One platform earns much less per impression.
iOS and Android users see the same content, so a large price gap usually points at the setup, not the audience. I check how ads are requested, rendered and refreshed on each platform.
Development / Ad revenueMore revenue from
More revenue from
the ads you already show.
I find where an app’s ad setup loses money: wasted requests, ads that never render, weak demand, and a platform paid less than it should be. Then I fix it in the code and the configuration, and measure the result.
Results / A large consumer app
The same ad slots. Much more money from them.
Two months of my own work on the app’s ads, on iOS and Android. The client stays confidential.
iOS ad price (CPM) after I rebuilt how the app loads ads. Now on par with Android.
3×
Header-bidding revenue on Android: from €1.2k to €3.7k a month.
~€30k
Estimated extra iOS revenue a year from the higher ad price.
When to bring me in
Where ad revenue usually leaks.
More ad slots, but revenue stays flat.
New placements can lower prices and hurt the experience. First I look at fill, render rate, viewability and the demand competing for each impression.
Header bidding is set up, but barely contributes.
Coverage, timeouts, bidder configuration and consent handling decide whether bidders actually win. I find where that demand is lost.
Users complain about the ads.
Sound from ads scrolled past, empty gaps, a feed that reloads by itself. These cost retention and revenue at the same time, and the cause is usually in the code.
Relevant work
The experience behind this work.
I’m Alex Severianov, founder of X91 Tech. These cases describe my own contribution in existing product teams.
Explore →
Rebuilding the ad integration
I built consent-based loading for Google Ad Manager and other ad providers, added bidding, and fixed request, configuration, and display issues.
Explore →A blank feed, white ads, and four separate defects
I traced failures across SwiftUI, an ad SDK, and bidder configuration, contained the immediate ad failure, and fixed the underlying code.
Explore →See what an ad revenue engagement looks like
The ad revenue sample shows the format of the findings and the implementation report. It uses a fictional company and synthetic data.
Working together
From the numbers to the fix.
Read the numbers
We look at the ad server data by platform, format and placement: price, fill, render rate, viewability and demand sources. I find where the gap is.
Trace it into the app
I inspect how the app requests, loads and displays ads, and how the SDKs and bidders are configured. Most of the money is lost between those layers.
Fix, test and measure
I implement the changes, run them as A/B tests where possible, and measure revenue and user experience before rolling out.
What you get
A diagnosis of where ad revenue is lost, implemented fixes in the app and the ad configuration, and measured results. Scope and price are agreed before paid work starts.
Before we start
Questions about the work.
Do we need to replace our ad stack?
No. I work with the setup you have, such as Google Ad Manager, header bidding and mediation, and improve how it is used. New demand partners are added only when the data supports it.
Will more revenue hurt the user experience?
It shouldn’t. In the work above, users stopped hearing sound from ads they had scrolled past and empty ad gaps disappeared. Ads that render properly are also worth more.
What should I send first?
Your platforms, ad formats and placements, what you use for ad serving and bidding, and how revenue has moved recently. Rough numbers are fine.
Let’s talkBring me
Bring me
the problem.
An app that needs building. A migration that needs someone to own it. Numbers that don’t make sense. A product decision your team can’t resolve. Or the thing your team is most sure about. Tell me what’s happening. I’ll tell you whether I’m the right person, how I’d approach it, and what the work would cost.
Email Alex ↗[email protected]You bring the context. I take the work seriously.
Not sure what you’d get? See sample reports →