Apple Search Ads Manager for iOS subscription app

Hello! I have reviewed your assignment and believe that I can successfully complete it. I would be happy to collaborate, please write to me personally for further details.

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Hello!

I have practical experience working with performance advertising and analytics (Google Ads, conversion funnel, bid optimization). I understand the logic of Apple Search Ads, the structure of campaigns, and the importance of negative keywords.

I have worked with subscription models, understand the user journey from trial to paid, and focus on ROAS / payback, not just CPI.

I am ready to take on keyword research, build campaign structures, launch, and optimize during the first month. An example of results (without names): campaign optimization focused on conversion led to a decrease in subscription cost and achieving positive ROAS after the testing period.

I would be happy to discuss the details.

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Hello! We are ready to take on the project. The tasks are clear, and we have experience with subscription models. To ensure we achieve a return on ad spend (ROAS) rather than just a report on clicks, I want to highlight the technical challenges we will face and how we will address them.

Challenge 1: "Blind" Optimization

Problem: Often, the data in the Apple Search Ads dashboard shows only installations but does not indicate who actually paid for the subscription. Optimizing for "cheap installations" is a path to budget waste.

Our solution: We will spend the first 2-3 days deeply linking ASA with your analytics (RevenueCat/AppsFlyer). I will set up Python scripts that will extract data on actual payments. We will see the return on investment for each keyword and disable those that do not generate revenue.

Challenge 2: Market and Auction Dynamics
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Problem: Bids in ASA fluctuate constantly. If checked manually once a day, you can either drop out of the results or overpay.

Our solution: I will deploy an automatic bid monitoring system (in a Docker container on my server). The script will monitor metrics 24/7 and adjust bids based on the target ROAS we set. This will save about 15-20% of the budget.

Challenge 3: "Garbage" Traffic from Apple

Problem: Apple often mixes in broad matches that do not convert into subscriptions.

Our solution: During the first month, we will conduct aggressive cleaning of Negative Keywords. I will use my methods for collecting semantics to exclude non-target queries right from the start and then filter new ones daily.

Challenge 4: Conversion of the Product Itself

Problem: If the payment screen (paywall) in the app does not "sell," even perfect advertising will result in a loss.

Our solution: We will conduct an audit of the trial-to-paid funnel. If we see that the traffic is high quality but there are no purchases, I will provide recommendations for optimizing the paywall to improve overall profitability.

I am ready to discuss technical access and get started. What do you say?

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Hello! Having studied your project with great interest, I am ready to start working on it. Let's discuss the details to achieve the best result.

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