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Mobile advertising networks connect advertisers that want app users with developers that have ad inventory. When an eligible placement needs an ad, an SDK sends a request containing contextual and policy signals; one or more demand sources compete to return a creative, and the developer earns money when the resulting impression, click, install, or other contracted event qualifies for payment.
The metrics that explain the result are related but not interchangeable: eCPM is earnings per 1,000 impressions, fill rate is the share of ad requests that receive an ad, and mediation lets multiple demand sources compete for each opportunity. A high eCPM with weak fill can earn less per request than a lower eCPM with reliable fill, so revenue decisions should use both measures plus latency, user experience, privacy compliance, and retention.
What a mobile advertising network does
A network is an intermediary between advertiser demand and the ad space inside an app. The developer creates an ad unit, places it in the app’s code, and configures an SDK. When the app reaches that placement—for example, when a screen loads or a user finishes a level—the SDK sends an ad request.
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The request can include signals needed to select and price an ad, such as the ad format, app and placement identifiers, device and operating-system information, geography, consent state, and policy-related data. The exact signals depend on the SDK and the applicable privacy rules. Networks and exchanges evaluate the opportunity against advertiser targeting, brand-safety, and buying rules.
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2. Demand sources return an ad or no fill
A source can return a creative and price, or it can decline because no eligible campaign is available. The selected ad is downloaded and displayed according to the platform’s measurement rules. A request that receives no eligible response is an unfilled request; it does not become an impression merely because the SDK asked for one.
3. The qualifying event produces earnings
An impression is counted when the returned ad is displayed under the platform’s rules. Depending on the buying model, payment can also depend on a click, install, or another interaction. The advertiser pays according to its contract, the network or mediation platform accounts for its fee and any intermediary deductions, and the remaining publisher earnings are reported to the developer.
eCPM, fill rate, match rate, and show rate
These metrics describe different stages of the delivery chain. Mixing their denominators is one of the fastest ways to misread a network report.
| Metric | Definition or formula | What it tells you |
|---|---|---|
| eCPM | (Total earnings / impressions) × 1000 |
The observed or estimated earnings associated with 1,000 impressions. |
| Fill rate | ads delivered / ad requests |
How often a network delivers an ad when the app requests one. |
| Show rate | impressions / matched requests |
How often a matched ad is actually displayed. |
| Revenue per 1,000 requests | Approximately eCPM × fill rate, with fill expressed as a decimal |
The yield of requests, not just the impressions that were filled. |
Use the denominator supplied by the platform. “Request,” “matched request,” “impression,” and “show” can represent different events, and a dashboard may apply additional filtering or delayed adjustments. Compare eCPM only across the same format, country mix, platform, and time window; otherwise a change in traffic composition can look like a pricing improvement.
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Why fill changes the meaning of eCPM
Suppose one configuration produces a $1 eCPM and an 85% fill rate. Its approximate revenue per 1,000 requests is $0.85. Another produces a $2 eCPM but only 30% fill, yielding about $0.60 per 1,000 requests. The second source wins on impression price but loses on request-level revenue.
This calculation is an approximation. Actual results can diverge because of show rate, latency, invalid-traffic adjustments, consent restrictions, rounding, and the platform’s precise accounting rules. For business decisions, track revenue per request and revenue per daily active user alongside eCPM.
How mediation decides which source gets an opportunity
Mediation is the control layer between the app and several ad networks or exchanges. It receives the app’s request, evaluates available demand, and chooses the source that is expected to produce the best eligible outcome while respecting the configured ordering and policies.
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In a waterfall, sources are ordered by an eCPM value. That value can be manually configured, observed from past performance, or supplied by an optimization system. The mediation layer calls the highest-ranked source first. If it does not fill, the request proceeds to the next source, and so on.
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The ordering is not a guarantee that the first source will return an ad. Availability, targeting, consent, campaign budgets, and network latency determine whether the chain reaches the next source. A manually stale eCPM can therefore place a weak source above a better one, while an aggressively high floor can leave the entire chain under-filled.
In-app bidding
With bidding, participating sources submit bids in parallel for the same opportunity. The winning bid is inserted into the mediation ordering according to its eCPM, after which the platform applies its normal eligibility and delivery rules. Parallel bids can reduce dependence on manually maintained rankings, but they still require compatible adapters, sufficient demand, and accurate reporting.
Hybrid setups
Many implementations combine bidders with waterfall-only sources. Bidders compete in the auction, while other sources are represented by configured eCPM entries. The resulting chain can include both a real-time bid and a historical or manually set value, so compare realized revenue rather than assuming that every displayed eCPM is a live bid.
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An eCPM floor is the minimum price a publisher is willing to accept for an opportunity. Raising the floor can improve the price of impressions that clear it, but it is likely to reduce fill because more bids are rejected. A floor should be judged against total revenue per request or per active user, not against eCPM in isolation.
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How to test a floor
- Separate tests by geography, ad format, platform, and meaningful audience segment; demand differs substantially across those groups.
- Change one variable at a time and keep the test period long enough to capture normal traffic variation and seasonality.
- Record requests, matched requests, impressions, show rate, revenue, latency, and retention for each configuration.
- Lower or remove a floor when the increase in eCPM is outweighed by lost fill and request-level revenue.
Optimization systems also need enough traffic to estimate performance. Sparse traffic can leave a source in a pending or low-confidence state, so a short period with few requests should not be treated as proof that a network is poor.
What percentage do ad networks take?
There is no single current percentage that applies to every mobile ad network transaction. The advertiser may pay for an impression, click, install, or another contracted outcome. The network or mediation platform then applies the fee and any contractual deductions before reporting publisher earnings.
The applicable share can vary by product, demand source, country, contract, and whether another intermediary is involved. Public documentation for a platform may explain that publishers are paid for clicks, impressions, and other interactions without establishing one universal rate for every first-party and third-party transaction. Use the terms for the specific product and account rather than quoting a generic “the network keeps X%” figure.
How to compare networks and mediation platforms
A useful comparison treats monetization as a system, not a leaderboard sorted by eCPM.
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| Area | Questions to answer |
|---|---|
| Realized yield | What are revenue per request, revenue per impression, and revenue per daily active user after unfilled opportunities and adjustments? |
| Availability | How do fill or match rate and show rate vary by country, format, platform, and season? |
| Demand mechanics | Does the source support bidding, waterfall placement, floors, and reliable optimization? |
| Format coverage | Are banner, interstitial, rewarded, app-open, native, and rewarded-interstitial placements supported for the target countries? |
| Operations | What SDK size, latency, crash risk, adapter maintenance, reporting detail, and debugging workload will the integration add? |
| Policy and privacy | What consent-management work, app-ads.txt or supply-chain controls, brand-safety tools, and ad-quality review are required? |
| User experience | Can you control frequency, timing, accidental clicks, reward rules, and the effect on retention? |
Format support, bidding availability, automatic data collection, and manual eCPM requirements can differ by network and country. Confirm those details in the current integration documentation before adding an adapter. For example, Google demand in AppLovin MAX requires a valid AdMob account, and MAX documentation recommends using new placement IDs for accurate MAX reporting.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical implementation sequence
- Instrument the baseline. Log requests, matched requests, impressions, show rate, clicks, revenue, latency, and crashes by ad unit, country, operating system, and format. Include consent state where privacy rules permit and make sure event timestamps can be joined across the app and mediation reports.
- Start with a focused demand set. Use one primary network and a small group of partners whose formats and geographies match the app. Avoid adding adapters merely to increase the count; every adapter adds binary size, maintenance, and another policy surface.
- Integrate mediation adapters. Verify SDK versions, initialization order, placement identifiers, privacy disclosures, consent signals, and test-ad behavior before sending production traffic. Confirm that the mediation dashboard and in-app events use the same ad-unit and placement mapping.
- Run a controlled baseline and comparison. Keep the original configuration available, then compare a mediation setup with it using revenue per request and retention guardrails. Hold traffic allocation and major app changes steady so a release or seasonal spike is not mistaken for a mediation gain.
- Adjust gradually. Change floors and waterfall order in small, documented steps. Record the date, segment, expected effect, and observed change in fill, show rate, latency, and revenue.
- Remove net-negative sources. Retire a source when it adds latency, poor creative quality, policy risk, crashes, or operational cost without improving realized yield or user outcomes.
AppLovin recommends beginning with at least six networks with strong global demand in addition to AppLovin when establishing a baseline. That is vendor guidance, not a universal requirement; a smaller, well-instrumented set can be more appropriate for an app with limited traffic or a narrow geography.
Diagnosing low fill and disappointing revenue
Low fill rate
- Check whether the denominator is requests or another event, then segment by country, format, platform, and consent state.
- Review floors: a threshold that is too high can reject otherwise eligible demand.
- Verify adapter initialization, placement IDs, account status, privacy signals, and app-ads.txt or related supply-chain requirements.
- Look for demand seasonality or a format-country combination with little advertiser competition.
High eCPM but low earnings
- Calculate eCPM × fill rate to estimate revenue per 1,000 requests.
- Check show rate and latency; a matched ad that is never displayed cannot produce the same value as a delivered impression.
- Separate invalid-traffic adjustments and delayed reporting from the initial estimate.
- Measure revenue per daily active user and retention, because an intrusive placement can reduce future sessions.
Revenue falls after adding mediation
- Compare the same countries, formats, and operating systems against the baseline rather than comparing two different traffic mixes.
- Inspect waterfall order and bidder participation for stale values or failed adapters.
- Check whether extra SDKs increased startup time, crashes, or ad-loading latency.
- Review creative quality, frequency caps, accidental-click rates, and reward delivery; a nominal yield increase is not useful if users leave or report the app.
What the scale figures do—and do not—mean
Google AdMob reported nearly 1 million advertisers and 200 billion ad requests per month globally in 2017. Those figures describe the scale reported at that time and should be treated as historical context, not as a current market-size estimate.
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More generally, no published eCPM, fill rate, or revenue-share figure should be treated as a promise. Country mix, format, device, consent state, demand competition, seasonality, placement quality, and reporting adjustments can all change the result. The most defensible forecast comes from the app’s own segmented request and revenue data, measured over a representative period.
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