Hello, thanks for visiting - I hope that you will find useful information. but also leave a comment if you have any comments on the subject.
Endless rain and temperatures in the single digits have motivated me to my summer break, despite announcing, once again to publish an article.
This time it's about the mystery of the conversion rate, especially about how to assess a conversion rate at best and compare. This also raises the question how the optimal conversion rate looks like.
For all those who have special requirements for statistics in Google Analytics, there are the possibility to create custom reports. Through these reports, for example, the individually most important KPIs (key performance indicators) are presented in a clear, subsequently, you can can also automatically send the reports via email. This will let a lot of time saving, especially when one considers customers, supervisors, etc. must provide a regular reporting. Depending on the target can thus be reconstructed currently available in Google Analytics reports and extended with additional values or simplified and reduced to a minimum.
Such reports can be easily set up under the menu item "Custom Reporting" in Google Analytics. Drag and drop the required report may be compiled. There are the following fillable fields:
Measured data (blue)
The measured data are the values that are later shown as columns in the report.
Dimensions (green)
Given the dimensions, it is a value that will be shown later in the rows. By sub-dimensions it is possible to nest these values. In the subsequent report will be called when a value click on the same table with a changed line content.
Tabs (gray)
About tabs can combine multiple reports, similar to individual tables in Excel.
In addition, there is a Google term definition of all available statistical values, this can can be very helpful. Because who knows right away the difference between take-offs and exits.
So much for the relatively straightforward theory is interesting but the whole thing now in practical use. In addition I have compiled some potentially useful reports.
Landing Page Performance
This is a report in which the performance of different landing pages can be compared. By inserting the exit side as a base for click on the entry page name and the exit side is visible.
Report: Landing Page Performance
Adwords Campaign Reporting
In this report, I have figures for Adwords campaigns together. You can click here beautiful display of the group about the campaign, the campaign content campaign by position.
Report: Adwords Report
Quality of visitors to referrer
The last example is a slightly reamed version of referrer statistics. Here are some interesting values are given in addition.
Report: Referrerqualität
They were now only a few examples as an inspiration and as always, applies here, that you can not customize to their own needs. Without eCommerce Tracking makes it to have little sense to spend, for example sales, etc. But when I'm always on the lookout for useful evaluations ... feel free and leave a comment with your favorite reports. Glad about comments and suggestions.
Today I did want to incorporate a little tip for all the multiple Google Analytics accounts on the same page. After the first account was then integrates all of the following codes must be modified a little.
First we will look at the first JavaScript call. This must be unique and therefore apart from all the codes are removed from the first.
<script type="text/javascript"> var gaJsHost = (? ("https:" == document.location.protocol). "https://ssl": "http://www."); document.write (unescape ("% 3Cscript src = '" + gaJsHost + "google-analytics.com/ga.js' type = 'text / javascript'% 3E% 3C/script% 3E")); </ Script> |
Then comes the actual call tracking, which triggers the counting. Here, the variable "pageTracker" unique. Therefore, we are in this second Code in "pageTracker2" change. Note, the need for all calls, the second on the Code should be counted to be adjusted. It will look like this:
<script type="text/javascript"> try { pageTracker2 var = _gat._getTracker ("UA-xxxxxx-x"); pageTracker2._trackPageview (); } Catch (err) {} </ script> |
Now we need, if any, additional calls to manually trigger counts are adjusted. For example, if a click is generated manually via a JavaScript event or Page View.
Continued from Google Analytics filter out its own IP (Part 1)
Setting up filters
For those where the variant is to remain imprecise segmentation via the filter. Filters enable the exact IP address or a Range via Regular Expressions to specify.
Google Analytics filters to the summary page (where the various accounts are listed) will be established and administered. For this one clicks on the "Filter Manager" right below. The manager can then filter in the gray bar directly, a new filter can be created. In my case, I would now again awarded the title "Without Me". Select "Exclude all traffic from an IP address" and enter in the box underneath my Ip address: then in the Filter Type. This is important, that is set before each item by a backslash. , Like that 193 \ .0 \ .0 \ .0.
The points must be "validated" by the backslash as the punk would otherwise be interpreted as a regular expression. In this case, the dot stands for a wildcard matching any character can be replaced by any. But if one has a static IP address you have to make it no further thought. For users who want to filter out an IP range but this is interesting. Thus, the following statement on all IPs from 193.0.0.1 - 193.0.0.50 be excluded: ^ 193 \ .0 \ .0 \ ([1-9] | [1-4] [0-9] | 50) $.
When regular expressions are not entirely trivial, but - frankly, I also do not like t so special - Google provides a practical tool for exactly this purpose of applying available. Here you can generate regular lockout for an IP Range: IP Range tool from Google .
Filter set
After all this done so far has yet to the desired profile for the filter is effective should be selected. Then save the whole thing and still be managed.
Finally, it is true to say is that the filter should be well tested, since one can easily destroyed with false information, its data. Therefore, it is best to create something first time in a test account.
Following up on my blog still quite young not romp too many visitors, I have my own visits in Google Analytics does not attempt to take into account. Although the numbers are then a bit sobering but at least you get a better view.
There are two ways of tracking in Google Analytics to influence based on defined rules. Filters appear to offer similar opportunities or advanced segment, but have different advantages and disadvantages.
Filter
Advanced Segments
- Rule will apply to the collection of data
- Affects the representation of the data
- Filtered data can not be restored
- Data can be at will, depending on and hide
- Rules, such as IP range can be defined exactly or via regular expression
- Rule is restricted definable. IP address can not be defined as
Setting up custom segments
I am personally a flexible version that I can always turn to, rather in this case. Since then I take into account that the definition can only be done approximately, and the data are not exact.
The decor is very simple. Thus, all existing Segmentationsmöglichkeiten in Google Analytics can top right, under "Advanced Segments: All Visits" are retrieved. Here it is then also possible to create in addition to the predefined variants, a new segment.
Overview Advanced Segment
To create one is led to a page on which the rules by dragging and dropping can be easily clicked together. In my case I created a rule which is to identify as accurately as possible and exclude my visits.
Network Location> Does not match exactly> my provider
AND
City> Does not match exactly> my city
Setting up of segments
Depending on the provider and the larger city, the statement or a relatively accurate but also very vague norm. A user in Munich online is Deutsche Telekom is using this statement probably have its problems. For users in a corporate network that is designated as a Network Location in Google Analytics, but that is a good way.
Then only needs to be more of a name chosen for this rule. Here I have simply listed times "without me". Now I have the opportunity to present the statistics in Google Analytics only for the segment "Without Me" and lo and behold 30% of my page views I create for yourself ... but hopefully that will change soon. ;-)
How exactly it all be done via filters, I declare tomorrow, until then ... continue to filter out its own IP Analytics (Part 2)
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