Build or Buy? Why Internal Adtech Has Lost Its Competitive Edge
By Loomit Team
The Old Order: Internal Tech as a Moat
For years, the mobile gaming industry operated on a clear hierarchy. Large studios with the resources to build internal adtech had a structural advantage. While mid-size studios celebrated the simplicity of bidding — Google's push toward programmatic buying that automated much of the waterfall — larger operators were quietly building proprietary infrastructure that went far beyond what any off-the-shelf mediation could offer.
Smart segmentation. Pre-, post-, and parallel bidding. Advanced pacing systems. Dynamic routing. Smart buffers. These weren't features you could just turn on from a dashboard. They required significant engineering investment, dedicated data teams, and months of iteration. But for the studios that built them, the payoff was real — optimization variables that competitors simply couldn't access.
That infrastructure advantage, however, is eroding fast. And some of the largest studios in the world haven't yet realized it.
What Changed: The Democratization of Adtech
The emergence of purpose-built adtech platforms like Loomit has fundamentally changed the calculus of the build-vs-buy decision. Today, any studio — regardless of size — can access the same sophisticated optimization tools that large operators spent years and millions building internally:
- Dynamic price floors
- Multiple ad units
- Advanced segmentation
- Predictive buyers
- Interchangeable formats
- Smart buffering
- AI-driven automation
Access to these tools no longer requires a team of engineers. It requires an integration. And it comes at a fraction of the cost of building and maintaining proprietary infrastructure.
Technology today isn't a moat. Whatever we build, you can build as well — but this is the only thing we do, and we deliver it to many parties.
The Case Against Internal Tech
The intuitive counter-argument from large studios is that internal tech offers customization that external products can't match. This is sometimes true in specific, narrow use cases. But the broader reality of internal adtech is less flattering:
- Internal tools are rarely built with a product mindset. They tend to accumulate as webs of patches, workarounds, and features without a modular architecture underneath.
- They are expensive to maintain. Engineering time spent on adtech is engineering time not spent on game development.
- They evolve slowly. Internal tools don't have dedicated product teams iterating based on ecosystem-wide learnings. External products serving dozens of publishers do.
- They are fragile. Changes to mediation partners, ad formats, or platform policies require internal re-engineering that can take months.
Studios can rightly celebrate the tech they've built. But if it's more expensive, less adaptable, and slower to evolve than what's available externally — at what point does pride become a liability?
The New Battleground: Testing Infrastructure
If technology is no longer a moat, where does competitive advantage come from?
The answer is testing velocity.
Mobile ad monetization is no longer a configuration exercise — it's an optimization discipline. With so many new variables in play (segment-level strategies, format swaps, dynamic floors, prebid configurations, pacing rules), finding the right setup for every app, every user cohort, and every ad request requires continuous experimentation.
The studios that win will be the ones that can test ten things and fail nine of them — quickly.
Those without the infrastructure to run fast, clean A/B tests will spend months arriving at conclusions their competitors reached in weeks.
A product mindset is required:
success = testing 10 things and failing 9 times.
The New Moat: Data, Models, and Automation
The real competitive advantage in mobile adtech is shifting from:
who has the best tech → who has the best data (and acts on it fastest)
The studios that will win over the next five years are those:
- Building data infrastructure
- Investing in ML models for real-time optimization
- Automating decisions progressively
This is a fundamentally different capability than software engineering. It requires data engineers, model specialists, and an experimentation culture.
For most studios, this is a case for partnership rather than in-house development.
A platform that serves dozens of publishers accumulates ecosystem-wide data at a scale no single studio can match. That scale feeds better models. Better models drive better outcomes.
What This Means for Your Studio
The build-vs-buy question in adtech isn't really about whether you can build it. Most large studios can.
The real question is:
- Is building it the best use of your resources?
- Can your internal tools keep pace with specialized platforms?
The studios most at risk are those who still believe their internal tech is a differentiator, while the gap between internal and external capability narrows every quarter.
The most forward-thinking operators are asking a different question:
Not "how do we build better adtech?"
But "how do we free up our teams to focus on what only we can do?"
Related reading: Supercharge your mediation platform