GA Data doesn't match TapClicks
Check your assigning
There is a possibility that you may have access to multiple similarly named Properties or Views and you are not viewing the correct data in the GA UI.
It is also possible that you have assigned the wrong View. To list Views for assigning, go to GA Account Property Name View Name and make sure that you are looking at the right data in the GA UI.
Check for multiple assigning
If the values you are seeing in the Dashboard are greater than expected, it is possible that you are combining data from more than one assigned. To crosscheck, build a Data Grid widget with Analytics Property and Analytics Profile (AKA View) as Group-By columns:
In this example, you can see that multiple properties/profiles are contributing to the data, so the total value cannot match a single GA View. Go through the list and delete unwanted assigning, or add Dashboard/Widget Filters to see the data that you are looking for.
The data might not match the UI, but is probably correct.
The GA API is very complex and powerful. As a result it does not behave intuitively in some situations like:
- Data Sampling: Under specific conditions, the GA API will down-sample large data sets in order to ensure a fast API response as per the algorithm. When TapClicks fetches your data, all efforts are made to get the full, non sampled data set. If the API returns a sampled report, TapClicks will reduce the date range until non sampled data becomes available. So, the data you see in Dashboard is never sampled unless TapClicks gets non sampled data when requesting reports day-by-day. As explained earlier, this is the smallest range supported by the API. However, when you view data in the GA UI, you may be shown Sampled Data, and this can cause marginal discrepancies with the Tap 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 will be captured for all users and sessions. The GA API returns the best data set but will exclude sessions for which the requested fields are unavailable. Each GA data view requests a specific combination of dimensions/metrics, and if you are viewing data in the UI for a different combination of dimensions/metrics, it is likely that you will see discrepancies with your Tap data.
For example, TapClicks Demographics data view stores data from a report that includes the User Age Bracket and User Gender as dimensions. If you view the standard Age report in the GA UI, you are viewing data where Age is a dimension but Gender is not.
For some of these sessions, it is possible that the Age of the is known but Gender is not. The report TapClicks captured in the Demographics data view will only include sessions for which BOTH Age and Gender were known. The data TapClicks captured was not incorrect, it was just a different data set than you are viewing in the GA UI.
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 TapClicks requests for an apples-to-apples comparison.
There’s good news though! If TapClicks standard data views do not match your needs because of an interaction of dimensions/metrics, TapClicks can build you a custom DIY Dataview with only the fields you want to view with Date.
Please refer to the next section Date Interactions for more detail
- Date Interactions: When you view data in the GA UI, 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 GA API for data, the request is always for the by date data. This can affect the values returned from the API under certain 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 in the UI, you may see more sessions because the privacy threshold is not triggered without the daily breakdown.
- When you view Users in a GA UI report, you will see the count of unique Users in the requested date range. If you break down the same report by date, the User's 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. TapClicks gets the data broken down by date, the Users metric will most likely not match the GA UI value.
- Goals Data must be handled with care
GA Goals provide a powerful way to track custom conversions on your websites. However, this results in complex data, which can lead to incorrect results in TapClicks widget. Any widget built from a Goals data view must either filter for one specific Goal or Group by Goal:
If not, 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 like Sessions, which must be duplicated for each Goal. For more clarity, look at how TapClicks store this data:
Please note that each Goal can have a different value for configured metrics (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. As you know, any number of Goals can be Started, Completed, or Abandoned during a Session. We need Sessions on each row so you can view the Goal 3 Completion Rate (Completions/Sessions * 100%). But if you don’t filter or group-by Goal, all these duplicated Sessions get added together, and your widget will display erroneous results.
The bottom line is, these Goals data views are not like other GA data views. They are meant for generating accurate data for individual Goal.
Using Google Analytics UTM Codes
Your UTM Codes are contained as a part of additional data views in the Google Analytics feed. Take a look at your Data Source to see what metrics are available within your dashboard. If you do not see what you are looking for, definitely reach out to your Account Manager or email@example.com to learn more.
|UTM CODE||TapAnalytics Label|
|utm_campaign||Analytics Campaign Name|
How do I connect Google Analytics Segments?
Items we will need to have in order to process the request:
- Your instance (the dashboard URL)
- The name of the Segments(s) you want to use - Please note you can have a max of three
The steps we take to connect Google Analytics Segments:
- We enter your request to the internal team
- The integration gets enabled in your dashboard - This happens once a week on Fridays
- Once it is turned on you will need to enter your credentials - DO NOT MAP ANYTHING!
- After the credentials are entered our developers will add coding to the backend to establish the connection to just the filtered data
- Then you will be good to map your clients
Why do my totals on the Google Analytics Demographic Data View look different than what I see on the Main level?
This is because Age and Gender columns are not always defined by on GA side. The API only ever returns data where these fields are known, it does not support an undefined type value. For this reason, the values on this level may be a bit lower when the Age and/or Gender is unknown.
Google demographic data on TapClicks
When TapAnalytics pulls data from the Google Analytics API, a date is always applied to that data set. Applying a date ensures that data is obtained for each day in range. If the request is made for the whole month and if the number does not trigger the data threshold for a particular date, the response will not carry any data for that date. After applying the date, the threshold for every day is triggered for a comparatively lesser number and the response has some useful data. For this reason, the numeric values in the Google Analytics feed that pertain to Age and Gender may appear somewhat lower than other data views.
For example, you might see that a specific page from Google Analytics has 40 page views for the Age Group 65+ for the entire month, let's say June. When TapAnalytics requests for June data, there is an additional granularity applied to get data by day. So the response might show that the specific page has 12 page views for Age Group 65+ on one day in June and 17 page views on another day in June and no additional daily rows for the Age Group 65+. This means that for the other days in June, there are not enough page views to meet the Google Data Threshold and those rows are excluded from the response. So, TapAnalytics will show 29 page views for 65+ Age Group for the month of June rather than a value of 40 page views for 65+ Age Group.
Please note that this is a system-defined threshold and there is no possibility for any change.
How Google samples demographic data
Google has the right to withhold certain data sets from the response if the result for a specific demographic combination is smaller than the Google Data Threshold. So, while requesting data from Google Analytics, Google can withhold some data and send the rest. As a result, any API user cannot infer the performance of specific demographics or interest groups.