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However, I disagree that stats are useless for anything other than measuring server load-- to assert that relative importance of pages can't be inferred ignores probability. Probability does not require exactness, but it does require logic. The suggestion that one visitor might go to the same page 400 times, for example, is extremely unlikely, much less month after month after month. Likewise any suggestion that pages indicating more visits might be cached less often than those indicating fewer visits is illogical.
As I see it, because of caching, it's a certainty that log statistics undercount actual visitors-- the author glossed over this overwhelming probability by suggesting 1 person could visit a single page 400 times. Sorry, but that example is just not realistic.
I don't think the author was suggesting that. If I'm grabbing the part of the page you are refering to, what he is suggesting is that you can infer AT LEAST one user hit the page. Perhaps one of them hit it 20 or so times. You can't infer all 400 hits came from 400 different people.
<<If by minimum you mean "at least one" then yes.>>
In purely mathematical terms, his is a true statement-- you can't know that any more than one person visited. My point was that, considering probability, this scenario is extremely unlikely. The author uses this premise to justify his conclusion that usage statistics are only useful to understand server load and nothing else, when really the conclusion should be (I think) that usage statistics are useful to calculate server load exactly, but that some other useful, informative, decision-feeding measures can be derived inexactly.
Maybe I read it wrong though-- it wouldn't be the first time. The piece did seem a little harsh and maybe that affected how I interpreted the author's words.
In any case, I'd be interested in a statistical analysis comparing cookie-based visits to IP-based visits for a large number of pages. Anyone here know of such a comparison?
Overall, the article seems a bit gloomy. We use logs stats for:
1. Checking up on what pages/sites are linking to us
2. Relative growth in popularity of certain pages over time. (We disagree with the ustor here that the stats are useless on this point. They are flawed but still indicative.
3. Rough unique visitor hits, (also aware of cacheing probelms)
4. Agree that actual hits are useless. We all know that. But using these stats are not much worse than the "subscription" or "readership" frigures used for years
in traditional publishing as an accepted measure. They too are subject to enormous margins of error.
That said, most of our hits come from spiders and hits to our XML news feeds, emal harvesetrs etc etc.. The actual pages "read" is really an unknown. People claiming "page reads" need to be asked how many are coming from these automated programs, how many of these are actual content (and not auto loading pages, pages with no or little content etc.)
Web stats don't even begin to do what we'd like them to do.
Bentler you say,
> As I see it, because of caching, it's a certainty that log statistics undercount actual visitors
Wait a minute--what's all this about visitors? The author cleverly did not use the word 'visitor' once in the document. And for good reason! The term 'visitor' has no good definition in terms of web-stats. When you're talking visitors, then the situation gets even worse, unless you have some special mechanism to track your users like generating a unique session ID for them.
Suppose you see that 10,000 requests came in to your server for page xyz.html. Of these requests, there are 7,000 unique ip addresses. You have no idea how many real visitors saw that page. It might be less than 10,000 ... or it might be less than 7,000 ... or it might be over 20,000. In theory, the true number of visitors could be as little as "1" and as many as "the population of the earth." How's that for an error factor?
In the case of visitor tracking you have other factors that effect it the other way, e.g., proxy servers. One one hand you have 100 people who appear, to your server, as a single user. On the other hand you have a 1 person who appears, to your server, to be 100 people. So in the end, you don't even know if your webstats are above or below the the truth.
He wanted me to sign an affidavit saying something like "The site averaged 9,820 visitors per day during 1999" as being "absolutely 100% correct in my professional opinion."
I told him, "no way--that figure could be totally false." Then he suggested that we modify the number, so that it reads "9,820 (+/- 5%) per day." I told him, "still no way. you don't know whether to say 5% accuracy or 25% accuracy, you just don't know." That brought up the question: with what accuracy do you know for sure that your visitor count is correct?
The site owner, no doubt, concluded I was just being obstinate. "How could this guy be right," he thought, "if he was, then these companies like Webtrends are just selling snake-oil?" Snake oil indeed, the kind that can grow hair on a turnip.
But it's only dangerous snake-oil if you place your faith too deeply in them. If you understand what the software is really doing, and know which portions of its output to take with a grain of salt, then it's quite useful information.
Usually it's about 60% of what Webtrends reports.