Google Analytics – Using filters
Google Analytics (GA) is a web analytics system that provides ample opportunities for analyzing and processing data about users’ actions on the site: where they came from, what device they used to visit the site, what pages they watched, how long they were on the site, what page they viewed last how many targeted actions were performed, which products were more often bought, at what stage of the purchase they left the site, etc.
It often happens that the diversity of data and reports does not help, but on the contrary is misleading. Consider GA’s capabilities that help weed out unnecessary and / or simplify data and create special reports — segments or filters.
The filter allows you to limit and change the set of data included in the view, and the segment is a set of data that does not change the source data. For example, using a filter, you can exclude traffic from individual IP addresses, retrieve data only on a specific subdomain or directory, or you can merge all users from a specific country or city into a segment, or buyers of certain products or visitors to a specific section of the site.
More details on the filters. Google Analytics has:
built-in filters that allow only to include or exclude traffic to the site, i.e. delete the data about the appeals that do not interest you;
custom filters with five parameters: Exclude, Include, Lowercase / Uppercase, Find and Replace, Advanced.
About what opportunities each of the above parameters gives you can read in the official Google Analytics help.
Filters can be particularly useful in organizing workflows. Consider the examples.
You have an online store and orders over the phone are made through the site. Filtering by IP-address will allow to exclude these visits, you will see only the statistics of online orders of real visitors to the site;
In the analytics you see in the report that the page http://site.com/catalog/ was viewed 5 times and the page http://site.com/Сatalog/ 4 times, but this is the same page. The Lowercase filter will allow you to set up correct data collection and it will be reflected in the analytics that the page http://site.com/catalog/ was viewed 9 times;
Your online store generates digital identifiers for categories or products in online orders. Using the Find and Replace filter, you can replace these identifiers with phrases and see in the analytics, not numerical values, but the names of categories or products;
You are only interested in data on visits from specific regions or cities. Filter by geographic location allows you to combine all visits from the specified regions or cities; The site has 2 different types of content. The content filter will allow collecting statistics separately for each one and, thus, analyze the behavior of two different types of site visitors.
Below we take a closer look at each of the listed filters.
The most important thing is to create several views of your site before creating Google Analytics filters: the original data profile without filters and the profile / profiles in which the filters will be used (thus, in case of incorrect configuration, the data will not be lost).
1. Exclusion of traffic
If your employees need to visit the site frequently or you have a list of site visitors that you do not need to be included in the reports, the filter Exclude traffic from IP addresses will help you to correct the statistics.
2. Translation of links in lower case
Google Analytics captures the URL data as it appears in the address bar of the browser. The presence of the same characters of different register in the same links slightly distorts the statistics. Linking is possible using a custom filter. Lower case.
3. Filter “Find and Replace”
This is a custom filter and it allows you to select any traffic parameter and replace it with the specified template. To do this, you must specify a filter field, a search expression and a new replacement expression. The search term must be regular, and any text can be used as a replacement.
using the Find and Replace filter, you can remove the main catalog from the reports. To do this, select the request URI field and enter the value ^ / directory / in the Search string field . In the Replace line field, enter the character /.
You can also use this filter to replace digital category identifiers with phrases.
For example: data about product categories look like:
/ catalog /? id = 11234
/ catalog /? id = 21234
The “Find and Replace” filter allows identifiers 11234 and 21234 to be displayed in GA reports by the name of the category of product that this identifier corresponds to (for example, 11234 – telephones, and 21234 – on smartphones ) .
This filter is useful for combining data — it can be used to combine statistics from two different host names, for example, www . site . com and site . com , i.e. exclude www and include all calls to the domain name site .com :
– Filter field: host name
– Search string: ^ www.
– Replace line: leave the field blank
4. Geographical filter
Google Analytics allows you to track visits from different regions not only separately for each, but also combining them. For example, you sell your products only in Kiev, Kharkov and Poltava. Using the filter by geographical location, you can view statistics only for these cities using the custom Include filter :
Similarly, you can filter by visitor region or country of visitor.
5. Content Filter
Visitors come to your site with a different purpose: buy, read a review, find out information, etc. For effective statistics and further analysis, these groups of people need to be divided. For example, you have a product catalog on your site with the ability to buy online, and there is also a blog with reviews of these products and / or interesting / useful articles for the products you sell, i.e. Potential buyers come to you who are already choosing a product and people who can only become potential buyers. By filtering these 2 groups of visitors by content, you can track, analyze and work with the data separately, depending on the tasks for each of the groups of visitors.
Please note that all filters have their drawbacks:
Data loss . When filtering, data about incoming calls in the view is changed, according to the type of filter. Therefore, it is important to ALWAYS leave the view without filtering;
It can take up to 24 hours before the filters are applied to the data;
Fields specified in the filter must be present in the address and have non-null values. For example, if the filtering is performed by the Host Name field , but this field is not in circulation (it is possible that the call was transmitted via the Measurement Protocol and the corresponding request did not contain the & dh parameter), then all filters on this field will be ignored and the call will be processed without filtering.
We hope that our recommendations will help to select the necessary data, weed out unnecessary and create the reports necessary for your business.