## Days in the Month Bias for Web Analytics

One variable often overlooked that causes fluctuation in Month over Month analysis in Web Analytics data (and I suppose other sets of data) is days in the month. February is a prime example where you go from 31 days in January to only 28 in February (except leap years) resulting in an apparent 9.7% loss in traffic.

Below is a chart of assuming steady traffic, meaning the exact same amount of traffic every day for the entire year. See how wildly it swings purely due to the number of days in the month? This is important to keep in mind if you are using M/M analytics.

Use the below numbers as a reference to better understand the month-by-month day count analytics bias to help you better explain your monthly reports:

• January: 0.00%
• February: 9.68% loss (6.45% loss during leap year)
• March: 10.71% gain (6.90% gain during leap year)
• April: 3.23% loss
• May: 3.33% gain
• June: 3.23% loss
• July: 3.33% gain
• August: 0.00%
• September: 3.23% loss
• October: 3.33% gain
• November: 3.23% loss
• December: 3.33% gain

One other variable that may be overlooked is the line-up of days in the month. For some this may be the number of weekends in the month, for others it may be the number of Mondays.

## Long Tail of Search

Finally some solid evidence showing how long the long tail of search really is! Having worked for some big high-traffic sites, I was always discouraged with the underestimation of the true length of the long tail in other public reports. Finally I did my own research and it was published on the Hitwise blog:

Sizing Up the Long Tail of Search

Here’s a sneak peak:

“After great dissatisfaction with the existing research, which I felt vastly understated the true size of the long tail, I decided to do my own research…There’s so much traffic in the tail it is hard to even comprehend. To illustrate, if search were represented by a tiny lizard with a one-inch head, the tail of that lizard would stretch for 221 miles.”

Understanding the long tail and how to target it from an SEO standpoint is no simple task. I hope this article sheds some light on how important long tail traffic is.

In my experience, I’ve ranked for head terms and I’ve ranked for millions of tail terms. I’d gladly trade in the head terms for a larger piece of the tail. A few companies have learned this, including the search engines, but they’d prefer you don’t know how much of a gold mine it really is.

## Possible Reduction In Spam

The NY Times reports that the largest spam gang on the Internet is being shut down, starting with their assets being frozen. Some key numbers shared in the article:

• This group makes \$400,000 a month
• They send 10 billion spam emails per day
• This group, at one point, sent out 1/3rd of all spam
• 90% of all email people receive is spam

If these numbers are true, then:

• The group made 1/7500th of a cent for each email sent (the only cost-effective way had to be sent from unknowingly affected computers)
• Email users should expect a 33% drop in spam, and an 44% drop in overall incoming email volume.

I wish it were true, but I’m skeptical that we won’t see such drops. Unless the penalties are extremely harsh, other spammers will step in to get a piece of the newly available spam pie.

## Omniture Buying Visual Sciences for \$394 Million

Say it ain’t so. Omniture (Nasdaq: OMTR) is buying Visual Sciences (Nasdaq: VSCN) for a reported \$394 million. The combination of the two best-of-breed analytic providers can’t be a good thing for companies using web analytics solution providers.

Omniture states that they will rapidly and grow their technologies, but I don’t see a near monopoly being a good thing for most companies. Competition is good. I’ve been a customer for both companies and felt they really were by far the two best offerings in hosted analytic solutions.

It will be interesting to see if regulators allow the purchase because it feels like it will be too close to a monopoly to me. I assume Visual Science stockholders will approve the purchase as the company has been riddled with problems, losing many key employees to Omniture. The acquisition is expected to close in mid-2008.

Congrats to Omniture. This news shows just how strong Omniture has become, especially after purchasing Offermatica last month.

## Detailed Google Search Referrer Data

Found some interesting nuggets when I decided to narrow in on Google referrer data (as reported by Omniture) from one particular high volume keyword.

The word was “lasagna” and when I dug into the Google data, I noticed some interesting things. Google shares the following data in the referrer URL. I compare each search type to the standard “lasagna” search in google (without quotes) to protect the actual traffic volume for the high-ranked website.

Standard lasagna search: 100%
(this is the search I base the rest of the data on)

(this was much higher than I anticipated – people probably ignored the “g” in lasagna).

Lasagna search: 8%
(I guess some people figure capitalizing the first letter will get them better results)

lasagna_ : 4%
(the underscore denotes a space after the search term – I guess some people can’t help but drop their thumbs down on that nice big spacebar)

lasagna search, but clicked search button: 40%
(looks like most people hit enter, but some take the time to click the search button)

standard lasagna search via Firefox: 19%
(firefox users continue to grow and Google likes tracking them)

standard lasagna search via iGoogle: 6%
(looks like some people are using iGoogle as their homepage)

UK standard lasagna search: 9.5%
Google UK misspelled did you mean correction: 34.4%
Google UK lasagna search, but clicked search button: 2.5%

Looks like our friends from the UK need to work on spelling. Misspelled version is 4 times more common than the correct spelling!