Some Woopra users see a discrepancy between their Woopra and Google Analytics stats. The primary reasons for this discrepancy are each service’s reporting and tracking methods. Woopra is committed to providing the most accurate data by showing you individual visitors and exactly how they're engaging across the omnichannel touchpoints you're tracking.
Woopra shows you exactly who is on your site or application, what they’re doing, and when they leave. Woopra’s reporting is accurate to the second. We use "beacons," which accurately record when a user enters, exits, switches tabs, or closes a browser.
Google Analytics reports time on page based on timestamps. They calculate this by subtracting the time of the initial event from the subsequent event. This can lead to inaccurate durations because the exit page will not have a next page to calculate, so the time on page for an exit page will be 0 seconds.
Another scenario is if a user goes idle for under 30 minutes. In GA, if a user visits a page at 12:00, stays on a page for 3 minutes, then goes idle for 29 minutes, and later visits another page at 12:29 -- GA will show that they stayed on the first page for 29 minutes. Using beacons, Woopra can accurately tell when the user navigated away from the page and will give you the 3-minute duration.
Another cause of this discrepancy is Google Analytics’ use of sampling, which means using a subset of data. Google Analytics often uses sampling for both collecting data and generating reports based on your data. That means that Google Analytics may only be collecting data on some of your visitors and/or only using a portion of that collected data when generating your reports.
Woopra never uses any kind of sampling. Since we report at the individual level, rather than simply aggregating, we always collect your full data set. You can see the full list of current visitors in the “Live Visitors” tab and the full history of individual visitors in the “Search” tab. Woopra’s analytics reports are generated using this full set of data.
Lastly, some discrepancies exist between Woopra and Google Analytics due to the growing tendency for each person to have multiple devices (e.g., mobile, tablet, home computer, work computer, etc.) from which they access the same online services.
Traditional web analytics, like Google Analytics, cannot track a user across multiple devices or browsers, so a visitor returning to the site from another device or browser is identified as a new visitor rather than a returning visitor. This can lead to skewed numbers because some of their visitors might be the same person.
Since Woopra focuses on individual-level profiles rather than device-based tracking, our numbers are much more accurate. For example, you might sign up for service X from your home computer, use the service’s app on your iPad, and upgrade your account from your work computer. Woopra will track this as one person because we merge profiles based on a common identifier like an email address. Whereas GA doesn't allow for any personal information to be tracked and would count this user as three separate people.
Lastly, when comparing numbers between Woopra and GA, it's important to get as close to comparing apples to apples as we can. While our tracking method is different, keep in mind that our reporting is also different. For example, when running a Trend report on a specific page, the filtering can vary on both platforms.
For example, if we're running a report in GA for 'www.site.com/page1', does that count include variations on the page like 'www.site.com/page1?utm_campaign=email'?
In Woopra, we have several constraint modifiers like 'is, contains, exists, is not, etc.' so to get more accurate results when comparing numbers, try to match the filtering as closely as possible on both platforms.
Another important point is that our reports use different metrics such as "People, Visits, and Actions." The numbers that are most similar to GA would be "Actions." The Action count is the number of times the tracked event occurred. Visits are the number of sessions that the event occurred in. People is the number of unique people that did the event. GA tracks sessions and people very differently, so using the action count would be the closest to what they track.
Updated 28 days ago