23.05.2018
Semalt Expert: Eliminating Referral Tra c
Many e-commerce companies are mostly on the lookout for their data reporting since the majority of websites are crowded with lots of activity. Currently, many referrals are posted on websites, which should be identi ed and eliminated. It is therefore important to be able to identify these referrals by following the list of recommendations offered by Julia Vashneva, the Senior Customer Success Manager of Semalt.
Most referrals sound too good to be true It is almost impossible for traf c to land on a website by chance unless it goes viral or is picked up and spread by a third party. The way to go about it is to check the last Analytics report and identify any signi cant change. If this takes place, the chances are that the data is inaccurate. https://rankexperience.com/articles/article1402.html
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Visit the referral link Once you identify a referral link, you should click it. If the website that opens up after clicking on the link redirects you for example to a legitimate business entity such as an electronics shop, the chances are that the referral is a part of a marketing strategy.
Half-live tra c Most traf c has a half-life that lasts for a few days. An analysis of the traf c should be carried out keeping in mind that things that go viral almost do so in a similar pattern. Traf c that has gone viral often fades away with time.
Non-human tra c It is essential to nd out that non-human users generate your traf c. Natural traf c does not increase over time and then gets cut off. The bounce rate is the best way to determine the nature of the traf c. For instance, a one hundred or zero percent bounce rate. Also, both a one hundred or a zero visitors rate indicate that the traf c is not natural.
Use of secondary dimensions These dimensions can be useful in validating the ndings. In addition to high bounce rates and percentages on new visitors, it is important to accumulate more evidence while con rming the validity of traf c. This can be done using secondary dimensions.
Blocking unwanted tra c This should be carried out immediately you realize that you have bad data on your Analytics Account. Traf c should be ltered out if the following indicators are detected: If there is a non-human traf c on the Analytics top ten sources. If more than one percent of the traf c is a traf c originating from bot sources.
Filtering the tra c The traf c can be ltered by visiting the Google Analytics account and selecting the Edit Filter section. This should be followed by Filter name, Filter Type, Exclude and the Field Pattern.
Application of an advanced segment
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An advanced segment should be created to block suspicious traf c. This can be done on the Google Analytics Account. An alternative method is installing Block Russian Segments, which can be accessed at the Google Analytics Solutions Gallery.
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