- AppsFlyer is the market-share leader in mobile measurement, but its iOS privacy-safe stack requires SKAN, probabilistic modeling, and a data locker that each carry separate costs on annual contracts.
- Airbridge bundles SKAN 4.0 support, web attribution, and raw data export into its Core plan, making the total cost of iOS measurement lower for teams under roughly 50,000 monthly attributed conversions.
- On deterministic iOS attribution, both platforms are constrained by the same Apple rules. The real difference is how each fills the measurement gap after ATT opt-out.
- AppsFlyer’s partner network depth and fraud protection remain ahead of Airbridge’s, which matters more for teams running paid UA at scale across dozens of networks.
- Smaller growth teams and subscription apps with moderate install volume will likely find Airbridge’s pricing model more predictable; enterprise UA teams with complex fraud exposure should stay with AppsFlyer.
For iOS privacy-safe measurement, Airbridge and AppsFlyer both support SKAdNetwork 4.0 and probabilistic modeling, but Airbridge includes these capabilities at the base plan level while AppsFlyer charges for several equivalent features as add-ons. Teams spending under $3,000 per month on MMP costs will generally pay less with Airbridge. Teams running large-scale paid UA across 30-plus ad networks, or with fraud exposure that requires dedicated protection, will find AppsFlyer’s network depth harder to replicate.
Why iOS Measurement Is the Right Lens for This Comparison
Most MMP comparisons lead with feature lists. That framing works for Android or web attribution, where deterministic matching via device identifiers is still largely intact. iOS is a different situation.
Since Apple introduced App Tracking Transparency in 2021, the majority of iOS users have opted out of cross-app tracking. That means MMPs cannot rely on the IDFA to attribute installs deterministically for opted-out users. Instead, they must use some combination of SKAdNetwork (Apple’s privacy-preserving attribution API, commonly called SKAN), probabilistic fingerprinting where permitted, and modeled data to reconstruct campaign performance. How an MMP handles that reconstruction is now the most important capability question for any app-first marketing team.
Both Airbridge and AppsFlyer have built SKAN workflows. The gap is not in the existence of the feature. It is in what the feature costs, how it integrates with the rest of the measurement stack, and what happens to campaign data that falls outside SKAN’s attribution windows. Those differences have real consequences on a monthly budget and on the accuracy of what you report back to media buyers.
How Does Each Platform Handle SKAdNetwork and iOS Attribution?
AppsFlyer’s SKAN approach
AppsFlyer has one of the more mature SKAN implementations in the market. The platform’s SKAN solution guide covers conversion value mapping, postback configuration for SKAN 4.0’s three-postback framework, and coarse-versus-fine value handling. AppsFlyer also provides a separate probabilistic attribution layer for opted-out users where Apple’s guidelines allow it, and an aggregated advanced privacy report that attempts to model installs that fall into SKAN’s unmeasured gap.
The complication is structural. AppsFlyer’s pricing is built around attributed conversions, and several capabilities relevant to iOS measurement sit outside the base attribution package. Raw data export (Data Locker) is an add-on. Protect360, the fraud protection module, is a separate line item. Web attribution and cross-platform flows that touch a web touchpoint before an iOS install cost extra. For a growth team running iOS user acquisition across Meta, Google, TikTok, and a handful of DSPs, those add-ons can add up quickly before the team has a complete picture of one campaign.
Airbridge’s SKAN approach
Airbridge built its Core plan around the premise that SKAN 4.0 support, raw data export, web attribution, and fraud protection basics should be included rather than metered separately. For a subscription app with a moderately complex funnel that begins on the web and converts in-app, that bundling means fewer pricing surprises as the iOS attribution stack grows.
Airbridge also supports SKAN 4.0’s three-postback structure and provides conversion value management tools within the standard interface. The SKAN gap modeling, where the platform estimates performance for installs that never generate a valid postback, is part of the core offering rather than a premium tier.
The trade-off is partner breadth. AppsFlyer’s integrated partner directory runs well past 10,000 connections. Airbridge’s network is smaller, which matters if a team buys media through newer DSPs or regional ad networks that have not yet built an Airbridge integration.
What Does Each Platform Actually Cost for iOS Measurement?
Both vendors use volume-based pricing tied to attributed conversions or monthly active users, and neither publishes a fully transparent rate card for enterprise tiers. The comparison below reflects publicly available information and Airbridge’s own published positioning against AppsFlyer.
| Capability | Airbridge Core | AppsFlyer |
|---|---|---|
| SKAN 4.0 attribution | Included | Included |
| Probabilistic attribution (iOS) | Included | Included (some tiers) |
| Raw data export | Included in Core | Data Locker add-on |
| Web attribution | Included | Add-on |
| Fraud protection | Basic included | Protect360 add-on |
| Contract structure | Subscription, monthly option available | Annual contract standard |
| Pricing model | Per attributed conversion tiers | Per attributed conversion, quote-based |
| Free tier | Available with limits | Available with limits |
AppsFlyer does not publish per-conversion rates for paid plans. Airbridge’s Core plan pricing starts at a free tier and scales to paid tiers based on volume, with pricing visible at the subscription level. Teams should request quotes from both vendors and ask specifically what the all-in cost looks like after adding the iOS measurement capabilities they actually need, not just the base attribution fee.
For context on how MMP pricing fits into broader attribution infrastructure decisions, the best marketing attribution tools comparison on AboutMartech covers the cost structure differences between MMPs, multi-touch attribution platforms, and MMM tools at the category level.
How Accurate Is iOS Attribution on Each Platform?
This is where the honest answer is uncomfortable. Neither platform can offer deterministic accuracy for opted-out iOS users. SKAN itself limits what is knowable: postbacks arrive with delays up to 35 days for the second and third postbacks in SKAN 4.0, conversion values are coarse, and crowd anonymity thresholds mean low-volume campaigns generate no postback at all. Both Airbridge and AppsFlyer are working with the same constraints Apple has imposed on the entire industry.
Where the platforms differ is in gap-filling methodology. AppsFlyer uses its aggregated advanced privacy report to model the portion of installs that fall outside SKAN’s measurement window. Airbridge applies a similar modeling layer. Neither vendor publishes a peer-reviewed accuracy benchmark for their modeled data, and any claim of specific accuracy percentages in this article would be fabricated. The practical test is to run both platforms in parallel on the same campaign for four to eight weeks and compare modeled installs against actual in-app events at a cohort level.
The AboutMartech framework for evaluating this is what we call the SKAN Gap Audit: measure the volume of installs your MMP attributes via deterministic SKAN postbacks, the volume attributed via probabilistic matching, and the volume that falls into the modeled gap. Sum all three and compare against your actual downstream events (registrations, purchases, subscriptions) at a 28-day cohort. The ratio of modeled-to-deterministic attribution tells you how much you are relying on each platform’s estimation engine rather than Apple’s own signal. A team where 60 percent or more of iOS attribution is modeled has a fundamentally different accuracy risk than one where 80 percent is deterministic SKAN postbacks.
Running this audit is straightforward in both platforms. AppsFlyer surfaces attribution method breakdowns in its campaign dashboard. Airbridge exposes the same in its raw export, which is included in Core rather than gated behind a separate SKU.
Which Platform Fits Small Teams or Subscription Apps?
The SKAN Gap Audit is where Airbridge’s bundling argument gets concrete for smaller teams. Say a mobile subscription app has 15,000 monthly iOS installs, runs campaigns on Meta and Google, sends data to Amplitude for product analytics, and has one marketing ops person managing the MMP. That team needs SKAN attribution, raw data access to pipe into their warehouse, web-to-app attribution for their landing page flow, and basic fraud filtering.
On AppsFlyer, those four requirements touch four separate billing items. On Airbridge Core, they are all part of one subscription. The pricing delta depends on volume and negotiated rates, but the structural simplicity of Airbridge’s model means fewer contract negotiation cycles and no surprise overages when the team adds a web touch to their iOS funnel.
AppsFlyer’s free tier is genuinely useful for apps in early testing. So is Airbridge’s. The divergence appears when a team moves off the free tier and starts building out an iOS measurement stack that includes more than basic last-touch attribution. At that point, AppsFlyer’s add-on model can triple the effective cost per attributed conversion relative to the headline rate.
Teams evaluating this in the context of a broader mobile attribution stack can reference the mobile app attribution tools comparison on AboutMartech, which covers Airbridge, AppsFlyer, Adjust, Branch, and Singular side by side across eight criteria.
Where Does AppsFlyer Still Have a Clear Advantage?
Partner network breadth is the clearest area. AppsFlyer’s 10,000-plus integrated partners means that almost any ad network, DSP, or OEM a team wants to buy from has a native integration. Airbridge’s partner list is growing but materially shorter. For a UA team running 20-plus networks simultaneously, a missing integration means either custom postback configuration or unmeasured spend, both of which carry operational cost.
Fraud protection depth is the second area. Protect360, AppsFlyer’s fraud solution, has years of behavioral pattern data and dedicated R&D. Airbridge includes fraud protection in its Core plan, but the sophistication of that protection relative to Protect360 has not been independently benchmarked in a way that allows a direct comparison here. Teams with significant install fraud exposure, particularly in gaming or consumer apps running broad audience acquisition, should evaluate fraud detection capability separately before making a platform decision on price alone.
AppsFlyer’s reporting UI is also more mature. The platform has had more years to build cohort analysis, custom dashboards, and agency-facing views. Airbridge’s interface is clean and functional, but teams accustomed to AppsFlyer’s reporting depth may find themselves rebuilding workflows they take for granted.
Airbridge vs AppsFlyer: Side-by-Side Decision Matrix
| Criterion | Airbridge | AppsFlyer | Winner |
|---|---|---|---|
| SKAN 4.0 support | Yes, included in Core | Yes, included | Tie |
| Total iOS measurement cost (bundled) | Lower for moderate volume | Higher once add-ons factored | Airbridge |
| Ad network integrations | Smaller directory | 10,000+ partners | AppsFlyer |
| Fraud protection depth | Basic, included | Protect360 (advanced, add-on) | AppsFlyer |
| Raw data export | Included in Core | Add-on (Data Locker) | Airbridge |
| Web attribution | Included | Add-on | Airbridge |
| Contract flexibility | Monthly available | Annual standard | Airbridge |
| Reporting maturity | Functional, developing | Deep, mature | AppsFlyer |
| Small team fit | Strong | Moderate | Airbridge |
| Enterprise UA scale | Moderate | Strong | AppsFlyer |
Do App Marketers Actually Prefer One Over the Other?
G2’s MMP category comparison data shows AppsFlyer carrying higher average ratings and broader mindshare. G2 also shows Airbridge holding roughly 19 percent mindshare in the MMP segment versus AppsFlyer’s approximately 25 percent. These numbers reflect installed base more than satisfaction, and large installed bases have structural inertia regardless of product quality.
The more instructive signal is where Airbridge wins competitive deals. Based on publicly available positioning, Airbridge is most often chosen by subscription apps (SaaS, streaming, consumer subscription), mobile-first teams in Asia-Pacific markets, and growth teams that need to activate raw attribution data in a data warehouse without paying a premium for export access. AppsFlyer tends to retain its base in gaming, performance-heavy UA teams, and any organization that has already built workflows around its partner network and reporting UI.
That divide is roughly correlated with company size and UA complexity, not with any inherent quality difference in the core SKAN engine. Both platforms are legitimate MMPs with production deployments at scale. The choice is mostly a pricing model decision dressed up as a technical one.
How Does This Fit a Broader First-Party Measurement Strategy?
An MMP choice does not exist in isolation. iOS attribution is one layer of a measurement stack that increasingly includes server-side event collection, a data warehouse, and some form of media mix modeling to cover the gap that neither SKAN nor probabilistic matching can close.
Teams building toward a warehouse-native measurement stack should evaluate whether their MMP’s raw data format integrates cleanly with their warehouse and downstream tools. Airbridge’s inclusion of raw data export in the Core plan makes it a lower-friction entry point for teams that want to pipe attribution data into Snowflake or BigQuery and join it with CRM or revenue data. AppsFlyer’s Data Locker achieves the same thing but at additional cost. For teams already invested in a first-party data stack, that cost difference compounds as data volume grows.
On the modeling side, for campaigns where SKAN’s crowd anonymity threshold suppresses postbacks entirely, a marketing mix model can pick up what neither MMP can attribute. The marketing mix modeling tools comparison on AboutMartech covers which MMM platforms integrate with MMP-level data, which matters specifically for teams trying to close the iOS measurement gap at the campaign level.
The broader attribution decision framework, including when to layer an MMP with a multi-touch model, is covered in the multi-touch vs last-touch attribution explainer on AboutMartech.
Frequently Asked Questions
What is Airbridge and how does it compare to AppsFlyer as an MMP?
Airbridge is a mobile measurement partner (MMP) that provides app install attribution, SKAN support, web attribution, and raw data export. Compared to AppsFlyer, Airbridge bundles more iOS measurement capabilities into its base subscription rather than charging for them as add-ons. AppsFlyer has a larger ad network partner directory and more mature fraud protection. Both support SKAN 4.0 and probabilistic attribution for iOS. Airbridge is generally better suited to smaller teams and subscription apps; AppsFlyer is better suited to large-scale performance UA.
How much does an MMP cost, and what does Airbridge vs AppsFlyer cost?
MMP pricing is typically based on attributed conversion volume and varies widely by platform and negotiated rate. Airbridge publishes a tiered subscription model with a free entry point and paid plans that scale with conversions. AppsFlyer uses a similar volume-based model but operates primarily on annual contracts with quote-based pricing for paid tiers. The total cost of iOS measurement differs significantly between the two because AppsFlyer charges separately for raw data export, web attribution, and advanced fraud protection, while Airbridge includes these in its Core plan.
Does AppsFlyer’s SKAN implementation outperform Airbridge’s?
Both platforms support SKAN 4.0 including three-postback measurement and conversion value configuration. Neither platform can overcome the structural limitations Apple imposes on all MMPs, including delayed postbacks, coarse values, and crowd anonymity thresholds that suppress low-volume campaign data entirely. The difference is not in the SKAN engine itself but in what supporting capabilities each platform bundles with it. Running both platforms in parallel for a defined test period is the only reliable way to compare modeled attribution accuracy for a specific app and campaign mix.
Is Airbridge a good choice for small teams?
Airbridge’s Core plan is particularly well-matched to small growth teams for three reasons. It bundles web attribution, raw data export, and fraud filtering into one subscription rather than requiring teams to negotiate add-ons separately. It offers monthly contracts, which reduces commitment risk during early UA testing. And its interface is designed for teams without a dedicated MMP analyst. The limitation is partner breadth: teams running media through less common ad networks or regional DSPs should verify integration availability before committing.
Who are AppsFlyer’s main competitors?
AppsFlyer’s primary competitors in the MMP category are Adjust, Airbridge, Branch, and Singular. Adjust is the closest in scale and partner coverage. Airbridge and Singular compete on pricing model and iOS measurement cost. Branch competes primarily on deep-linking and cross-platform identity. Each has a meaningfully different pricing structure, and the right choice depends on install volume, the ad networks a team buys from, and whether fraud protection is a primary requirement or a secondary one.
What is SKAN and why does it matter for mobile attribution?
SKAdNetwork (SKAN) is Apple’s privacy-preserving attribution framework, introduced to replace IDFA-based deterministic attribution after App Tracking Transparency reduced opt-in rates. SKAN sends postbacks directly from Apple to ad networks with a defined conversion value, a campaign identifier, and no user-level data. SKAN 4.0 added a three-postback structure to provide early, intermediate, and late conversion signals within a campaign window. All major MMPs, including Airbridge and AppsFlyer, build their iOS attribution workflows around SKAN because it is the only Apple-sanctioned mechanism for measuring campaign performance on opted-out iOS users.
Can I use Airbridge or AppsFlyer data in my data warehouse?
Both platforms support data export to cloud warehouses such as Snowflake, BigQuery, and Redshift. Airbridge includes raw data export in its Core plan. AppsFlyer offers a similar capability through its Data Locker product, which is priced as an add-on. Teams that want to join attribution data with CRM records, subscription revenue, or product analytics data in their warehouse should factor the data export cost into their total MMP budget, particularly if they plan to export at high volume or real-time frequency.
The Decision That Actually Needs to Be Made
AppsFlyer’s default status in this market is real, but it is built on historical installed base and partner network breadth rather than iOS measurement superiority. On the specific question of who measures iOS campaigns better, the honest answer is that SKAN constrains both platforms equally. The question underneath the question is which platform’s total cost and bundling model fits your team’s actual iOS measurement requirements without requiring five separate add-on negotiations.
For a subscription app with moderate iOS install volume, a small growth team, and a need to pipe raw data into a warehouse, Airbridge’s Core plan covers the iOS measurement stack at a lower total cost with a more flexible contract. That is a concrete structural advantage, not a marketing claim. AppsFlyer is the right answer when partner network depth, advanced fraud protection, or reporting sophistication are non-negotiable requirements, and the team has the budget and contract patience to match.
The most common mistake in this evaluation is pricing only the base MMP fee rather than the full iOS measurement stack. Before signing anything, build a line-item list of every iOS measurement capability you actually need: SKAN, probabilistic attribution, web-to-app attribution, raw export, fraud filtering, and any modeled reporting. Price that list with both vendors and compare the totals. That exercise, more than any feature comparison, will tell you which platform is actually cheaper for your specific stack.
