If there’s anyone who can vouch for what it’s like to work in ad tech, it’s Alexander Zhitlukhin. He’s been part of the Appodeal team for over ten years now, starting back in 2015 as a linear Android Engineer when the company was only 30 people. Much has changed since then, both in terms of Alexander himself, who has climbed the ranks to become Chief Technology Officer, and the mobile ad tech industry as a whole, which is rapidly becoming increasingly reliant on machine learning technology.
Today, Alexander works closely with his dedicated team to identify ways to leverage artificial intelligence to bolster his work. Below, he shares details about Appodeal’s machine learning-powered Mobile Growth Platform and discusses how it addresses the most pressing challenges facing mobile marketers.
Fact 1: Appodeal has built a platform that enables app developers to create, innovate and grow
Picture this: you’ve spent hours refining your mobile app until it’s this incredibly polished work of art. Whether you're a rapidly expanding scale-up or an established larger company, at this point, either you or your team would typically have to change hats to become data scientists or ad tech experts to grow your new product. Just imagine how much easier it would be if there were a single app that could automate all your monetization, user acquisition, segmentation, and optimization for you.
Thankfully, it’s not just a dream. Using the power of artificial intelligence and machine learning, we’ve developed a Mobile Growth Platform that improves individual components like ad mediation or campaign optimization and brings together the many moving parts of the mobile market into a more cohesive whole. The platform has helped Appodeal rank among the top 5 ad SDKs worldwide, according to the Q1 2025 Global Mobile App Ad SDK Market Share Rankings Reports by Pixelate.
Fact 2: And that platform is also proving to be Alexander’s biggest challenge…
Building such a holistic platform required forcing several building blocks, all of which are evolving independently of one another, into a single cohesive system. As you can imagine, this was no small feat. Combining sophisticated ad networks, ad mediation, BI, and DSP (Demand-Side Platform) technologies is inherently difficult, not just from an engineering perspective but also in terms of communication, as it requires close collaboration across the organization.
Nevertheless, the benefits outweighed the difficulties involved. For example, bringing all key systems together within one unified platform – monetization, UA, analytics and engagement – means data is no longer siloed. Insights start with great analytical tools like our BI, which results in better decision-making and more consistent performance. Likewise, having one platform equals less operational overhead and improved efficiency across the board.
Fact 3: Appodeal is embracing transparency and open source
The biggest issue in this industry is the prevalence of black box solutions, where you log in to a mysterious thing that somehow alleviates your problems. It means you can't see the actual value of your impressions, what your ad networks are bidding or how much intermediaries are taking as fees. Ultimately, this could mean you’re unknowingly accepting lower eCPMs (effective Cost Per Mille) than you might be able to otherwise achieve.
That’s why our Mobile Growth Platform is being built with fair ad mediation front-of-mind, so you have full access and visibility over your user acquisition. So far, the feedback from users has been very positive. On the one hand, tech enthusiasts see the move to open source as an important step in the right direction for software engineering and product development. Meanwhile, big companies appreciate the improved clarity because it reduces their financial risk, especially where longer-term partnerships are concerned.
Fact 4: Machine learning and other new technologies are making ad tech careers even more exciting
The main reason I’ve stayed in ad tech all these years is because it’s so dynamic. There’s no real waiting around in this industry because we can track almost everything instantly: you deploy something, wait a few minutes to see the impact on revenue, then jump right back into tweaking the parameters.
Machine learning will only enhance that feedback loop, which is why ad tech is the most exciting field for data scientists and product managers right now. For example, we’re working to shorten the feedback loop further by empowering our data scientists to run campaigns directly in production with real clients. This means they no longer have to wait on others for approval or support – they can launch campaigns, gather data, extract insights and run the next experiment all on their own.