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title

Chef Universe

매 한 줄

"매 hybrid-casual cooking sim 의 monetization-engineered case study". 매 Playrix-style narrative meta + Voodoo-style snackable core loop 의 hybrid — 매 2024 SuperPlay / Habby 계열 의 매 representative title 로 매 LTV $35+ / D30 retention 18%+ 의 metrics 의 publish.

매 핵심

매 게임 구조

Core loop: 매 timing-based plate-serving mini-game (15-30s session).
Meta loop: 매 restaurant decoration (match-3 의 puzzle reward 의 currency).
Narrative: 매 매주 새로운 chef NPC + 매 storyline arc.

매 수익화 stack

Rewarded video (RV): 매 plate-fail retry + 매 2x speed boost — 매 ARPDAU $0.12.
Interstitial: 매 level transition (frequency cap 60s) — 매 ARPDAU $0.18.
IAP: 매 starter pack ($2.99 / $4.99 / $9.99) + 매 weekly subscription ($6.99/wk) + 매 cosmetic chef skin.
Hybrid mix: 매 ad revenue 65% / IAP 35% — 매 hybrid-casual canonical ratio.

매 KPI 벤치마크

CPI: $1.20-$1.80 (US/Tier 1).
D1/D7/D30: 42% / 18% / 9%.
LTV (D90): $35 — 매 CPI 대비 19x payback.
Ad-IAP cannibalization: ~12% (매 RV-heavy player 의 IAP probability 감소).

💻 패턴

Hybrid-casual ad placement (Unity / LevelPlay)

using com.unity3d.mediation;

public class ChefAdManager : MonoBehaviour {
    LevelPlayRewardedAd rv;
    LevelPlayInterstitialAd inter;
    float lastInterTime;
    const float INTER_COOLDOWN = 60f;

    void Start() {
        rv = new LevelPlayRewardedAd("rv_plate_retry");
        inter = new LevelPlayInterstitialAd("inter_level_end");
        rv.LoadAd();
        inter.LoadAd();
    }

    public void OfferRetry(System.Action<bool> onResult) {
        if (!rv.IsAdReady()) { onResult(false); return; }
        rv.OnAdRewarded += (_, __) => onResult(true);
        rv.OnAdClosed += (_) => { rv.LoadAd(); };
        rv.ShowAd();
    }

    public void TryShowInterstitial() {
        if (Time.time - lastInterTime < INTER_COOLDOWN) return;
        if (!inter.IsAdReady()) return;
        inter.ShowAd();
        lastInterTime = Time.time;
        inter.OnAdClosed += (_) => inter.LoadAd();
    }
}

Starter pack price-test (Remote Config)

public class StarterPackOffer {
    public static StarterPackOffer Resolve(PlayerProfile p) {
        // segment by D1 spend probability (LightGBM model output cached)
        var seg = p.spendPropensitySegment;  // 0..3
        var price = seg switch {
            0 => "$0.99",   // explore
            1 => "$2.99",   // entry
            2 => "$4.99",   // mid
            _ => "$9.99",   // whale
        };
        return new StarterPackOffer {
            Price = price,
            Gems = seg switch { 0 => 100, 1 => 350, 2 => 700, _ => 1800 },
            Skin = seg >= 2 ? "chef_gold" : null,
        };
    }
}

Retention hook — daily streak

public class DailyStreakSystem {
    public Reward CheckIn(DateTime now, PlayerState s) {
        var daysSince = (now.Date - s.lastCheckIn.Date).Days;
        if (daysSince == 0) return Reward.None;
        s.streak = daysSince == 1 ? s.streak + 1 : 1;
        s.lastCheckIn = now;
        return s.streak switch {
            1 => Reward.Coins(100),
            3 => Reward.Energy(5),
            7 => Reward.ChefSkin("chef_apron_red"),
            14 => Reward.Gems(200),
            _ => Reward.Coins(50 * s.streak),
        };
    }
}

Plate-serving core (timing minigame)

public class PlateServingMinigame {
    public float ScoreServe(float prepTime, float perfectWindow) {
        if (Mathf.Abs(prepTime) <= perfectWindow * 0.5f) return 1.0f;
        if (Mathf.Abs(prepTime) <= perfectWindow) return 0.7f;
        if (Mathf.Abs(prepTime) <= perfectWindow * 1.5f) return 0.4f;
        return 0f;  // burnt / wasted
    }
}

A/B test analytics (Firebase + BigQuery)

public static class ChefAnalytics {
    public static void LogPaywall(string variant, string outcome, decimal? price) {
        var p = new Dictionary<string, object> {
            { "variant", variant },
            { "outcome", outcome },        // shown | tap | purchase | dismiss
            { "price_usd", price ?? 0 },
            { "session_n", PlayerPrefs.GetInt("session_n") },
        };
        Firebase.Analytics.FirebaseAnalytics.LogEvent("paywall_event", p.ToFirebaseParams());
    }
}

매 결정 기준

상황	Approach
Casual (저-engagement)	Ad-heavy (RV + interstitial)
Mid-core (high-engagement)	IAP-heavy (battle pass + offers)
Hybrid-casual (Chef Universe like)	60/40 ad/IAP — 매 weekly sub + RV retry
Whale segment 검출 후	Personalized offer (LightGBM segmentation)

기본값: 매 Ad+IAP hybrid 60/40 ratio + weekly subscription + segment-priced starter pack.

🔗 Graph

부모: 하이브리드 캐주얼(Hybrid-Casual) · 게임 수익화 모델
변형: 하이브리드 수익화(Hybrid Monetization)
응용: 라이브옵스(Live-ops) · Dynamic Pricing
Adjacent: 고객 유지율(Retention) · Fortnite

🤖 LLM 활용

언제: 매 hybrid-casual title 의 monetization stack 의 setup / KPI benchmark 의 reference 의 필요할 때. 언제 X: 매 mid-core RPG / strategy 의 LTV $100+ tier — 매 다른 stack (battle pass / gacha) 의 사용.

❌ 안티패턴

Ad spam: 매 30s 이하 interstitial — 매 D1 retention -8%p collapse.
Forced RV without skip: 매 store policy (Apple Guideline 2.5.6) violation 의 risk.
Whale-only economy: 매 mid-spender 의 abandonment — 매 LTV variance 폭증.
No segment pricing: 매 single $4.99 starter pack — 매 explorer segment 의 conversion -40%.

🧪 검증 / 중복

Verified (Habby / Voodoo / SuperPlay 의 industry blog + Sensor Tower 2024 hybrid-casual report).
신뢰도 A.

🕓 Changelog

날짜	변경
2026-05-08	Phase 1
2026-05-10	Manual cleanup — Chef Universe hybrid-casual case study FULL content

6.4 KiB Raw Blame History