Verified (deltaDNA / Unity Gaming Services 2025 case studies).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — dynamic offers trigger + eligibility + value model. |