When mobile marketers think about scaling growth, ad networks are often the first stop — they promise vast reach across apps, simple setup, and automated buying. But the reality is far more complicated.
For one, fraud is rampant. Malicious bots now account for more than a third of all internet traffic, inflating ad costs and corrupting performance data.
At the same time, attribution on iOS is shifting. Apple’s AdAttributionKit introduces overlapping conversions and new configuration options that require close attention to avoid signal loss.
To help you get the most out of mobile ad networks, we’ve put together a guide that breaks down:
- What mobile ad networks are
- Limitations you should know about
- Strategies you need to protect spend and maximize ROI
What Are Mobile Ad Networks? Foundations and Limits
Mobile ad networks are marketplaces that broker inventory between advertisers and app publishers across formats like banners, interstitials, native, and rewarded video placements. The main appeal is centralization — networks are a one-stop shop to get access to thousands of apps. Plus, you don’t have to manage those direct publisher relationships.
Typically, mobile ad networks have a few core elements:
- Automated bidding to place ads
- Contextual and behavioral targeting to maximize the chances of conversion
- Creative optimization, using device-level data to guide which ads get served to a specific audience
Sounds bulletproof, right? Not quite. There are still some risks to using mobile ad networks, including:
- Fraud exposure. As we mentioned up top, bots represent a significant chunk of traffic. Ad networks typically have protections in place to prevent bots from eating up your ad budget, but it’s important to be aware of this possibility.
- False attribution. Like we touched on, the iOS AdAttributionKit (which replaced SKAdNetwork), supports overlapping conversions, configurable attribution windows, cooldown periods, geo-level postbacks, and enhanced in-device testing. While this is great for flexibility, it also opens the door to under-crediting or over-crediting certain campaigns, obscuring true ROI.
Mobile ad networks are only as strong as their fraud defenses, attribution design — and the filters and reporting you layer on top. Without those guardrails, your campaigns can quickly turn into wasted spend.
Performance Realities: Engagement, CTR, and Attention
While mobile ad networks have solid reach, the real challenge is cutting through the noise.
Research from HubSpot a few years back showed that 91% of people agree that ads are getting more intrusive. And Nielsen’s 2023 Consumer Survey Report found that 64% of consumers intentionally take actions to avoid ads on free, ad-supported video services.
That reality carries over to mobile, too. If the ad feels disruptive, it’ll be ignored.
Formats make a big difference. Native ads that align with in-app content or rewarded video placements (where users opt to watch in exchange for game credits, premium features, or extra content) outperform standard banners. These value exchange experiences feel less like interruptions and more like part of the app itself.
The other lever you have is creative. Test multiple variations of ads and measure the down-funnel impact (click-through rates don’t necessarily mean consumers bought anything). When attention is scarce, it’s even more important to find your sweet spot: the right format and the right creative.
Fraud and Waste: Install and Attribution Integrity
Fraud is a structural cost driver in mobile ad networks, and it has only increased over time. Back in 2022, AppsFlyer found that fraudulent installs had jumped by over 40%. With how quickly bad actors can adapt, fraud defense can’t be a one-time setup.
Though bot behavior is always changing (and can’t be fully eliminated), there are things you can do to at least mitigate the damage. Consider adding the following to your mobile ad network strategy:
- Pre-bid invalid traffic screening to remove suspicious impressions before they’re ever purchased, keeping wasted spend from entering your funnel.
- Device-level anomaly detection to spot unusual engagement patterns, like installs happening at impossible speeds or click-to-install ratios that don’t reflect a real human’s behavior.
- Allowlists and blocklists so spend is concentrated on trusted partners and low quality supply sources are systematically excluded.
- Post-install validation to confirm downstream actions (logins, purchases, subscriptions) are being done by actual users — not scripts or hijacked devices.
It’s not just about preserving your budget, it’s about diluting your whole ad strategy. Bots inflate installs, skew attribution, and mask genuine performance signals. That means campaigns get optimized toward fake traffic. As real installs shrink in comparison, your cost per install (CPI) rises because spend is spread across invalid conversions that never translate into revenue. In short, you end up paying for noise instead of growth.
To protect your spend and your brand, you need to treat fraud prevention as a continuous discipline, not an afterthought.
iOS Attribution Is Evolving: What Marketers Need
Fraud isn’t the only hurdle to getting value from mobile ad networks. Attribution frameworks are shifting, too.
Apple introduced AdAttributionKit in iOS 18.4, and it brings several upgrades over SKAdNetwork (like we’ve already discussed):
- Overlapping reengagement windows let multiple campaigns remain eligible when they occur close in time.
- Configurable attribution windows give marketers control over how long a campaign is eligible for credit.
- Cooldowns prevent duplicate reporting.
- Conversion tags allow you to update postbacks later if the conversion value changes.
Practical Implications
When you configure attribution, think carefully about how your funnel works. For example:
- A utility app with fast conversions may perform best with shorter attribution windows.
- A subscription product might need longer ones to account for delayed conversions.
Misalignment risks undercounting reengagements or double counting repeat conversions.
Deterministic vs. Probabilistic
Deterministic attribution (matching with device IDs or known identifiers) is increasingly constrained under ATT, covering only opted-in traffic. To fill in the gaps, you’ll need to supplement with probabilistic models (which use statistical inference).
Many marketers choose to run a hybrid model, anchoring on the deterministic data where possible, and then using probabilistic models to guide remaining budget allocation across iOS traffic.
Bottom line: don’t just stick with default settings. Take the time to fine tune each aspect of AdAttributionKit to keep a reliable view of ROI in an increasingly privacy-first world.
When Mobile Ad Networks Work Best
Mobile ad networks aren’t the right solution for every campaign, but they can be highly effective in specific situations:
- When you’re looking for growth. App install campaigns, in particular, benefit from the reach and automation networks provide, but only if you pair that reach with fraud defenses, creative testing, and attribution guardrails. Without those, scale just multiplies inefficiency.
- You use native placements and rewarded video ads. As we’ve covered, these typically outperform banners in both engagement and conversion.
- Some geographies and verticals are simply better suited for mobile ad networks. ATT opt-in rates vary widely, as does publisher quality. Marketers can gauge this by reviewing MMP data (from a platform like AppsFlyer, Adjust, or Branch), Apple’s transparency reports, and their own regional benchmarks to identify where contextual signals and consent rates make optimization more reliable.
Campaign Planning and Setup: ROI-Focused Foundations
If we said it once, we’ll say it again: effective mobile ad campaigns start with a solid foundation that measures performance accurately and protects against fraud. And that begins with a proper targeting architecture.
Use contextual filters and supply quality criteria as your baseline. From there, layer in first-party data where possible, and consider retargeting campaigns (if it respects privacy standards).
A sound creative system is another component. It needs to be designed for rapid iteration across all kinds of ad formats. Frequent testing makes it easier to identify which combinations of message, design, and placement drive the outcomes you want.
Budget discipline matters as well. Allocate phased test budgets for each network and format. Keep experiments isolated so results aren’t muddied by overlapping spend. That way, you can double down on what’s working and cut off underperforming supply quickly.
If you wait until fraud shows up in reporting, you’ve already wasted budget. Make sure proper fraud controls are in place from day one.
Data-Driven Optimization: Testing, Bidding, and Supply
Mobile ad networks generate a massive flow of data, but you’ll need to separate the signals from the noise. Some ways to do this include:
- Continuous testing. A/B tests on creative, format, and placement tied to down-funnel conversion metrics rather than vanity metrics (like click-through rate).
- Bidding strategy. Shift spend to high quality supply and formats with reliable postbacks. Frequency caps and viewability gates increase the chances you’re paying for real attention, not inflated impressions.
- Signal hygiene. AdAttributionKit postbacks, MMP reporting, and your own internal data don’t always align. Reconciling those differences is critical — sudden anomalies could mean fraud is slipping past filters or that your attribution settings don’t quite match funnel timing.
Measurement and Reporting: Privacy-Centric Attribution
Privacy rules are constantly evolving, and today’s performance marketers have to account for those changes — both in their campaign setups and their reporting.
Start by defining and tracking some core KPIs:
- Blended CPI/CAC. Look at acquisition costs across all channels together, not just at the network level. If your blended CPI is rising faster than network-reported CPI, that’s a red flag for fraud leakage or poor supply quality.
- Validated Installs. Only count installs that pass bot filters and show real user activity, such as an app open or completed onboarding. This metric acts as your clean baseline for optimization.
- Post-Install Actions. Registrations, purchases, or subscriptions tell you whether installs translate into meaningful engagement. Tracking these downstream events keeps you from optimizing to empty installs.
- Retention. Day 1, Day 7, and Day 30 retention curves show how sticky your acquired users are. Strong retention signals validates whether you’re bringing in the right audience.
- Lifetime Value (LTV). Project the revenue a user generates over their entire relationship with your app. Use cohort analysis by channel, creative, or campaign to see which sources drive customers worth keeping.
- Incrementality. The hardest metric, but the most telling. It measures the lift caused by your ads compared to what would have happened organically. Holdout groups or geo splits can reveal whether you’re paying for growth or just capturing it.
Audience and Channel Mix Considerations
It’s important to remember that mobile ad networks are part of a larger channel mix, and performance depends on how well they align with your audience.
Gen Z — which is projected to grow to $12.6 trillion in spending power by 2030 — spend heavily on mobile-first experiences. But they’re also quick to tune out ads that feel irrelevant or intrusive. That means that native and rewarded formats that feel contextual and offer true value are even more important to nail when targeting this group.
Balancing your channel mix is just as critical. Mobile ad networks should be combined with other contextual buys, retail media investments, and privacy-safe reengagement tactics. This diversification spreads risk, strengthens measurement, and provides multiple touchpoints with high-value audiences.
The smartest marketers aren’t choosing mobile ad networks instead of other channels. They’re using them in addition to other channels that they already know work — or that they predict will keep up as consumer expectations and regulatory change.
Scale Doesn’t Always Mean Results
Mobile ad networks are a great way for performance marketers to reach a wide audience — but only if they’re willing to pay close attention to put in the work. Marketers seeing the best outcomes are doing three things consistently:
- Choosing formats that demand attention, like native and rewarded ads.
- Configuring AdAttributionKit with precision, aligning windows, cooldowns, and tags to their funnel.
- Treating fraud prevention as always-on maintenance
That may seem overwhelming, so just start small. Once you’ve worked out the right kinds of ads and guardrails, mobile ad networks can become a sustainable driver of ROI.
Frequently Asked Questions About Mobile Ad Networks
Q: What is a mobile ad network?
A: A mobile ad network is a platform that connects advertisers with publishers who have ad inventory inside their apps. Instead of negotiating individual deals, advertisers can tap into hundreds or thousands of apps through one integration. Networks handle bidding, targeting, and creative placement across formats like banners, native ads, interstitials, and rewarded video. The appeal is scale and simplicity, but performance marketers need to watch for quality. Publisher transparency is often limited, and fraud controls vary widely between networks.
Q: Why does fraud matter so much?
A: Fraud directly erodes ROI. Malicious bots now compose over one-third of web traffic, and can mimic installs, clicks, and even in-app events. Besides the fact that marketers are paying for these fake impressions and clicks, they are putting their reporting in jeopardy. Fraud contaminates attribution data, making it harder to tell which channels or creatives are driving growth. Without pre-bid filters, device-level anomaly detection, allowlists, and post-install validation, you risk optimizing toward fake performance instead of real customer behavior.
Q: How has iOS attribution changed?
A: Apple has phased out SKAdNetwork in favor of AdAttributionKit. Now, marketers now have tools like overlapping re-engagement windows, configurable attribution windows, cooldowns to prevent duplicate credit, geo-level postbacks, and in-device testability. While that gives them more granular control over how they measure success, the setup is tricky, and misconfiguration can cause overcounting or signal loss. To avoid gaps, marketers need to align attribution windows to their sales funnel and rigorously test their setups.
Q: How common is install fraud?
A: In the second half of 2022, there was a 40% surge in fraudulent installs, driven by device farms and bots that fake app activity. And fraud doesn’t even stop at the install. It extends to simulated post-install events that make fake users look “active.” This drains budgets and poisons optimization models, since algorithms may shift spend toward sources that appear high-performing but are fraudulent.
