Data integration and analytics

Improve Attribution Accuracy by Avoiding Google Analytics Sampling

Google Analytics (GA) is a staple of any MarTech stack, but reporting limitations can hurt attribution accuracy, especially for large organizations with huge web traffic volumes. Is there a better way to process GA data? Let’s find out.

How Google Analytics sampling works

Google Analytics offers a range of reports on various aspects of a website including audience, acquisition, and conversions. But not all reports are made equal. 

Default reports such as those mentioned above are analyzed using the full dataset, while ad hoc queries involving large datasets may be derived from a subset of data. Queries are also limited to the latest 14 months on a rolling basis.
While Google does offer a premium version, Analytics 360, with more features and significantly fewer restrictions, it starts at $150,000 per year, effectively pricing out all but the most established businesses.

For most organizations on the free Analytics Standard plan, these restrictions and sampling methods may produce the following outcomes: 


Less accurate insights

Small and inconsistent sample sizes can lead to inaccurate insights, especially when the margin of error can be more than ±5% depending on the sample size.

Limited query range

Sampling starts for queries above 500K sessions for Analytics Standard and 100M for Analytics 360. This severely limits the 100% accurate query range for most organizations.

Limited historical data

GA’s 14-month restriction makes it hard to analyze data that’s more than a year old. Exploring trends spanning years or decades will be a challenge.

Accessing Google Analytics data without limits

Sona’s built-in extract, transform, load (ETL) capabilities allow you to import and store a copy of your GA data for thorough, unrestricted analysis.

When a Google Analytics report is configured within the Sona platform, data is pulled in on a daily basis and appended to the previously stored data. This automatic data extraction and synchronization process avoids sampling issues related to pulling larger datasets, delivering the following benefits:

Bridge the Gap Between Marketing and Revenue

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