Relevant website traffic is very different from your regular traffic. The difference is in the confidence that the resource is visited by the right audience. And since web analytics of clicks is largely anonymous, a deep understanding of visits is extremely important and consists of many factors. Here are the aspects to consider.
New or repeat clicks: Did visitors know about your brand beforehand or were they actually clicking for the first time?
Geolocation of traffic. If you work for a specific region, for example, the Moscow region, is the majority of traffic there?
Most visited pages: Are pages with product information or less important content visited more often?
Bounce Rate: Are your visitors leaving after viewing just one page of your site?
Traffic source: What channels are new visitors chile phone number data coming from? Are you successfully promoting new traffic channels?
These aspects are revealed by cohort analysis . With its help, narrower segments of varying degrees of relevance are created.
Building brand awareness is the beginning of your lead generation funnel, so it’s important to make sure you’ve accurately measured the top of your funnel. The concepts above are easy to test in any web analytics system. Below is an example of building a segment in Google Analytics.
example of building a segment in Google Analytics
The country segment is used to measure awareness. It is the top-level segment that brings together all awareness efforts into a single metric. It can be further segmented in branded campaigns launched across specific channels or for specific services.
In the above segment, brand awareness is defined as traffic:
From USA (target market);
Appearing on service pages (illustrates interest);
No churn (meaning visitors viewed more than one page).
This definition is quite limited, but it works. After all, marketers are not interested in just any visitors, but those whose behavior is related to brand awareness.
With this approach, your web analytics measuring awareness will move from unskilled high-level metrics to actionable segmented metrics.