It’s also important to test the Referral Exclusion List under Testing View, or a view created for the purpose of preserving your current collection methods. This feature filters referral from your results, starting from the date of application. However, this filtering doesn’t impact the previous results and website data. You can filter any suspicious traffic or traffic coming from a bot traffic source from our results by using this feature. To filter bot traffic from your GA, consider four options:Ī popular way to exclude bot traffic referral sources from analytics results is the Referral Exclusion List. For example, Hostname, Network Domain, City, Campaign.Īny website without your website's hostname can be defined as bot traffic.Īn example of some bot traffic sources is:įour options to filter bot traffic from GA Step 3: If there’s referrer spam that disguises itself, use the Secondary Dimension option to search for different options. If a 100% bounce rate has a visit duration close to 00:00:00, this traffic may be bot traffic. Use different metrics such as Bounce Rate, Average Visit Duration, Sessions and Users. Step 2: Examine the traffic sources in the source list you think is suspicious. The traffic from a source called '' is an unknown source and looks suspicious. In the referral information on this screenshot, we can see the visits from various sources. Then browse the traffic distribution by choosing a wide date range. In this section, you can see various referral sourced visits and referral information.ĭo you know all the listed sources? Examine them in detail by clicking the Show Rows option at the bottom of the page. Click Referral in the Default Channel Grouping list. Step 1: In the Google Analytics Master View section, select Acquisition from the left side column and select All Traffic and then Channels. Three steps to identify bot traffic in GA Make sure that the Bot Filtering box is ticked in this section. To view this option, go to Admin and then View Settings in Google Analytics. This option filters many bots that Google can identify as a bot or spider. Was there a special campaign or an activity that would lead to an increase in web traffic in March? If not, and the traffic is not internally sourced, it can be concluded that this traffic may be generated by bots.īefore starting this research, it is very important to check whether the standard Google Analytics bot traffic and spider filter is selected in the Analytics settings or not. There are also two other spikes that aren’t in the normal flow of traffic distribution. The screenshot below shows an increase in traffic. You should also set up alerts that notify you automatically when a threshold is reached. Detecting suspicious activity in GAĭo you review your web traffic and analytics results on a daily or weekly basis? Examining your analytics results regularly and knowing your web traffic and traffic sources can help you identify bot and spam traffic. Doing this will help you make effective data driven decisions. More importantly, it’s vital for your business to be proactive in detecting bot traffic, and then to filter out bot activity. It could also have an impact on overall business performance. This traffic can cause misleading results in your web page data and Google Analytics reports. Bot traffic is the name given to non-human traffic and traffic created by various spiders and programs.
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