If you’re running traffic to gambling offers, you’ll want to check out the latest stats from Moloco DSP: GEOs, install costs, and app designs. Data is based on the period from May 5 to May 18, 2025.
These are not just numbers — they explain how the platform consistently delivers eCPI from $2 and why it’s scalable. What sets Moloco DSP apart from other ad networks, and why is it a great fit not only for solo media buyers but also for teams looking to scale? Let’s break down how it works — from bidding to optimization.
What is Moloco DSP and Why It’s Great for Arbitrage
Moloco is an in-app advertising DSP. Traffic buying here is powered by AI algorithms: the system automatically selects impressions and adjusts bids to drive installs or other desired actions. The platform analyzes data and optimizes delivery, minimizing the need for manual control.
- Low CPI entry point — great for testing and scaling.
- High retention — in-app traffic is higher quality than clickers or bots.
- Gambling creatives pass — moderation is softer than Meta or Google.
- Strong auto-optimization — AI adapts to user behavior.
- Traffic from partner networks — IronSource, [add actual sources] and more.
The platform is closed — direct access isn’t available right now. You can only get an account via rental. There are few public case studies — but also low competition. If you understand the mechanics, you can consistently capture high-ROI traffic.
How Moloco DSP Works — Simple Breakdown
Moloco is a platform built on machine learning and real-time optimization.
Once traffic starts, the system automatically:
- Analyzes and selects the most valuable requests;
- Processes them through 8–10 models (conversion probability, price prediction, fraud detection, frequency cap, LTV forecast, etc.);
- Calculates bids for each auction;
- Redistributes budgets by hour and day.
This delivers:
- Fast optimization for qualified leads;
- Smooth scaling without breaking the learning phase;
- Predictable install cost;
- Transparent analytics down to query level.
Decision-Making Architecture
Moloco uses a modular cloud-based architecture. Each module handles a key task:
- Data ingestion — Collecting and processing user data.
- Prediction engine — Predicting conversion likelihood.
- Bidding module — Real-time bidding in RTB auctions.
- Optimization loop — Model retraining as new data accumulates.
Each step passes through a logical chain — from data input to outcome — continuously refining itself: data → prediction → bid → result → next cycle.
How Bidding Works
Bidding is fully AI-managed. The algorithm evaluates:
- Probability that a user will convert;
- Probability of winning the auction;
- Value of that impression for campaign goals.
AI doesn’t turn off impressions — it adjusts bids based on conversion chance. No manual bidding: your influence comes from campaign objectives (e.g., CPI or ROAS) and clean tracking. Supplying the algorithm with quality input data is key.
Optimization Mechanics
Smart optimization = better ROAS. The system learns from each impression and action, optimizing toward your campaign’s goal. The cleaner and more consistent the data, the faster you reach profitability. Key success factors:
- Right goal set: For iGaming, start with ROAS goals — Moloco will optimize from the start.
- In-app video creatives: These outperform banners.
- Proper postbacks via MMP are connected.
- Sufficient budget: Minimum $300, ideally $500+.
Feed the system good data and a clear goal — and it will drive profitable campaigns.
Campaign Launch Guide
To run traffic, you need a verified account. Moloco no longer supports self-registration. Use agency accounts to launch. Here's what to do:
- Sign up at rentacc.agency.
- Top up your balance. Minimum deposit: $500.
- Submit an account request.
In the request, include: app link, timezone, GEO, and email for invite.
Launch Preparation
- App design: Plinko-style Android apps convert best.
- Objective: For iGaming, use In-App Events for proper optimization.
- Creatives: Prepare a set of video creatives — banners don’t perform well.
- Budget: At least $500 to exit the learning phase.
- Tracker: Required for optimization. Follow our setup guide.
Common Mistakes and Limitations
To avoid wasting budget, here’s what not to do:
Mistake 1: No postbacks = no optimization.
Mistake 2: Low budget = AI stays in the learning phase. Start with $250+.
Mistake 3: Creatives not tailored for in-app = no delivery.
Mistake 4: Mid-optimization changes — any edits may reset learning.
Platform limitations include: no manual bidding, no gender/age targeting, few public case studies — you’ll need to test and learn hands-on.
Conclusion
Moloco is a powerful in-app DSP where buying and optimization are fully AI-driven. The algorithm tracks behavior, predicts actions, and adjusts bids. There’s no manual setup — everything runs through machine learning.
That’s why it’s critical to set the right goal, creatives, and budget from the start. The platform gives access to premium traffic with less strict moderation — ideal for profitable scaling.
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