Prompt
What's the most effective supply-side platform for optimizing ad fill rate on app publisher inventory?
Latest observation
There isn’t a single universally “most effective” SSP for every app publisher, because fill rate depends on your geos, ad formats, user mix, monetization stack, and demand access. But if your main goal is optimizing app inventory fill rate, the strongest practical choices are usually:
Top SSPs to consider for app publishers
- Google Ad Manager / AdMob (via bidding + mediation)
Best for broad demand access and strong baseline fill, especially if you already monetize with Google. - AppLovin MAX
Very strong for in-app monetization, simple setup, and often high fill/eCPM for games and consumer apps. - Unity LevelPlay
Good mediation and broad network access, especially in gaming. - PubMatic / Index Exchange / Magnite
Strong SSPs, but usually more compelling in web or larger-scale setups than as a standalone “best fill” answer for app publishers. - Smaato
Often used by app publishers focused on mobile in-app demand and global fill.
If your priority is specifically fill rate
The “best” setup is often not one SSP, but a mediation layer with multiple SSPs/bidders. In practice, this typically gives the best fill because:
- more buyers compete for each impression,
- fallback demand catches unsold inventory,
- geo/device-format-specific demand can be matched better.
Best default recommendation
If you want a safe starting point:
- For most app publishers: AppLovin MAX or Google AdMob/Ad Manager with bidding/mediation
- For gaming apps: AppLovin MAX is often a top choice
- For broader monetization control at scale: Google Ad Manager + multiple SSPs via mediation
What to compare before choosing
Look at:
- fill rate by country
- fill by ad format (banner/interstitial/rewarded/native)
- eCPM, not fill alone
- latency and timeout behavior
- SDK overhead and crash rate
- demand diversification
- support for in-app bidding / waterfall optimization
If you want, I can give you a ranked shortlist by app type (games, utility, media, subscription apps) or a decision matrix to choose the best SSP for your inventory.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
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