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| Behaviour data: intent |
Behaviour data: intent
Web users’ behaviour can indicate a lot about their intent. Looking at referral URLs and
search terms used to find the web site can tell you a great deal about what problems visitors are expecting your site to solve.
Click density analysis, segmentation, metrics that define the visit and content can all be used to gauge the intent of your visitors.
Web users’ behaviour can indicate a lot about their intent. Looking at referral URLs and
search terms used to find the web site can tell you a great deal about what problems visitors are expecting your site to solve.
Click density analysis, segmentation, metrics that define the visit and content can all be used to gauge the intent of your visitors.
A crucial, and often overlooked, part of this analysis is that of internal search. Internal search refers to the searches that users perform on the web site, of the web site’s content. While a great deal of time is spent analysing and optimising external search – using search engines to reach the web site in question – analysing internal search goes a long to way to determining how effective a web site is in delivering solutions to visitors.
Internal and external search data are likely to be very different, and can go a long way to exposing weaknesses in site navigation and the internal search itself, and can expose gaps in inventory on which a web site can capitalise.
For example, consider the keywords a user might use when searching for a hotel web site, and keywords that might be used by a the user when on the web site.
Keywords to search for a hotel web site:
Cape Town hotel
Bed and breakfast Cape Town
Once on the web site, the user might use the site search function to find out further information. Keywords they might use include:
Table Mountain
Pets
Babysitting service
Analytics tools can show what keywords users search for, what pages they visit after searching, and, of course, whether they search again with a variation of or different keywords.
Internal and external search data are likely to be very different, and can go a long way to exposing weaknesses in site navigation and the internal search itself, and can expose gaps in inventory on which a web site can capitalise.
For example, consider the keywords a user might use when searching for a hotel web site, and keywords that might be used by a the user when on the web site.
Keywords to search for a hotel web site:
Cape Town hotel
Bed and breakfast Cape Town
Once on the web site, the user might use the site search function to find out further information. Keywords they might use include:
Table Mountain
Pets
Babysitting service
Analytics tools can show what keywords users search for, what pages they visit after searching, and, of course, whether they search again with a variation of or different keywords.
