Enter the ( SEO ) Matrix

There are two very commonly known things about search engine optimization (SEO).

1) Great, targeted content drives PageRank.
2) Google’s page rank algorithm is recursive.

Given how common this knowledge is, it’s surprising that so many Web sites haven’t put 1 + 1 together: Your pages earn a PageRank based on content and links, and then they lend that PageRank power to your other pages based on how you link to them.

In effect, your internal link structure may be causing your most powerful, highest-ranked pages to spread their PageRank weight across your entire site, instead of to the specific campaigns or initiatives you mean to support with those individual pages.

The takeaway: Instead of thinking of your SEO efforts as a collection of channels (FaceBook, Twitter, YouTube, and the obligatory blog) meant to drive content — think of SEO as a structured set of Content Tiers, each of which are built and interlinked to support your marketing and SEO objectives.

Enter: the SEO Matrix.

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SEM for Longer Time-to-Convert Businesses: How to Stop the Bleeding

I’m always surprised that you don’t see more direct marketers hired into Web analytics roles — they’re expert in a number of skills such as predictive modeling, experimental design, and statistical analysis that really turn the Web analytics role into a strategic source of business revenue. Along those lines, I wanted to give an example of how a tried-and-true direct marketing technique — using regression modeling to predict how likely each user is to convert — can allow media buyers and SEM managers to significantly reduce the amount of time it takes to determine which campaigns are winners and campaigns are losers.

Companies rely on pay-per-click and online ad buys to drive growth.  While buying clicks is easy, ensuring that individual campaigns are profitable – before significant losses have been incurred – presents a host of challenges to media buyers.  Continue reading “SEM for Longer Time-to-Convert Businesses: How to Stop the Bleeding”

How to identify real trends in user behavior

There is a perennial question in Web analytics:  “Are the numbers up?”

Certain web metrics can be highly variable on a day-to-day or week-to-week basis.  Daily Unique Visitors (UVs) and Daily Visits are just two examples of metrics that can change dramatically from one day to the next.  These big swings in day-to-day numbers can make it difficult for managers to tell whether their KPIs are really trending up or down.

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Using search engines to measure social behavior

Let’s start with a simple premise: The more often something happens, the more often people write about it.

Sounds reasonable, right?

Albert Saiz and Uri Simonsohn, in their article “Downloading Wisdom from Online Crowds,” demonstrate that the relative frequency of documents returned by a search engine can be a good measure of how frequently a phenomenon occurs.  For example, if you want to know the relative cost of living in all U.S. cities (or the relative amount of corruption, or perhaps even how good the golfing is) then simply searching for “Dallas cost-of-living” and “San Francisco cost-of-living” may give you a great index.  If it works as advertised, this is a fantastic general research tool for analysts and marketing researchers. Let’s take a look.
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Don’t Count Me!: Google Analytics and WordPress

As a new WordPress blogger, going back and forth editing pages and making sure they look terrific — I’m generating most of my own Google Analytics page views.  When I get a real page view, I want to know it!  Fortunately, if you already have Google Analytics installed, it’s very simple to accomplish in WordPress. Continue reading “Don’t Count Me!: Google Analytics and WordPress”

Omniture SiteCatalyst Variables 101

Data analysis begins with understanding the available data. To social scientists, this usually involves understanding your data type — nominal, ordinal, scalar, ratio. Web analysts, however, must always be concerned with the level of measurement as well — page level, session level, user level. If Omniture SiteCatalyst is your data source, understanding SiteCatalyst’s levels of measurement is key to being a good analyst. Those esoteric SiteCatalyst variables: sProps, Success Variables, and eVars, are easy to remember once you’ve seen their levels of measurement and Continue reading “Omniture SiteCatalyst Variables 101”