Before you begin: This guide helps you understand why data in TapClicks doesn't match data in Google Analytics and what your options are to correct it.
Check Your Mappings
|NOTE: One possibility is that you have access to multiple, similarly-named, Properties/Views and you’re not viewing the correct data in Google Analytics (or you mapped the wrong View).|
1] Navigate to correct view in Google Analytics by going to Account-->Property-->View.
2] Make sure you're looking at the correct data in Google Analytics.
Check for Multiple Mappings
|NOTE: If the values you’re seeing in a TapClicks Dashboard are greater than what you’re expecting, it’s possible that you’re aggregating data from multiple mappings.|
3] Build a Data Grid widget with Analytics Property and Analytics Profile (i.e., View) as Group-By columns.
4] Look to see if multiple properties or profiles are contributing to the data. You'll know if the total value does not match a single view.
5] Delete unwanted mappings or add Dashboard/Widget filters to view the data you're looking for.
The Data Doesn't Match but is Correct
|NOTE: The Google Analytics API is very complex, and as a result, behaves unintuitively in some situations.|
Data Down-Sampling: Under certain circumstances, the Google Analytics API will algorithmically down-sample large datasets in order to ensure a fast API response. (See Google’s explanation here.) When TapClicks fetches your data, we do everything we can to get the full, unsampled dataset. If the API returns a sampled report, we reduce the date range until we get unsampled data. So, the data you see in TapClicks is never the sampled dataset, unless we could not get the unsampled dataset when requesting reports day-by-day (this is the smallest range supported by the API). However, when you view data in Google Analytics, you may see sampled data, and this can cause marginal discrepancies with TapClicks data.
Excluding Invalid Data: Google Analytics collects data for hundreds of dimensions and metrics when tracking your website traffic. However, there is no guarantee that the dimensions/metrics you are interested in is captured for all users and sessions. The Google Analytics API returns the best dataset it can, but will exclude sessions for which the requested fields are unavailable. Each one of our Google Analytics data views requests a specific combination of dimensions/metrics. If you are viewing data for a different combination of dimensions/metrics, it’s likely you will see discrepancies with your TapClicks data.
As an example, TapClicks Demographics data view stores data from a report that includes User Age Bracket and User Gender as dimensions. If you view the standard Age report in the Google Analytics, you are viewing data where Age is a dimension but Gender is not.
For some of these sessions, it’s possible that the User Age was known but the Gender wasn’t. But the report TapClicks captured in the Demographics data view only included sessions for which BOTH Age and Gender were known. The captured data was not incorrect, it was just a different dataset than what you are viewing in Google Analytics.
Ultimately, the best single source of truth is the Google Analytics Request Composer. This tool allows you to request any valid combination of dimensions and metrics, so you can request the exact report we are requesting for an apples-to-apples comparison.
If TapClicks standard data views do not meet your needs because of an interaction of dimensions/metrics, we can build you a custom DIY data view with only the fields you want to view (see Date Interactions below).
Date Interactions: When you view data in Google Analytics, it treats the selected date range as a single block of data (unless you specifically request a monthly/weekly/daily breakdown). But when TapClicks calls the Google Analytics API for data, we always request the data broken down by date. This can affect the values returned from the API under the following circumstances:
- Small samples of Demographics data may be altered to protect individual users. If you don’t get very much Age/Gender data in a day, the API may exclude some or all sessions from an API response to prevent any possibility of identifying individual users. But if you view a larger date range, you may see more sessions because the privacy threshold is not triggered without the daily breakdown. (See Google’s explanation here.)
- When you view users in a Google Analytics report, you will see the count of unique users in the requested date range. If you break down the same report by date, the users metric will show the number of unique users for each day. So, if there are users who visited your site on multiple dates, they will be counted once for each date, and the total for the date range will be greater than the user count without the daily breakdown. Because TapClicks must get the data broken down by date, the users metric in TapClicks will most likely not match the Google Analytics value.
Handle Goals Data With Care
|NOTE: Google Analytics Goals provides a powerful way to track custom conversions on your websites. The result is complex data which can result in incorrect TapClicks widgets.|
6] If you built a widget from a goals data view, either filter it for one specific goal or do Group by Goal.
If you don't filter for a specific goal (or do Group by Goal), you will be aggregating the values from multiple goals. This is particularly problematic if you are viewing calculated fields that rely on a standard metric (e.g., sessions), which must be duplicated for each goal. The image below depicts how TapClicks stores this data
Notice that each goal can have a different value for configured metrics (e.g., starts, completions), but all show the same number of sessions. This is because sessions is a standard metric, independent of any configured goal. There are no “Goal 2 Sessions”. There are just sessions, and any number of goals may be started, completed, or abandoned during a session. TapClicks needs sessions on each row so you can view the Goal 3 Completion Rate (Completions/Sessions * 100%). But if you don’t filter or do Group by Goal, all these duplicated sessions get added together and your widget becomes incorrect.
In summary, these Goals data views are not like other Google Analytics data views. They are meant for looking at individual goals, and doing otherwise will result in incorrect data.