What is Visitor Insights?

 In Data-driven Marketing, Standard, Web Analytics

As our first post, we thought it would be appropriate to describe what the term Visitor Insights means. As you know, our personal backgrounds are from the field of Web analytics. As a user of a Web analytics solution, you can learn a lot about your web site visitors.

However, web analytics solutions do not give you the full picture. Web analytics solutions by nature tell you a great deal about your web site activity, but there’s a lot of qualitative data that they don’t capture. We feel that in order to gain a full understanding of your web site visitors, you’ll need these three pillars:

  • Quantitative data – this is the data that you get from your Web analytics solution. The solutions will tell you just about everything there is to know about your visitor activity on your site.
  • Qualitative data – what are your visitors thinking? Why are they on your site? Although web analytics give you some insight onto this, they do not provide the full picture. This is done using surveys and questionnaires. By asking some simply questions, you can get a wealth of information about your site visitors that typically wouldn?t be captured by web analytics.
  • Affinity & Benchmark data – when not on your site, what do visitors do? How do competitive sites stack up? This data can be made available in panel-based solutions such as Quantcast, Hitwise, comScore and others in this category. Although the data is often not completely representative of your entire audience, you can still learn a great deal from these solutions. Take some time for example to go to Quantcast.com and enter your Web site domain. Within seconds, you’ll get information about other sites visited by your audience and their demographics that can help you target more visitors to your site.

So Visitor Insights is about gaining a holistic view of your audience: their demographics, their browsing behavior, their likes and dislikes and their affinities. Of course, none of this matters if the data is not actionable. In other words, for each data point that you’re reporting or analyzing, you should ask yourself: “how is this actionable?”

Over the next blog posts, we’re going to cover different topics explaining these topics in more detail. In the meantime, we’d like to hear back from you as to what items should be covered in detail. Thanks for your feedback.

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