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This article covers the following:
- Overview
- Discrepancies Due to Configuration
- Discrepancies Due to Operational Differences
- Discrepancies Due to Browser Settings
- Discrepancies Due to Divergent Conversion Criteria
Note: While this list of potential reasons for data discrepancies is written with Wingify and Google Analytics in mind, these factors are equally relevant to other third-party integration tools. If you are comparing Wingify data with an analytics tool other than Google Analytics, refer to Troubleshoot Data Discrepancies Between Wingify and Third-Party Analytics Tools.
Overview
The insights gathered from your campaigns provide a narrative of your visitors' online interactions with your website. Therefore, ensuring the utmost accuracy of this data is of paramount importance. Each website analytics platform presents its data uniquely, emphasizing the need to comprehend the evaluative dimensions of these platforms to draw meaningful conclusions from the data they offer.
Divergent evaluation methodologies employed by these tools could potentially account for inconsistency in the data presented across these platforms. Here are a few factors detailing why the data presented in Wingify might contrast with that found in Google Analytics (GA):
Discrepancies Due to Configuration
These are the discrepancies that arise due to the lack of configuration parity maintained in both applications, which can be averted by exercising due diligence.
| Parameter | Impact | Resolution |
|---|---|---|
| Timezone and date range | The report data will be presented in accordance with the configured time zone in the respective tools or applications. Thus, if the timezone is different between the tools, the data will differ accordingly for the specific date range. For example, if GA is configured with PMT and Wingify is configured with IST, there will be a corresponding mismatch in the reporting for the specific date range owing to the timezone differences | Ensure to keep the time zones similar on both platforms and then check the numbers for the same date range. Refer to the steps mentioned in Wingify and GA articles to manage your timezone settings, respectively |
| Cookie consent | The differences in the configuration of cookie consent would lead to differences in visitor count and subsequently impact the metrics and other dependent parameters. For example, keeping Wingify in the strictly necessary cookie category while keeping GA as an optional one will execute the code snippets at different triggers, thereby impacting the tracking | Ensure that code snippets for the respective tools are configured under the same cookie consent category so that both tools will track the visitors on the same consent condition for uniform visitor tracking |
| Tracking code implementation issues | The tracking of visitors relies on the tracking code implementation. Pages without the tracking code won't be part of the results. For instance, a scenario where Wingify’s SmartCode is installed only on specific pages while GA code is installed site-wide could lead to divergent data | Ensure that Wingify tracking code / GA code is installed across all the website pages where tracking needs to be done. This would ensure that the data is tracked consistently across all the website pages by both tools |
| Filtering and segmentation | The difference in filters, segment conditions, or campaign trigger configuration could lead to data distinctions. For example, GA may exclude specific IP addresses or track only certain pages, while Wingify may include all of them or vice versa | Ensure that similar segment conditions, filters and triggers are applied across the tools. If you are tracking only desktop visitors in Wingify, ensure to filter the respective device type in GA as well. Similarly, if specific IP addresses/locations are excluded from GA, ensure to do the same in Wingify campaigns as well so that data is tracked for the same cohorts. Additionally, check if you have applied any campaign trigger in Wingify and try to add the same event condition to your GA report. Ref: Using Segmentation in Wingify How to Exclude IP Addresses from Wingify Tracking? |
| URL / Pages Configuration Issues | The tracking of visitors in Wingify completely relies on the URL/ Pages implementation in the campaign. Pages that have been included in the campaign will only be tracked in Wingify. Tracking will not be done on the URLs which have not been included in the campaign. For example, a scenario where Wingify targets specific pages while GA tracks the entire site could lead to imbalanced data interpretation | Ensure to fetch the results for the same set of URLs amongst both the tools. Ref: Using URL Patterns in Wingify |
| Changes in Campaign Course | Altering the campaign settings, such as the campaign URL, including an excluded URL, flushing the campaign data, and starting and pausing the campaign multiple times could possibly lead to disparity in the resultant numbers. For instance, if you start a campaign in Wingify on 1st August and then pause on 10th August. And start on 15th August again. This would not track the data in Wingify between 11-14 August as the campaign was paused. But GA will still be tracking the data as the campaign pause does not apply there | Try to run a campaign after carefully considering all the factors from your hypotheses to prevent altering the campaign later. If a change (like URL configuration, data flush, etc.) in a campaign is much needed, pause the existing campaign, clone the campaign and start the cloned campaign. Now, you can compare the data of the cloned campaign with that of GA for the same date range. If the campaign was paused in Wingify for some duration, ensure to apply the corresponding date range in GA before checking the data |
Discrepancies Due to Operational Differences
These are the discrepancies that arise due to the difference in the functionality of the applications. These differences should be noted, and the results should be weighed accordingly rather than directly comparing them with each other.
| Parameter | Impact | Resolution |
|---|---|---|
| Sampling | GA uses data sampling for reporting on large data sets. Therefore, if your website has a large amount of traffic, the numbers you see in GA might be based on a sample, whereas Wingify test campaigns report on all visitor data | You can check the sampling status in GA, as shown below and confirm if GA is showing the data for 100% of the audience or the sampled audience. |
| Session Handling | Wingify tracks visitors, whereas GA tracks sessions as well as visitors. A session in GA ends after 30 minutes of inactivity and at midnight. For example, if a user interacts with the website after 30 minutes of inactivity, the session count increases, while the visitor count remains unimpacted | Ensure to check the unique visitors' data in GA. You can use Total Users or Users as a metric and then compare it with Wingify to confirm if the numbers are comparable. |
| Delayed Reporting | GA might consume up to 48 hours for reporting, whereas Wingify provides real-time numbers | You can do historical report comparisons by viewing the data corresponding to the day before the current day on both platforms. For example, for a campaign that has been executed from Aug 1 to Aug 31, you can set the date range from Aug 1 to Aug 30 on both Wingify and GA and then check the numbers |
| Page Load Issues | Any hindrance in the loading of GA or Wingify JavaScript codes can result in discrepancies. Partial page loading due to errors or slow connections may affect proper script firing for either tool | Run frequent checks on your website to ensure it is free of page load errors |
| Control Showing More Visitors in Wingify for a Split Test | If a split campaign is running and GA is installed, GA could log a visitor for the control page before the redirection to the variation page (for both Synchronous and Asynchronous versions of Wingify SmartCode), showing a discrepancy in the visitor count. | To solve this issue, you can execute the GA code on the Control page/s based on a custom code. The custom code lets Wingify execute on the page before GA. For more information on the custom code and how to apply it, refer to the solution provided in How to Implement Event-based Redirection for Split URL Tests? |
Discrepancies Due to Browser Settings
These are the discrepancies that may arise due to visitors’ browser settings, potentially influencing differences in reporting.
| Parameter | Impact |
|---|---|
| Ad Blockers | Visitors using ad blockers or privacy tools could hinder proper tracking by Wingify or GA. This blocking might not always be consistent across the tools, leading to discrepancies. There might be certain ad blockers that might interfere with specific tools. Thus, there can be a small discrepancy because of these settings, leading to a difference in the overall data comparison |
| Cookie settings in visitors’ browsers | The tracking efficacy of Wingify and GA is directly influenced by the cookie settings in the visitors’ browsers, such as disabling third-party cookies and Do Not Track (DNT) settings. Nevertheless, these tools exhibit varying effects because of this configuration disparity |
Discrepancies Due to Divergent Conversion Criteria
Differing goal conversion definitions between GA and Wingify can lead to corresponding variations in the results. It is significant to note that the options provided by these apps for defining conversions tend to have moderate to larger differences.
| Parameter | Impact | Resolution |
|---|---|---|
| Differences in conversion tracking mechanism | The conversion tracking mechanism can differ for Wingify and GA. For instance, a page visits goal in Wingify and GA can show different results. A page visit goal in Wingify would be tracked only after a visitor becomes a part of the campaign before arriving at the goal URL. Whereas, GA would increment the conversion number as soon as a visitor lands on a goal URL | Always understand the rationale behind the created goal and replicate the exact logic in the other tool. For instance, a page visit goal in Wingify can be checked in GA by creating a page sequence like this: Page → Contains → Campaign URL followed by Page → Contains → Goal URL This will actually create the same flow for the goal as in Wingify |
| Differences in the goal trigger condition | Any deviation in the goal trigger condition could cause a fluctuation in the numbers. For example, if a form submission goal is to be recorded as a conversion in Wingify, the same event should be tracked in GA as well. You can ensure to create goals basis the exact same event in both the tools to get accurate results. | The trigger condition for the goal should be consistent across the apps. For example, If you are creating an event via GTM, which will be executed on successful form submission, try to track the same event in Wingify. You can create a custom conversion goal in Wingify and execute it on the same GTM event. This would ensure that the goal would be tracked on the basis of the same trigger condition across the tools. Ref: How to Implement a Custom Conversion Goal in Wingify? |
By acknowledging these factors, you can better understand and manage the differences between Wingify and Google Analytics data, or any other third-party tool for that matter, leading to more accurate and insightful conclusions for optimizing your website's performance.
Note: In general, the expectancy of the data discrepancy between the tools lies around 10-15%, exceeding which it is recommended to reach out to Wingify Support.