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Tag Archives: web analytics

Tracking into oblivion

written by Ben Mosbarger for the internet marketing, PPC, SEO section(s)
Tracking into oblivion

Tracking PPC data has been on my mind so much lately that I can hardly think about anything else. I know you have likely read many blog posts about tracking data and how important it is. The reason there are so many people writing about it is because companies aren’t doing it! Not tracking your data is like not balancing your checkbook… errr, wait, you probably don’t do that either, do you? Be honest. Maybe we should move on. Read On

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Traffic Diversification: Don’t Put All Your Chickens in One Basket

written by Clint Eagar for the Other, PPC, SEO, Small Business Tips section(s)

For some time now I’ve been mulling over a marketing/analytics idea I call traffic diversification. Simply put, traffic diversification is a methodology whereby a website diversifies the sources of traffic it receives.

In my time as an internet marketer, I’ve audited and optimized 100′s of websites. One underlying challenge I see for most sites is that they receive 70-80% of their traffic from a very few sources.
Read On

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PPC vs. SEO: Apply the mantra!

written by Josh Summerhays for the PPC, SEO, Small Business Tips section(s)
PPC vs. SEO: Apply the mantra!
Who knew cannibals could be so cute? Photo by deanj

Short post from me today, and many of you will be very tired of reading about this subject. If that’s you, feel free to move on to other posts. You won’t hurt my feelings.

However, there is still a large number of small business owners and marketing folks who persist in the notion that if you rank top-10 organically for a keyword (sometimes even top-20 or 30), that you shouldn’t bid for it with your PPC campaign. The reason is that you don’t want to cannibalize sales from SEO, which makes complete sense.

Except when that doesn’t happen.

Read On

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Website Friction and the SMB

written by Josh Summerhays for the web site marketing strategies section(s)
Website Friction and the SMB

When it comes to their business website, too many small business owners still cling to the false notion of, “If you build it, they will come.” The idea is that having a web presence will get the job done. Put up the site, get the products on there, slap the logo on it and watch the sales roll in, right?

Once upon a time, when the concept of a business website was fresh and exciting, that may have been true. But times have changed. You can’t crank out any old website and expect customers to magically line up like the cars leading to Ray Kinsella’s remote baseball field.

Read On

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Web Analytics: Follow the Trend

written by Janet Thaeler for the PPC section(s)

Like SEO, web analytics is not as clearcut as many would like. Unfortunately, there is no standard that all web analytic companies follow. And here’s the even worse news: without a “standard” there can never be reconciliation of web analytic data.

Why not?

Because every program defines a visitor, a bounce, and a click, differently. So when it comes to web analytics this holds true: “The trend is king when analyzing web analytics data.”

There are general guidelines that may help make sure you’re comparing data from two different site tracking information. Here are some important questions to ask.

  1. Are both analytics tracking codes implemented correctly on every page of the sites?
  2. Are the reporting date ranges the same?
  3. Is the same page of the website being reported?
  4. Is the bounce rate an isolated metric? Are there also massive differences in the number of visitors to the site, or other statistics?

And the final kicker…

How does the web analytics program define a bounce?

What is the difference in the definition of a bounce for each program? One program might define a bounce as someone leaving after 5 seconds, another 10 seconds, etc. This could result in a big difference. And there are many other variables that can create large discrepancies, in fact, some programs allow the web developer to define their own parameters of a “bounce.” Because of these reasons and the fact that this information is usually propriety, it is not possible to reconcile data from different analytic programs.

If we look at the trend then the differences don’t have to be a problem, but can be complementary. However, those that like to deal with absolutes, this is a hard pill to swallow. It certainly doesn’t make our clients happy and some threaten to cancel unless we can reconcile web stats. It’s not something we’re going to take on but we can guide our clients through to try to make sense of the information.

The bottom line?

SEO and PPC is an art form that are always chasing a moving target.

This post was written by Clint Eagar who previously worked for web analytics company Omniture. I asked him to write it after some complaints about numbers on our tracking not matching the client’s tracking system.

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How to Reconcile Differences in Web Stats

written by Janet Thaeler for the PPC section(s)

This is a common question – how do you reconcile the differences in web stats. It seems like every analytics program comes up with a different number, which can be frustrating for businesses of all sizes. It’s also a problem with paid search because the numbers you see from your PPC analytics may not match up with the numbers in Google.

OrangeSoda recently hired Clint Eagar who worked for web analytics firm Omniture. I asked him to write a post to try to demystify the discrepancies that are common between different web analytics tools.

I get a lot of questions about why there is a variance between how different web analytics packages report traffic results.

It’s All About Cookies
This has to do with how an analytics vendor uniquely identifies a visitor. Most analytics providers uniquely identify a visitor by a persistent browser cookie. When a visitor comes to a website the analytics code checks to see if the cookie exists. If the cookie does not exist it attempts to place it.

If it cannot place the cookie many analytics providers will ignore the entire visit. A large portion of the discrepancy between analytics providers comes into play when a web site cannot place this cookie. Some vendors will build a unique visitor cookie by combining user-agent and IP address. Some analytics vendors use third party cookies to uniquely identify visitors while others set a first party cookie and some visitors have their browsers configured to not accept third party cookies.

Establish Analytic Metric Definitions
The next thing you need to understand is how each analytics vendor defines a page views, visits and other metrics. One vendor may define a visit as a user session that lasts for at least one minute. Others will count an additional visit if the visitor views a page and then leaves the page idle for more than thirty minutes.

So, for example, say you’re reading a news story at CNN.com and get about half way through the article then you head out to lunch for thirty minutes and then come back to your open browser, finish the article and then click to read a new article. This will count as two visits – not one. Some analytics vendors will count this as only one visit. How does your provider track a visit?

How is a unique visitor defined? Is it a daily unique visitor (a visitor that is unique to the site today)? Is it weekly (a visitor that is unique to the site this week)? Is it monthly, etc? I think you get my point.

Tracking Code Execution
Other obstacles to having perfect harmony between analytics vendors could be loading time of site and the location of the tracking code JavaScript, does it load before page content or after. Did the visitor close the browser or click back button before the JavaScript had time to execute?

Web Analytics Is About Trends
Trend is king when analyzing web analytics data. More important than squabbling over a ten percent difference in how Google Analytics or Omniture reports a visitor you should instead be questioning: How many visits to do I have this week compared to last? How are different referring domains driving conversions over time?

Ultimately the differences between analytics vendors is just noise and you should never (did I say never?) attempt reconciliation.

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