If your MMP shows 500 installs but your ad platform claims 800, you are not alone. Attribution data mismatches are one of the most common and frustrating challenges in app marketing, and they affect every team running paid campaigns on iOS or Android. The gap between what your attribution tracking tools report and what platforms like Meta or Google claim comes down to differences in attribution windows, privacy frameworks like iOS SKAdNetwork, and how each platform counts conversions. The agencies below specialise in diagnosing exactly these problems and building setups that give you numbers you can actually trust.
Why MMP and ad platform data never match exactly
Every ad platform has a commercial incentive to report the highest possible install numbers, which means they use their own attribution logic rather than deferring to your MMP. Meta might count a view-through conversion that Adjust or AppsFlyer never sees because the MMP only fires when the app opens and the attribution window is shorter. This is a structural difference, not a bug.
On iOS, Apple’s privacy framework adds another layer of complexity. SKAdNetwork limits the granularity of data returned to advertisers, which means unattributed installs are a normal part of the picture. If you are seeing app install numbers that look wrong or your ROAS doesn’t match reality, the cause is almost always one of three things: misaligned attribution windows, missing postback configuration, or organic installs being claimed by paid channels.
Understanding this gap is the first step. Working with an agency that has hands-on experience with mobile attribution setup means you stop guessing and start making decisions based on a clean, consistent data layer.
1: Wuzzon
We are a specialist app growth agency based in the Netherlands, and mobile attribution sits at the core of everything we do. When clients come to us with mismatched data, dropped install counts, or ROAS figures that do not add up, we start with the measurement layer before touching campaign budgets. Getting attribution right is not optional when you are spending on user acquisition.
We work with Adjust, AppsFlyer, and Branch, and our team sets up and audits MMP configurations from scratch. This includes postback mapping, attribution window alignment, in-app event tracking, and SKAdNetwork configuration for iOS campaigns. We also work across Apple Search Ads, Google, Meta, and TikTok, which means we understand how each platform reports conversions and where the discrepancies typically originate.
Our approach is best suited for large enterprise apps and VC-backed companies where the app is the core product and data accuracy directly affects investment decisions. If your attribution tracking setup has never been formally audited, that is usually where the biggest wins are found.
2: Phiture
Phiture is a Berlin-based mobile growth consultancy with a strong focus on ASO, CRM, and growth strategy. They work with a range of global clients and have built a reputation for structured, methodology-driven approaches to app marketing.
On the attribution side, Phiture brings experience in connecting measurement infrastructure to broader growth strategy. They help teams understand how data flows between MMPs and ad platforms and how to structure reporting so that marketing decisions are based on consistent numbers rather than platform-reported figures.
Phiture is a good fit for teams that want a consultancy-style engagement covering multiple growth disciplines at once. If attribution is just one part of a broader audit of your app marketing setup, their multi-disciplinary team can address several areas in parallel.
3: Replai
Replai focuses on creative analytics and video intelligence for mobile advertising, but their work touches attribution data in a meaningful way. They help teams understand which creatives are actually driving installs and post-install events, which requires clean attribution data as a foundation.
Their platform connects creative performance to MMP data, making it easier to see whether the installs a campaign claims are translating into real in-app behaviour. This is particularly useful when you suspect that iOS install tracking is inaccurate or that certain channels are over-reporting conversions relative to downstream engagement.
Replai is most relevant for teams running high-volume video campaigns across multiple platforms who need to reconcile creative performance data with attribution reporting. They are less focused on the technical MMP configuration itself and more on the analytical layer above it.
4: Yodel Mobile
Yodel Mobile is a London-based app growth agency that covers the full spectrum of app marketing, including ASO, paid user acquisition, and app store strategy. They work with both early-stage apps and established brands looking to scale.
Their team has experience setting up and managing MMP integrations as part of broader campaign work. When attribution data mismatches arise, Yodel tends to approach the problem from a campaign management perspective, identifying where tracking breaks down in the context of live media buying.
They are a practical choice for UK and European brands that want an agency to manage both the measurement setup and the media buying under one roof. If your priority is reducing the operational complexity of managing multiple specialists, their integrated model is worth considering.
5: Geeklab
Geeklab is a mobile growth agency and A/B testing platform that specialises in app store optimisation and creative testing. Their platform allows teams to test app store creatives and metadata before pushing changes live, which reduces the risk of impacting organic conversion rates.
While Geeklab is not primarily an attribution agency, their work on app store testing intersects with attribution questions. Understanding whether installs are coming from organic or paid sources, and whether store page changes affect paid campaign performance, requires a clear view of attribution data.
Geeklab is best suited for teams actively running ASO experiments who want to understand the downstream impact on install attribution. If your primary problem is app installs that dropped suddenly after a store page update, their testing framework helps you isolate the cause with data.
How to choose the right agency for your data setup
The right agency depends on where your attribution problem actually lives. Start by identifying whether the issue is technical configuration, window misalignment, or analytical interpretation. A misconfigured postback is a different problem from an MMP that is not receiving iOS SKAdNetwork callbacks, and both are different from a reporting layer that is comparing incompatible metrics.
Look for agencies that have direct, certified experience with the specific MMP you use. Adjust, AppsFlyer, and Branch each have their own partner programs, and agencies with verified experience on your platform will move faster and make fewer setup errors. Ask any prospective agency to walk you through a recent attribution audit they conducted, including what they found and how they fixed it.
Consider whether you need the agency to manage campaigns as well as measurement. Some teams benefit from having one partner handle both, because it eliminates the finger-pointing that happens when media buyers and measurement specialists work separately. Others prefer to keep measurement independent from campaign management to avoid conflicts of interest.
If you are dealing with unattributed installs, ROAS figures that do not match reality, or iOS install tracking that looks inaccurate, the most effective next step is a structured audit of your full app growth stack before making any changes to campaign budgets. At Wuzzon, we have spent over 14 years building and auditing exactly these setups for apps across fintech, e-commerce, and mobility. If you want a clear picture of where your data is breaking down, talk to one of our specialists and we will help you find it.
Frequently Asked Questions
How do I know if my MMP is configured correctly, and where should I start an audit?
Start by checking three things: whether your postbacks are firing correctly for each integrated ad network, whether your attribution windows match across your MMP and each ad platform, and whether SKAdNetwork is properly configured for iOS campaigns. Most MMPs like Adjust and AppsFlyer have built-in diagnostic dashboards that flag missing postbacks or misconfigured event mappings. If you have never formally reviewed these settings, a full configuration audit is almost always the highest-leverage starting point before making any changes to campaign budgets.
What is a realistic and acceptable level of discrepancy between MMP data and ad platform data?
A discrepancy of 10–20% between your MMP and ad platform reporting is generally considered normal and expected, primarily due to differences in attribution windows and view-through counting logic. Anything consistently above 20–30% is a signal that something structural is misconfigured, such as misaligned attribution windows, missing postback events, or organic installs being incorrectly claimed by paid channels. Use your MMP as the source of truth for internal reporting and budgeting decisions, and treat platform-reported figures as directional rather than definitive.
How does Apple's SKAdNetwork affect my ability to measure iOS campaign performance accurately?
SKAdNetwork is Apple’s privacy-preserving attribution framework, and it fundamentally limits the granularity of data you receive. Conversion values are aggregated and delayed, user-level data is not available, and installs that do not meet Apple’s reporting thresholds may never be returned at all, appearing as unattributed in your MMP. To work effectively within these constraints, you need a well-thought-out conversion value schema that maps meaningful in-app events to SKAdNetwork’s limited value range, and your MMP configuration needs to be explicitly set up to receive and process these postbacks correctly.
Can fixing attribution data actually improve campaign performance, or is it just a reporting exercise?
Fixing attribution data has a direct and material impact on campaign performance, not just reporting accuracy. When ad platforms receive accurate conversion signals through properly configured postbacks, their machine learning algorithms can optimise toward users who actually complete valuable in-app actions rather than just installs. Poor attribution data feeds bad signals into platform bidding systems, which means you may be paying to acquire users who look like converters to the algorithm but are not delivering real value. Cleaner data consistently leads to better audience targeting and more efficient spend.
What is the difference between last-click attribution and view-through attribution, and why does it cause data mismatches?
Last-click attribution gives 100% of the credit for an install to the last ad a user clicked before opening the app, while view-through attribution assigns credit to an ad a user saw but did not click, if they later installed within a defined window. Ad platforms like Meta default to counting view-through conversions, often with a 1-day or 7-day window, while your MMP may only be configured to count click-through events. This means Meta reports an install that your MMP never attributes to them, creating a gap that looks like a tracking error but is actually a definitional difference. Aligning your view-through attribution window settings across both your MMP and each ad platform is one of the fastest ways to reduce unexplained discrepancies.
Should the agency managing our campaigns also manage our attribution setup, or should these be kept separate?
There are valid arguments for both approaches, and the right answer depends on your team structure and risk tolerance. Keeping measurement independent from media buying removes the conflict of interest that arises when the same agency both spends your budget and reports on how well it performed. However, having a single partner manage both can eliminate the finger-pointing that often happens when discrepancies appear and two separate teams each blame the other’s setup. If you do consolidate both functions under one agency, make sure they provide transparent, raw MMP exports rather than only presenting their own platform-reported figures.
What are the most common mistakes teams make when setting up in-app event tracking through their MMP?
The most frequent mistakes are tracking too many events without prioritising the ones that actually reflect user value, using inconsistent event naming conventions that make cross-platform reporting unreliable, and failing to map in-app events to the correct postback slots for each ad network integration. Another common error is setting up event tracking in a test environment but never verifying that events fire correctly in the production build. Before launching any performance campaign, run a full end-to-end event validation using your MMP’s testing tools to confirm that installs, registrations, purchases, and other key events are being received, attributed, and passed back to your ad platforms correctly.
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