Introduction
An Adjust implementation audit should explain whether acquisition and revenue data are reliable enough to guide spend. Use this checklist to trace the journey from a first app open to the decisions made in your reporting stack.
Executive summary
Key Takeaways
- Test complete user journeys, not only whether the SDK starts.
- Separate expected reporting differences from missing or duplicated events.
- Give every critical finding a reproducible example, an owner and a retest.
1. Define the Decisions Your Audit Must Support
Start by naming the decisions that depend on Adjust: reallocating acquisition budget, comparing paid cohorts, valuing a trial start or evaluating a market launch. For each decision, record the report, metric, attribution basis and person who relies on it. A technically successful integration is insufficient if the team cannot explain what a reported acquisition or revenue figure represents. The audit scope should follow these decisions across iOS, Android and the destinations that receive their data.
Collect the installed SDK versions, event-token inventory, app identifiers, partner configuration, reporting filters and a release timeline. Add the backend or subscription system that confirms payment. Ask for read-only evidence where practical and keep customer identifiers out of shared screenshots. The deliverable at this stage is a map of where data originates, how it is transformed and which team owns each handoff. This makes later findings actionable rather than a list of disconnected settings.
2. Trace First Open, Activation and Revenue Events
Choose a small set of representative journeys: a new installation, an existing user upgrading, a first purchase and a returning customer. Record the expected event sequence before testing. Follow each journey through device evidence, Adjust reporting and the receiving destination. Include failure paths such as losing connectivity after a purchase or reopening the app after an interrupted onboarding. Record the test environment so sandbox transactions cannot be confused with commercial activity.
Adjust describes installs as first opens, which can differ from a store download. It also warns that sending the same event through both the SDK and a server integration can duplicate counts. Use those distinctions when interpreting a discrepancy. Our recommended audit control is an event ownership register: one authoritative producer for each business event, documented retry behavior, a reconciliation key where available and a clear rule for any intentional parallel delivery.
3. Separate Attribution Rules from Collection Failures
Inspect click and impression windows, reattribution rules, campaign naming and the filters applied to the actual reports used by the team. Take a recorded acquisition example and explain why it belongs to its reported source. Do not copy a window from another account simply to make totals look similar. The settings should match your business question and the reporting conventions of the compared platform. Save the configuration alongside the period you are analysing.
Keep consent-eligible user-level attribution and aggregated privacy-preserving reporting in separate analyses. A missing advertising identifier is not evidence that every event is missing. Likewise, an aggregated postback cannot be treated as a row that can always be joined to a named subscriber. A useful finding identifies exactly which signal is absent, which decisions are affected and whether the limitation follows platform rules or an implementation defect.
4. Verify What Advertising Partners Actually Receive
A visible event in Adjust does not prove that an advertising partner receives the intended optimization signal. Review event mapping, revenue-sharing choices, relevant parameters and the destination's own diagnostics. Compare the event name and meaning on both sides. For example, a trial-start event should not silently stand in for a paid subscription just because both appear near the purchase screen. Capture the configuration and one observable delivery example for each priority destination.
Work backward from a campaign's optimization event. Can the app produce that event consistently? Does the receiving platform recognize it? Is the value field meaningful, and does the event happen often enough for the team's chosen operating approach? Keep privacy and sharing requirements within the product's agreed consent model. Missing data should trigger a documented investigation, not an automatic decision to send more user information.
5. Reconcile Revenue with a Controlled Sample
Build a sample ledger containing the transaction reference, event time, app platform, original currency, amount, environment and reporting destination. State whether the amount represents gross sales, estimated proceeds or another revenue definition. Trace successful payments, renewals and refunds separately. If the subscription system also forwards revenue into Adjust, verify that an application event does not count the same payment again. Never infer correct revenue merely from a plausible-looking ROAS chart.
Compare mature periods with matching filters before escalating a gap. An illustrative diagnostic pattern is revenue diverging immediately after a release while purchase counts remain stable. That would justify checking amount, currency and event mapping before changing attribution rules. It is a hypothesis, not proof of a particular bug. Use a reproducible sample to confirm the cause, then compare the same sample after remediation.
6. Turn Findings into a Retestable Repair Plan
Each issue should contain the observed behavior, expected behavior, evidence, affected decision, scope, owner and acceptance criterion. Prioritize errors that distort bidding or access to paid features before cosmetic reporting inconsistencies. Distinguish a verified defect from an unresolved question and an accepted platform limitation. A suspected discrepancy should not receive the same confidence label as a duplicated transaction demonstrated in logs.
Finish with a release-ready backlog and a baseline for ongoing monitoring. Retest repaired journeys on the relevant platforms and confirm the downstream report, not only the code change. Grovix's measurement audit connects these technical checks to the acquisition and revenue decisions they support. The outcome is a defensible measurement system and a prioritized set of fixes, rather than a promise that all platforms will eventually display identical numbers.
Explore Grovix's Adjust implementation and measurement support
Frequently Asked Questions
Does a difference between Adjust and another dashboard mean the SDK is broken?
No. First align definitions, reporting dates, filters and attribution rules. Investigate collection or delivery when the remaining difference has reproducible evidence.
When should we audit an existing Adjust setup?
Useful triggers include a major app release, an MMP migration, a new revenue integration, a persistent unexplained discrepancy or a change in the event used for campaign optimization.
Related Client Evidence
These documented engagements provide practical context. Their observed outcomes are specific to each client and measurement window.
Building a Trustworthy Measurement System for a Fintech App
The engagement established a documented framework for tracing acquisition traffic from source to conversion, giving the team a repeatable way to validate MMP configuration, data handoffs, and campaign traffic.
This NDA-protected case describes the verified scope and operating outcome of the engagement. The report spans more than 200 pages and demonstrates audit depth; it is not presented as a performance-lift claim. No revenue, ROAS, CPA, or incrementality result is attributed to the audit.
Editorial standards
How This Resource Was Prepared
The Grovix Growth Team reviews official platform documentation and the primary sources listed in each resource, then translates that evidence into an operating framework for mobile teams. Platform requirements are cited directly; Grovix recommendations reflect practitioner judgment and should be validated against the app, market, and measurement setup.
Written and reviewed by Grovix Growth Team, senior-led practitioners working across app store optimization, apple ads, mobile measurement, lifecycle, and monetization. The page was published on and last reviewed on .
Grovix, Türkiye. Questions, corrections, or source updates can be sent to hello@grovix.co.Sources and Further Reading
Platform features and measurement conventions change. These primary sources support the platform-specific statements in this resource and should be checked during implementation.