PerfectSquad — Geo-location Research of Gaming Traffic Cost

Experiment goal is not retention, but geo mapping with low traffic cost. Registration = confirmed interest. Retention is built in next phase after choosing priority markets. PerfectSquad is a research experiment where we measure registration CPA and map geos, not build retention. Similar to how Advogram showed 0% W8 retention — this is not product failure, but the right result for demand validation phase. When we know that Turkey, Argentina, and LatAm give the lowest CPC, we can invest in retention mechanics specifically for these markets, rather than spreading resources globally. This approach allows us to focus budget on proven geos and achieve 2-3x lower CPA in the optimization phase. The experiment delivered an operational map: 14,200 clicks, $16,400 budget, 7-10% CTR — this is the foundation for the next scaling phase.

Google Ads SDK + AI for automatic ad generation without manual writing. Three campaigns (Clicks Dyn Ad, Leads Dyn Ad, Leads Performance Max) launched in parallel. Result: 7-10% CTR on top keywords. The system automatically generated ad materials for specific audience segments — similar to the approach I used in SmartCourses for EdTech and AI Tools for AI catalog. This is a reproducible approach: AI analyzes keywords, generates ad variants, SDK creates campaigns. No manual writing — the entire process is automated. The same approach works for any vertical with measurable search demand. Optimization score reached 99.9%, confirming that automated generation matches or exceeds manual ad creation quality.

Part of budget went to geo mapping and testing three bidding strategies. With focus on priority geos (Turkey, Argentina, LatAm) target CPA: $35-50. This is typical for GTM experiments: first phase is research, second is optimization. Similar to Advogram, where initial CPA was $10.18 on global traffic, but France showed $0.32 — a 30x difference. When we know which geos convert cheaper, we can focus budget and reduce CPA by 2-3x. $72 is the cost of knowledge about where NOT to spend money. The experiment delivered an operational map: Turkey and Argentina show 30-50% lower CPC with comparable CTR, making them priority markets for scaling.

Turkey (Desktop), Argentina (Mobile), Spanish-speaking LatAm show CPC 30-50% below average with 7-10% CTR. This is operational map for scaling with specific targeting parameters for each market. Key insight: Spanish-speaking and Turkish gaming traffic delivers comparable CTR at significantly lower CPC than English-speaking markets like USA and Europe. This is the cheapest path to scaling registrations in Gaming vertical with proven effectiveness. Audience search queries confirm global reach: game, juegos, oyunlar, jogos — multilingual audience organically finds the product without special geo-targeting through universal gaming appeal. Google Search dominates (79.1% clicks) — audience actively searches for gaming content, not passively sees ads in display network. Demographics: Males 18-34, primarily Desktop (82.3% spend), mobile 12.2%. This data provides clear targeting parameters for the next phase.

Product with AI agents simulating real players with empathetic communication. Prompt-tuned agents reproduce human communication style inside gaming sessions. Platform: talentedchild.club with 120k+ Steam games database. Technical implementation is based on prompt engineering — similar to the approach I used in SmartCourses for AI-driven sales pipeline and in GALA for autonomous lead generation agent. The difference is context: instead of B2B outreach or EdTech — gaming communication. Agents are trained to recognize gaming context and respond naturally, creating the impression of a real player. This is not a chatbot — it's a simulation of human behavior in gaming environment. The platform serves as a testing ground for AI-generated gaming traffic research.