As a full time web based professional, I am often interested in page rankings, site traffic, and other forms of analytics data. While I use the ever popular Google Analytics and SquareSpace Stats packages for my personal blog, I often want to know information about my site that isn’t given there. Furthermore, I am often curious about other sites in my area (technology, food, blogging.)
Recently, I was introduced to a new tool called SiteTrail that gives users an incredibly amount of information about any domain. You can learn about a site’s social media prescence, their SEO, and even see an analysis their content, as well as seeing a break down of their traffic. Traffic is devised by country of origin, as well as into daily, monthly, and yearly visitors.
On top of al the expected features that I listed above, SiteTrail gives you something that I find pretty unique. It will use an algorithm to computer the approximate amount of advertisement revenue earned by a site. It will then give you an approximate value for a site, given that it were to go up for sale.
While the information that SiteTrail gives is unique and interesting, I am not sure of a practical use for some of it. Most of what is given is pubically available anyway, so wants the purpose of going here? Maybe if I was a more competitive website owner I would find a better use for it. As it is, my blog doesn’t make me any money right now, and I’m okay with that. I don’t think that knowing how much another technologist’s blog earns in revenue would give me any edge.
As far as I can see, SiteTrail has taken the idea of analytics and given it a new face. It provides a single point for learning vital statistics about a website, and it does it for free. The information it provides is interesting, and potentially useful for the right person.
If you can think of a time when you would use SiteTrail, or if you have a suggestion for a feature I missed, let me know in the comments below. The team at Techie Buzz always likes to hear from you.
Score: 3.5/5, for changing the face of analytics, while being only vaguely useful.