How to Debug Reporting Discrepancies

Sometimes, implementing new technology can be a bit challenging as everyone learns the intricacies of both the product and the needs of their specific clients. This page presents the most common issues that Attribution Analytics clients encounter with reporting (and includes tips on how to resolve them).

Dashboard Settings

This section describes the issues related to account settings (which can affect reporting accuracy).

Time Zone

Unlike most of our competitors, we allow Attribution Analytics users to set their own time zone. While this option helps to tailor the Attribution Analytics platform to you, it can lead to confusion when comparing analytics data across different platforms (because all parties may not be in the same time zone). Specifically, this setting can make it appear as if there are data discrepancies between the Attribution Analytics platform and third-party platforms. For example, the date/time of an app install can vary widely because each system records the same event with different time zone settings.

In addition, both the Apple® iTunes® App Store and Google Play™ Store use different time zones for their reporting, which can also introduce discrepancies in reporting. For information about comparing measurements with other app stores, visit comparing installs to other app store reports.

Instead of changing the time zone in your account settings, you can change the reporting time zone for the reports themselves as you run them (to debug discrepancies). Simply select the appropriate time zone when choosing the date range for report generation.


This section describes the issues related to implementation of not only the Attribution Analytics SDK, but also other partner SDKs (which can directly affect reporting accuracy).

Dual Implementation

If your app has a partner SDK installed (in addition to the Attribution Analytics SDK), then the advertising partner (publisher) may claim credit for installs in which they’re not actually responsible for (clients have reported to us that some partners are over-billing by as much as 20%). Our SDK only attributes partners if they are truly responsible for the last click that an end user made, whereas a partner typically claims credit for any install that involves a user clicking on one of their banner ads. If you have multiple partner SDKs installed, then you may be paying multiple times for the same install because multiple networks claim credit for it.

To avoid this problem, make sure that only the Attribution Analytics SDK is installed. Our SDK allows you to advertise with any of our integrated partners without requiring you to install their SDKs (except Chartboost).

Postback URLs

This section describes the issues related to postback URL setup in the Attribution Analytics platform (where the postbacks notify your advertising partners of installs and other in-app events).

Using Templates

You can simplify server postback configuration by leveraging the postback templates, which are great for quickly creating postbacks but they’re only valid for the event specified during postback creation. So for example, if you use the “Install” template, then the created postback URL is only valid for the install event (and no other type of event).

Using a postback URL template is convenient for the specific app event that it’s associated with, but can potentially create reporting problems if used for a non-intended event. For example, if the network receives the same postback URL for an install and an additional app event, then it cannot differentiate between them and may consider both postbacks as installs (or count both as events), leading to unpredictable and skewed data (especially if the postback URL does not contain identifying information, or the network cannot de-dupe install counts).

Using the Same Call for Multiple Events

If you configure postbacks with the same call for multiple events, then you may encounter issues in reporting. If you do not append the appropriate macros to your postback URLs (to pass in event information), then you may see discrepancies in event counts (which may prevent the partner from optimizing effectively). For more information about configuring server postbacks, please visit Setting Up Postback URLs.

Data: All

If you configure your postback URLs to send ALL data to a partner, then they may take credit for installs that Attribution Analytics attributed to someone else. We’re working with networks to implement our conversion flag in their postback templates so they can see all data. Partners who support this flag can enable the “Data: All” setting on the postback URL (else, the default setting is “Data: Attributed“). You should only send attributed data to partners unless they support the conversion flag. For more information about postback URL parameters (including “Data: Attributed” and “Data: All“), visit “Is Attributed?” Postback Parameter.

If you set “Data: All” for the postback URL but the integration does not support it, then Attribution Analytics cannot debug any discrepancies.


This section describes the issues related to attribution practices and related settings (which play an important role in reporting accuracy).

Reporting Window

Attribution Analytics allows you to customize the attribution window for determining if a partner receives credit for an install. For example, many partners have a default window of 7 days from click (to claim the install), but if you have high install volume or are willing to pay a higher price, then we’ll let you reduce that window. Since we’re not involved in that negotiation, we detect custom attribution windows through the settings in our dashboard. If the reporting window that you negotiated (and agreed upon) with the partner is different from the attribution window that you set in our dashboard, then discrepancies can arise in the number of installs attributed.

Integrated Partners & Ad Networks

This section describes the issues related to unique integrations with other partners and ad networks. As these integrations are unique to each partner, we created separate guides for resolving the resulting discrepancies.


For information about reconciliation with ChartBoost, visit our article on reconciling discrepancies between Attribution Analytics and Chartboost.

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