Common Questions Series: Why Are There Discrepancies Between Channel Data and Data from Third-Party

As digital marketers, we rely on data to make informed decisions and optimise our marketing strategies. However, it's not uncommon to encounter discrepancies between the data provided by various channels (such as Google Ads, Facebook Ads) and third-party analytics tools (like Google Analytics, Adobe Analytics). In this article, we explore the reasons behind these discrepancies and shed light on the challenges of data measurement in digital marketing.

1. Different Tracking Methodologies

One of the primary reasons for discrepancies is the variance in tracking methodologies used by different platforms. Each channel and analytics tool employs different tracking mechanisms, such as cookies, pixels, or tracking codes. These variations can lead to differences in data collection, attribution, and measurement methodologies, resulting in disparate results.

2. Data Sampling and Aggregation

Large-scale platforms often rely on data sampling and aggregation techniques to process vast amounts of data efficiently. While these techniques provide a representative snapshot, they may introduce some degree of error or approximation. As a result, the data provided by these platforms may not always match the precise data recorded in paid-for third-party analytics tools.

3. Attribution Models and Timeframes

Attribution models determine how credit is assigned to various touchpoints in a customer's journey. Different platforms and analytics tools may use varying attribution models, such as last-click, first-click, or multi-touch attribution. These models can lead to differences in how conversions are attributed and reported across platforms, resulting in measurement discrepancies.

Additionally, the timeframe used for reporting can impact the data alignment. Some platforms provide real-time data, while others may have a delay in data processing. As a result, comparing data across different timeframes can lead to discrepancies.

4. Data Privacy and Tracking Restrictions

Data privacy regulations and user tracking restrictions imposed by platforms or web browsers can also impact data accuracy and consistency. Ad-blocking software, cookie consent settings, and ever more privacy-focused browsing options can affect data collection and tracking, leading to differences between channel data and third-party analytics tools.

5. Data Processing and Filtering Logic

Each platform or analytics tool may apply its own data processing and filtering logic. This includes removing spam or invalid clicks, deduplicating conversions, or applying anti-fraud measures. These processing methods can vary, leading to discrepancies in the reported data between different systems.

Addressing Discrepancies and Ensuring Data Accuracy

While complete alignment of data across all platforms is challenging, there are steps you can take to mitigate discrepancies and ensure data accuracy:

1. Implement Proper Tagging and Tracking

Ensure that you have correctly implemented tracking codes, pixels, or tags across your digital assets. Regularly validate the implementation to minimise tracking errors.

2. Establish a Primary Source of Truth

Select a reliable analytics tool or platform as your primary source of truth. Use this tool as a reference point for data analysis and decision-making. Remember that it won't be perfect, but if it's consistent then that's OK.

3. Compare Data on a Relative Basis

Rather than focusing solely on absolute numbers, compare trends and patterns across different platforms to identify insights and optimisations.

4. Use Data Discrepancies as Learning Opportunities

Understand the differences in measurement across platforms and use them as learning opportunities to fine-tune your tracking and optimisation strategies.

5. Leverage Data Integration and Attribution Solutions

Explore data integration and attribution solutions that allow you to consolidate and analyse data from multiple sources. These tools can provide a more comprehensive view of your marketing performance.

6. Work with Experienced Analytics Professionals

Partnering with experienced digital marketing and analytics professionals can help navigate the complexities of data measurement, interpretation, and optimisation. Their expertise and knowledge can provide valuable insights and assist in aligning your data effectively.

Key Point: Remember, while discrepancies in data measurement exist, it's essential to focus on trends, patterns, and insights rather than getting caught up in exact numbers. By understanding the factors contributing to these discrepancies and taking the necessary steps to mitigate them, you can make informed decisions and optimise your digital marketing strategies effectively.