Mar 18, 2010, 11:21 by User Not Found

We have recently received inquiries  from several hospital or health systems Webmasters who want to know our opinion about Web sites like Alexa, Compete.com, and Quantcast.com. These  “third party web data providers” use proprietary algorithms to estimate the number of visitors on any Web site, and have become a major resource for many Web marketers. Let me start off by saying I am a huge fan of these sites. The possibilities for comparison are limited only by your imagination. Having a friendly disagreement at the ballgame about whose fans are better? Simply point out to your buddy that ChicagoCubs.com gets 4-5 times more monthly traffic than does ChicagoWhiteSox.com or StLouisCardinals.com. Following the Leno-Letterman ongoing ratings war on network TV? Type in nbc.com and cbs.com and you can watch the ongoing saga play out in cyberspace. Most of these 3rd-party data sites use server traffic patterns as the basis for their estimates. (Quantcast.com is unique in that it offers a script to download that will quantify the exact number of visitors, but still must rely on projections for sites that have not installed the script) With so many people using these sites, it begs the question: how reliable are these sites, and how useful are they to hospital/health system marketers? Using real data from Google Analytics, I was able to compare the actual number of Web visitors to three hospital Web sites with the projections made by Compete.com for a recent five month period. For my comparisons, I chose three different-sized organizations (one small health system, one large one, and one roughly in the middle) located in three different regions of the country (West Coast, Southeast, East Coast).

Large Hospital Sept        Oct       Nov     Dec       Jan Google Analytics     308830    338770   318100    272040  329780 Compete.com         195605    216997   260732    213240  229912 % Difference        36.7%    35.9%    18.0%      21.6%     30.3%

Medium Hospital Sept      Oct      Nov      Dec       Jan Google Analytics    53634    54202     55721    45422    54300 Compete.com         23149    33107     25873    16954    21079 % Difference          56.8%   38.9%     53.6%   62.7%   61.2% Small Hospital Sept        Oct        Nov        Dec        Jan Google Analytics  16278     16516     14293     13560     15765 Compete.com      6368        4940      4160        4509     6357 % Difference       60.9%       70.1%   70.9%      66.7%    59.7% My comparison above was hardly scientific. I only compared three hospitals using a single tool metric over a five month time frame. It was not always possible to line up the comparison periods exactly using the free version of Compete.com. If you ran this same comparison substituting Omniture or WebTrends for Compete.com, you would likely see differences, as all Web analytics packages vary in how they tabulate Web metrics. Nevertheless, it is clear from my analysis that the accuracy of 3rd party data is highly questionable. Reliablity does seem to increase the more traffic a site receives. This makes sense intuitively, as more data should lead to more accurate models. However,until someone can prove to me otherwise, if I were a Webmaster at one of the thousands of healthcare sites out there that get less than 100K visitors per month, I would be extremely reluctant to use a tool like this for any serious analysis. Fortunately, there are other options available. There is a free benchmarking tool imbedded in Google Analytics that, while it does not let you get very granular in your comparisons (all hospitals are looped into a single group), does have some value. You may also want to consider a free trial Greystone.Net Benchmarking, the program that allows users to make comparisons from data directly imported from Google Analytics and allows segmentation based on hospital size and specialty.  (full disclosure: I am the Product Manager for this service)  Perhaps one day the “hosted script” model employed by Quantcast.com will take off, while sites like Compete.com will likely continue to improve the accuracy of their models. Until then, however, be careful about relying on 3rd party Web data providers for meaningful comparisons. Unless, of course, you are able to prove that Cubs fans are better than White Sox or Cardinal fans, in which case these sites work just fine.