Measure what happened in a practical way
FreeCROTool uses identifiable testing events to compare a control against a challenger so you can understand whether a change is improving user behaviour. The default reporting route is Google Analytics, with optional deeper analysis routes where needed.
Google Analytics allows you to report on what happens on your website, such as page views, funnel progress, signups and purchases. FreeCROTool can use clearly identifiable testing events so you can compare versions of a test through a familiar platform.
FreeCRO Tool combines the accessibility of Google Analytics with a streamlined reporting layer that removes much of the manual effort typically involved in test analysis. Key metrics are pulled, structured, and presented in a way that makes results easier to understand and act on.
While the experience is simplified, you still benefit from the flexibility of GA and the ability to explore deeper insights when needed. As with any analytics platform, some metrics may use probabilistic methods to improve performance at scale.
Google Analytics is designed to be fast and scalable, which means it sometimes uses approximation techniques behind the scenes. FreeCRO Tool works with this data in a structured way, but it is still helpful to understand how it behaves.
Some reported numbers, particularly unique counts or segmented data, may be approximate rather than perfectly exact.
These techniques allow Google Analytics to return results quickly and handle very large volumes of data without slowing down.
For most small to medium-sized websites, these effects are minimal and the data remains highly practical for decision-making. Combined with FreeCRO Tool’s structured reporting, trends and winning variants are still clear and actionable. For the types of businesses FreeCRO Tool is designed for, these limitations rarely impact decision quality.
For most users, Google Analytics provides everything needed to run effective experiments. But if you want to go deeper, BigQuery unlocks a much richer layer of analysis within FreeCRO Tool.
By connecting BigQuery, you move beyond standard reporting into understanding how and why users convert, not just what happened.
Understand how long it takes users to convert after key actions. For example, compare whether a challenger variant leads to faster purchases than the control, helping optimise funnel efficiency.
Analyse behavioural sequences, such as users who added to basket and then visited a specific page. This helps uncover hidden paths that influence conversion.
Identify which hours of the day drive the strongest performance, rather than relying only on daily aggregates. This can reveal timing opportunities for campaigns or UX changes.
See how different conversion points relate to each other. For example, what percentage of users who trigger Event A go on to complete Event B, helping you understand which steps truly drive outcomes.
BigQuery is no longer the completely free route. There can be modest costs related to storage, querying and report generation. For some businesses that extra capability is worth it. For others, Google Analytics alone is the more sensible starting point.
BigQuery data collection is not retrospective. This means it will only apply to tests running after it has been set up, and cannot be used tore-analyse past experiments.
Start with the practical free route, then step up into deeper analysis only when it starts to add real value.
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