AI growth consultant for apps and subscription businesses
Vlad Yasinski builds and runs full-cycle marketing systems for app and subscription businesses: paid acquisition, web funnels, analytics and BI, automation and competitor intelligence in one loop. Two apps taken to Top-1 in their US App Store categories, Facebook and TikTok budgets of up to $1.5M per month. For founders and growth leads who already spend on paid acquisition and need tracking, reporting and budget decisions that hold up.
The Control Room above walks one payment through the stack. These are the gaps that run is built to close.
Ad platforms report one number and Stripe shows another.
Reports take a person's week, and alerts arrive after the money is spent.
Budget rules live in one person's head.
An AI marketing system connects the tools that spend and measure your money: ad platforms, checkout, server-side tracking, BI and automation. Agents read the dashboards and propose actions, and a person approves every budget change. Vlad Yasinski builds and runs these systems for app and subscription businesses. He has 10+ years in paid acquisition and took two apps to Top-1 in their US App Store categories.
The agent proposes a lower daily budget and waits. Nothing changes until you approve, edit or reject.
Weekly competitor brief
Intelligence. Public ad libraries and store pages, checked on a schedule under platform terms, become a weekly brief. Watched pages: App Store, Google Play, public ad libraries. Weekly brief, drafted from public data and sent to AI agents.
Spend the budget
Acquire. Ad platforms spend the budget against payback and ROAS rules set before launch.
Take the payment
Convert. Landing page, checkout and paywall send each step as an event the ad platform can learn from.
Join spend and revenue
Measure. One data layer joins spend and payments. Dashboards show CAC, LTV, ROAS and payback by cohort.
Read the numbers, draft changes
Automate. Agents read the dashboards, spot broken rules and draft a proposal with reasons attached.
Used for analysis, scripts and reporting automation: Claude and Cursor. Typical stack: LLM agents, n8n, OpenAI, Gemini, MCP connectors, scripts.
Product names and logos belong to their owners. They appear only to show tools used or typical in this work. No endorsement or partnership is implied. To request removal of a logo, use the contact form. A dashed outline marks a typical stack tool: an example of what a system like this runs on, listed without a claim of past use. Letter tiles are monograms drawn for this site and are not the owners' logos. Apple, App Store, iOS, SKAdNetwork, Google, Google Play and Android are trademarks of their respective owners.
Each budget change waits here. You approve, edit or reject it.
Agent proposalSample
Lower the daily budget
Sample campaign A on Meta, US
Why: a rule fired
Approve sends the new budget to Meta. Nothing changes until you decide.
Illustrative rule, simplified: CPA must not exceed 90-day revenue per subscriber. Sample 90-day revenue per subscriber: $30. Sample CPA: $36. Over the ceiling by $6.
Budget change applied (sample)
Daily budget: $100 to $60
No change sent (sample)
Daily budget stays at $100
Approved by you (sample).Rejected by you (sample).Edited. Tap Approve to send this change.
Map your own stack in an audit.
Fixed scope. You get a ranked list of gaps and the order to close them.
Vlad Yasinski is a performance marketer and growth consultant based in Warsaw, Poland, with 10+ years of paid acquisition experience. He took two apps to Top-1 in their US App Store categories, managed Facebook and TikTok budgets of up to $1.5M per month, and builds the analytics, web funnels and automation around paid acquisition for app and subscription businesses.
InPulse (Health & Fitness) reached Top-1 in its US App Store category at $500K+ per month on Facebook and TikTok, run on hard ROAS and payback targets. It is now in AIBY's portfolio.
Read the caseThemify (design and graphics) returned to Top-1 in its US App Store category. The work included running the creative engine with in-house design and motion.
Read the caseAt DreamTeam Apps I built web funnels end to end: landing pages, Stripe checkout, Meta Pixel and Conversions API, BI and FunnelFox, with performance read on actual payments.
Read the caseFor a client under NDA I took over an unprofitable app portfolio and rebuilt it to positive unit economics with budget-allocation logic, scaling thresholds, structured testing and clean reporting.
Read the casePaid acquisition, funnels, measurement, agent ops and competitor intel are separate parts with their own rules. They share one loop: measure, decide, approve, apply. Nothing live changes until a person approves.
Weekly
You decide
Nothing live changes until a person approves.
Channels, budgets, pacing, kill and scale.
Parts
Control: pacing and kill-scale rules
Feeds Apply
Data flow
Landing, checkout, subscription events, server-side tracking.
Parts
Control: payment and event integrity
Feeds Measure
Tools
Data flow
Attribution, one data layer, dashboards, unit economics, forecasts.
Parts
Control: trusted numbers before spend moves
Feeds Measure
Tools
Data flow
Agents read dashboards and draft; a person approves each budget change.
Parts
Control: person approves every budget change
Feeds Approve
Tools
Used for analysis, scripts and reporting automation
Typical stack
Data flow
Public sources on a schedule, weekly brief, public data only.
Parts
Control: schedule and public-data-only
Feeds Decide
Tools
Data flow
Select a system to see its parts, control and tools. Escape closes the panel.
Acquisition, funnel, measurement, automation and competitor intelligence usually live in separate tools. These six layers are the same loop, cut down for the homepage.
Meta, TikTok, Google and Apple Search Ads run against payback and ROAS targets, with scale and stop rules written down before money moves.
Landing page, checkout and paywall send each step as an event the ad platform's optimizer can learn from.
Tracking and attribution tie ad spend to payments, flow into one data layer and surface in dashboards you can trust.
Reporting, alerts, pacing and test logistics run on schedules and rules. Agents draft proposals; a person approves them.
Public ad libraries, store pages and pricing are monitored on a schedule where official sources cover your markets, and turned into briefs.
One review rhythm: kill what fails, scale what pays back, log what you learned, and feed it into the next round of acquisition.
Paid acquisition splits into three routes from the same channel set. Open a route to follow the identifier from click to revenue. App to app is the store path. Web to app and web to web are web funnels, then a cohort view in BI.
Paid channels
Paid traffic uses a store path, a web-to-app path, or a web-to-web path. The stages below are structure, not conversion rates.
Ad to payment to web product
Ad to store to in-app purchase
Web payment, then into the app
Quiz, onboarding and paywallA visitor moves from quiz to onboarding to paywall. Each step sends an event the ad platform can learn from, and the purchase goes back as a server-side event. Event names are illustrative.
On the web path these steps sit between the click and the payment. Onboarding here means the value steps that explain the offer before payment. Each step can send an event the ad platform can learn from.
Collect answers and move the visitor toward checkout.
quiz_completeValue steps that explain the offer before payment.
onboarding_completePrice and checkout on the web.
purchaseOne data layer joins spend and payments. Dashboards show CAC, LTV, ROAS and payback by cohort. The figure is a structure sketch, not a results table.
Agents read data and draft proposals. A person approves each budget change before it reaches an ad account.
Start with a fixed-scope audit. It ends in a ranked plan, so you see what a build involves before you commit.
Card data stays inside Stripe. Competitor monitoring reads public data under platform terms.
An engagement can start with an audit, move to a build and continue as a run. Each step also works alone.
A fixed-scope review of your spend, tracking, funnel and reporting. You get a ranked list of gaps and the order in which to close them.
Tracking, BI, web funnels and automation built around your stack and handed over with documentation, or built and run together.
Fractional or full-time ownership of paid acquisition and its economics, hands-on in the ad accounts and accountable to your revenue numbers.
Vlad Yasinski is a performance marketer and growth consultant based in Warsaw, Poland, with 10+ years of paid acquisition experience. He took two apps to Top-1 in their US App Store categories and builds the analytics, web funnels and automation around paid acquisition.
Full-cycle marketing systems for app and subscription businesses: paid acquisition, web funnels with server-side tracking, analytics and BI, automated reporting and alerts, and competitor monitoring on public data, connected into one loop.
Two apps at Top-1 in their US App Store categories (InPulse in Health & Fitness, Themify in design and graphics), Facebook and TikTok budgets of up to $1.5M per month, web funnels and BI built from scratch, and an unprofitable app portfolio rebuilt to positive unit economics for a client under NDA.
Founders and growth leads of app, subscription and web-funnel businesses that need someone to build the measurement and automation layer and run paid acquisition on revenue.
Start with an audit, then build the system, then run it together, as a project, fractional or full-time. Contact: insk.ma@gmail.com, Telegram @ua5er, or the form at roimobi.com/contact.
Warsaw, Poland, working remotely. English, Polish and Russian.
Agents read your data and draft proposals. Each budget change waits for a person's approval before it reaches the account. Write access to an ad account is a separate decision.
Cost depends on the size of your stack and how much routine you want automated. Start with the audit: a fixed scope that ends in a ranked list of gaps and the order to close them. You see what a build involves before you commit.
Card data stays inside Stripe, and the system reads purchase events and reports. Competitor monitoring reads public ad libraries and store pages under platform terms, and work that touches personal data is scoped under GDPR, with a data processing agreement where needed.
Tell me about your app and where growth is stuck. You can start with an audit, then move to a build and a run. Pick the step that fits.