Data Discrepancies and Reporting Issues

Introduction

When comparing data across different reports or platforms, it’s common to encounter data discrepancies. These variations may arise from several factors including attribution differences, time zone variations, reporting methodologies, data sync delays, and filtering differences. This guide will help you troubleshoot and resolve these discrepancies, ensuring accurate reporting.

Common Causes of Discrepancies

Understanding the factors that contribute to data discrepancies is essential for accurate comparisons. Here are some common causes:

Platform Differences: Data from EZmob may differ from external tracking platforms due to distinct attribution models or methods of data collection.

Time Zone Issues: EZmob reports in UTC by default, which can lead to discrepancies when compared with platforms that use local time zones.

Attribution Windows: Variations in click versus view attribution windows between EZmob and other platforms can result in differences in reported conversions.

Data Sync Delays: Real-time reporting on EZmob might not align immediately with platforms that process data in batches.

Filtering Differences: The inclusion or exclusion of specific traffic types or data sources may vary between EZmob and external platforms.

Diagnostic Procedures

To effectively troubleshoot discrepancies, follow these diagnostic procedures:

Check Time Zone Settings: Ensure you are comparing data for the same time period, accounting for any time zone differences.

Verify Attribution Models: Compare the attribution window settings on EZmob with those on the external platform.

Review Data Processing Timelines: Understand the data update frequency on both platforms to identify potential sync delays.

Examine Filtering Criteria: Ensure that the same data filters (e.g., traffic types, geographies) are applied across platforms.

Resolution Strategies

Here are some strategies to resolve discrepancies:

Data Reconciliation: Manually adjust data for time zone differences and re-check totals.
Acceptable Variance Ranges: Identify what variance range is acceptable for your reporting needs, as minor discrepancies are often normal.
Technical Issues: If discrepancies persist or are significant, contact EZmob support for further assistance.

Helpful tip: Regularly communicate with team members about discrepancies to ensure everyone is aware of potential issues.

Best Practices for Data Comparison

To minimize discrepancies in the future, consider implementing these best practices:

Standardize Reporting: Align reporting time zones, attribution models, and data processing timelines across platforms whenever possible.
Regular Audits: Periodically review and reconcile data across platforms to identify and resolve discrepancies early.
Documentation: Keep detailed records of your data reconciliation processes and any adjustments made for future reference.

By following this guide, you can better navigate data discrepancies and ensure consistency across your reporting efforts.

Updated on: 04/11/2025

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