Web Analytics Articles by SEO Speedwagon

June 27, 2008

Exactly How Accurate IS Google Trends for Websites?

Much has been made of the week-old announcement that Google is in the traffic trending game. I weighed in earlier this week at ClickZ, focusing mostly on ways you can benefit from the information and largely sidestepping the already-trodden issues of Google being the only company able to opt out of the reporting, etc.

One question that hasn't been discussed to death, however, is the actual accuracy of the traffic numbers that Google is reporting. I ran some numbers on some sample sites and laid the Google Trends lines over the actual traffic numbers:

Example 1:

Example 2:

The verdict? In general, Google doesn't do too awfully bad, especially considering that neither of the sites above use Google Analytics or Urchin to measure their traffic.

The peaks and valleys are roughly similar. Roughly. Yet the scale is off pretty dramatically, with Google underreporting the traffic on one of the sites by a factor of two.

So my recommendation is that to gauge large trends (seasonality, results of large offline campaigns, etc.), Google Trends is a decent first look. It's probably a safe bet that when you plot two sites within the same vertical, that their relative lines will be more or less accurate when contrasted. But don't trust it for raw numbers.

Just to be fair, Google never said it was 100% accurate, stating in the post that "because data is estimated and aggregated over a variety of sources, it may not match the other data sources you rely on for web traffic information."

Exactly How Accurate IS Google Trends for Websites?
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March 04, 2008

SEO Success Factors

I was recently asked about the success factors of an SEO campaign. There are many, but let's take a look at three of what we consider the most important success factors:

1) Knowledge Is Power

It's very important for us to know what prior SEO activities have been conducted on a site. This can make or break the campaign. On a few occasions, our team of site analyzers have uncovered controversial techniques that even our client didn't know had been performed!

It's also very important for us to have access and learn from your web site analytics data. SEO is about getting the right people to your site from search engines. Your analytics data prior to SEO and after SEO is a constant gauge to see if your SEO company is traffic-focused, not just placement-focused.

Finally, the knowledge of understanding how your target audience is searching for your offerings allows an SEO best practices firm to shoot for the bullseye where visitors convert, not the outer rings of the target where visitors are "just browsing". Since the early days of SEO, this has not changed.

2) Link Popularity

With the significant weighting of link popularity in Google's algorithm, there are very few sites that can ignore link building. Now crucial to your site's success at major search engines is the continual effort of adding quality, relevant third party links to your site. Trust me, most of your competitors are doing just that.

3) Flexibility To Site Changes

We always make sure to take the temperature of potential clients as to their flexibility to make changes to their site that will make the site more search-engine-friendly. If you are considering SEO, I would suggest you rate your flexibility to site changes on a scale of 1-10. Bottom line, if you are below a 5, you may want to consider Paid Search along with Natural SEO.

SEO Success Factors
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February 28, 2008

Heirs Still Fighting Over the Page View Estate

Good article in Computerworld this week called Life After Page Views: Web Analytics 2.0.

To sum up, the page view has been tossed into the Pythonesque "bring out your dead" cart by a lot of people, including me, in an article I wrote at ClickZ a year ago:

Page views have long been one of the Web's most reliable measurements. But because of technologies like AJAX, Flash, and RSS, a site can perform at engines better than ever and users can spend as much (or more) time on your site than ever before, but the page view count won't reflect it. Page views rely on Web 1.0's click-and-wait model. ...
Sites with an income model that relies on excellent search engine positioning and subsequent page views must be especially diligent in showing potential advertisers a true picture of the site's user experience. Whether it's shifting the influence of time spent on a site, adding script-based click tracking to internal AJAX applications, or something entirely different, a multifaceted approach to Web measurement is becoming more and more important for Web monetization.

So imagine how vindicated I felt when, last July, Nielsen / NetRatings decided to abandon the page view as the primary web analytics metric. From the CW article:

At the time, the Internet benchmarking firm cited the growing popularity of Asynchronous JavaScript and XML, or AJAX -- which can refresh content without completely reloading a Web page -- as the main reason for the change to measuring time spent on a site.

But it turns out that video, not AJAX widgetry, is the major culprit in the growing chasm between falling page views and climbing "time spent" online. All of which leaves us with the same question: How do we measure consumer engagement in a post-page-view web publishing landscape?

The article is a little too long to sum up quickly, so I do recommend the read. The basic issue is that companies like Nuconomy are trying to be the first out of the gates with new engagement-measuring metrics such as "comments added to blogs, ratings, applications shared with friends, clicks on ads and online video use -- all of which can show how 'engaged' a user is with a particular brand or product," while folks like Avinash Kaushik (Google Analytics guru and recent SEMMY winner) caution us against rushing out and arbitrarily defining concepts while totally abandoning concrete measurements.

"I am not saying don't create engaging experiences," he added. "[Just] don't use the term engagement, because it has been bastardized to the point that it doesn't mean anything."

More questions than answers, certainly, but that's not necessarily bad.

Heirs Still Fighting Over the Page View Estate
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December 14, 2007

Big Update at Google Analytics

Late yesterday, the Google Analytics team announced a major update to its free analytics package.

Taking full advantage of the upgrade requires something that I'm sure that the GA team wishes didn't have to happen -- the modification of the tracking codes on every page of your site. Basically, you'll need to change the small snippet of code that used to refer to urchin.js so that it now will reference ga.js -- Google's new JavaScript tracking file.

But not to worry. The team has assembled a 22-page Tracking Code Migration Guide (PDF) designed to, um, walk you through the process.

Beyond a simply explaining how to update your code (which shouldn't be a problem if you input the original code in the first place), the guide explains the benefits of the new system by showing additional features, such as:

• Tracking virtual page views
• Tracking downloaded files
• Tracking a page in multiple accounts
• Tracking subdomains
• Track a visitor across domains using a link
• Track a visitor across domains using a form
• E-commerce transactions
• Adding organic sources
• Segmenting visitor types
• Restrict cookie data to a subdirectory
• Control data collection settings
• Control session timeout
• Control campaign conversion timeout
• Custom campaign fields
• Using the anchor (#) with campaign data
• Setting keyword ignore preferences
• Control the data sampling rate

Some of these features already exist in one form or the other. For example, you can track file downloads by defining one of your conversions as such. But the new iteration promises more simplicity, which is never a bad thing.

Remember, as always, this is a beta release. (But you knew that, didn't you?) I haven't updated the code on our sites yet, so I can't vouch for any particular improvements. But I am eager to get into it and will certainly post any interesting tidbits right here.

Big Update at Google Analytics
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October 23, 2007

Analyzing A PPC Campaign Without Analytics

In my mind’s eye I have an idealistic view of each paid search account that I manage. Of course it includes my clients achieving stratospheric ROI, but at heart I am a numbers guy. I know that in order to get the best possible results it requires the best possible data. However I do live with both of my feet on the ground and I realize that not all clients possess the ability to successfully deploy/integrate analytical tracking into their ‘web systems’ for a plethora of reasons.

The idealist in me wishes this were not so, while the realist tells me to move on. In that vein, and using the data that is readily available to all PPC campaigns there is still a lot of analysis that can be done to help guide us in making decisions. The hardest part is deciding which piece of the data that we do have should be ‘worth’ more than the others. In light of that, I try to visually represent things as much as possible so that they can stand or fall on their own merits and go from there.

To borrow a phrase from someone much wiser than me, I have found that where there is a will there is a way. Part of that way for me is described below in a section of a case study for a client that is not able to take advantage of analytics. Please keep in mind that this is not a complete analysis but rather highlighting how to find a way to gather useful data out the information that we do have.

Some Basic Facts:
•Who: A large client that has excellent brand awareness and a sizable spend
•What: Specific areas of interest are in brand vs. non-brand and key phrase length
•Where: Continental U.S.
•When: 3rd Quarter 2007
•How: Analyze the ‘big five’ data points (Impressions, Clicks, Click-Thru-Rate, Average Cost-Per-Click, Cost).
•Statistical Constraints: To be included in our data set each phrase must have had at least 1,000 Impressions and a Click-Thru-Rate of at least 5%.

Branded Terms

When I look at branded phrases the first thing that sticks out to me is the obvious dominance of the 4 word key phrase. In this instance the length of the brand name has a lot to do with this, also but notice that 1, 2, and 6 have roughly the same footprint. How do we make a judgment between 1, 2, & 6? Well, taking a more holistic view will aid us in this.

From the pie chart we can see that the 6 word key phrases rate far better than 1 or 2 word key phrase’s because of the negative impact of the higher cost associated with them.

Non-Branded Terms

When I look at the non-branded phrases I am first struck by fact that only key phrases with 2 and 3 terms qualified for inclusion in our data sample. The biggest difference, however slight, is in the impressions where 2 wins over 3.

The next fact that sticks out is how close the two phrases are together in overall performance. They may have individual nuances that can be tweaked but neither phrase should be overlooked in its importance to the success of the non-branded phrases.

Overall
The final piece that I will examine is comparing the branded phrases directly to the non-branded phrases. I find it important to introduce another measurement to the ‘big five’, number of keyword phrases, at this point to add weight to the question of reach.

The most striking thing besides the dominance of the branded keywords, is in looking at the enormity of the Average Cost-Per-Click for non-branded terms.

Conclusion
As a campaign manager one of my core duties is to make sure that I have collected as much important information as possible before we start to make decisions that guide the direction of the campaign. Although I would prefer a campaign with fully integrated analytics that is not always possible. In that case it is vitally important to make the best analysis that we can with the data that we do have.

Analyzing A PPC Campaign Without Analytics
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September 17, 2007

PPC vs. Yellow Pages vs. Direct Mail CPA

Via Chris Zaharias via MediaPost via Piper Jaffray, we get this stark contrast:

Search advertising has proven to be fertile ground for customer acquisition. A recent study by Piper Jaffray & Co. entitled, “The New eCommerce Decade: The Age of Micro Targeting,” indicated that the average CPA for search was $8.50, considerably lower than the CPA for the Yellow Pages ($20), online display ads ($50) and direct mail ($70).

Could you imagine how low the Organic CPA would have been in comparison, had they found a way to incorporate that into the study?

PPC vs. Yellow Pages vs. Direct Mail CPA
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August 20, 2007

New SEM Industry Term Coined: Disposable Clicks

We sure did have fun with this Quote of the Month while taking The Wagon for a spin this morning. From the magazine that takes itself so seriously it demands all caps, ADWEEK, we are treated to this breathless lede:

New research by Microsoft suggests a big chunk of search ad spending is wasted because advertisers pay top dollar for high ad placements clicked by consumers who are en route to their sites anyway. Listings tied to such "branded" keywords, typically a company's name or products, eat up about half of search budgets, Atlas estimates.

Wasted, indeed. Heard while The Wagon pulled up to fill itself up with coffee:

It's like saying Applebee's doesn't need specific signage or identifiable markings on its building to show out-of-towners where it is, because people are going to go there for dinner anyway. That is exactly how stupid this is.

Isn't this also an argument against any brand advertising of any kind?

New SEM Industry Term Coined: Disposable Clicks
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August 08, 2007

Download all query stats for this site (including subfolders)

I get the feeling that most people, even in our industry, using Google Webmaster Tools for themselves or a client aren't scrolling far enough on the Query Stats page to reach this link:

What you get if you click is rather unwieldy, sure, especially if you are dealing with a very large site, but the payoff is simply as large by the same degree. We are beginning to view it more and more here as a kind of matrix for how Google views your site architecturally, especially in light of GSI now having been moved to an undisclosed location. Actually, now that I've said it I'm a bit afraid it, too, will be taken away...

Download all query stats for this site (including subfolders)
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May 03, 2007

SEO Lessons from Jurassic Park

I get a kick out of it when SEO and Analytics overlap into other areas of life.

There's a great passage in Crichton's Jurassic Park (I don't think it made it into the film) that is applicable in all sorts of business and personal situations.

I can't find my copy of the book anywhere, since it's been about 15 years (!) since I read it. So I'll have to paraphrase. Here's the scene: An outside auditor is watching a Jurassic Park computer guy monitor a specific type of dinosaur within a certain part of the park from his computer workstation.

Here's the paraphrased scene. Remember (as if it will be hard) that I'm no Crichton:

Auditor: Hey Computer Guy. What's up?

Computer Guy: Hey Auditor. Just checking on how many T. Rexes we have in Area 8H.

Auditor: Cool. How do you do that?

Computer Guy: Oh, you know -- each one emits some fiction novel-based signal that is picked up by my computer sensor here.

Auditor: Cool. How many T. Rexes do you have?

Computer Guy: Twelve.

Auditor: Cool. How do you know that?

Computer Guy: Well, according to our records, we're supposed to have 12. When the computer counts the signals and finds 12, it tells me everything's okay.

Auditor: Cool. Why don't you try searching for 25 of them?

Computer Guy: Okay. Hey now, that's interesting...

Auditor: What happened?

Computer Guy: It found 25.

Auditor: Cool. Why don't you try searching for 50?

Computer Guy: Okay. OH CRAP.

Auditor: What's wrong?

Computer Guy: Can you lock that door over there?

AND ... SCENE.

So what does this have to do with SEO or web analytics? It means that getting the right answer is very important, but only when you're asking the right question or looking for the right data.

• If you're going after a "trophy phrase" -- and you actually start ranking for it -- you might think you've hit the jackpot, when in reality, some keyword research would reveal a much smarter strategy.
• If you're buying traffic to hit a certain visit or pageview goal -- and you hit those marks -- you might think you've achieved something, while sales languish.
• If you're pursuing a link-building strategy based on PageRank or raw numbers -- and you get that SuperLink or hit the right IBL count -- you might expect your sales to skyrocket, while instead you get a bunch of curious tire-kickers who do nothing but suck bandwidth.

So remember: When you're looking for dinosaurs, find out how many there are, period. Don't just stop when you get to 12.

I hope you've enjoyed this edition of SEO Morality Theatre.

SEO Lessons from Jurassic Park
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March 16, 2007

Google Webmaster Tools Beefs Up Anchor Text Report

As if you needed another reason to verify your site within Google Webmaster Tools, that specific team announced early this morning that they've improved the report that shows incoming anchor phrases that point to your site. Get to the report in the Webmaster Tools area in the Statistics tab, then by clicking Page analysis:

Previously, the report showed only individual words that made up anchor text phrases. Now, the reports shows up to 100 specific phrases themselves, which is significantly more helpful:

Data like this ranges from interesting to very helpful. It offers great insight to the behavior of people who link to you, since many people probably think incoming anchor text focuses mainly on company or site names. In addition, it might lend some guidance about some strange referring keywords you've seen in your analytics reports - as well as why you might not be seeing some specific referring phrases that you want.

Google Webmaster Tools Beefs Up Anchor Text Report
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January 04, 2007

How to Calculate Keyword-Based Conversion Numbers in Google Analytics

Google Analytics is great for assigning goals to certain events, showing you the referring keyword that triggers those events, and displaying what keywords have the best conversion percentage. But how do you determine the exact number of conversions that took place? If G1 is the download of a file, and G2 is the sale of a book, how do you determine the number of downloads or the total number of books sold, sorted by individual keywords?

You can easily determine a hard number of conversions (over a specified date or date range) in the Goal Verification menu:

But assigning raw conversion numbers to specific keywords is a bit trickier. Not rocket science, but it takes a little work. Here's what I do.

1. First, create a Google Analytics keyword report. You have to determine conversions-by-keyword on a source-by-source (i.e., domain-by-domain) basis. So navigate to All Reports -> Marketing Optimization -> Visitor Segment Performance -> Referring Source. Pick a specific source (I chose "google [organic]"), then specify the Keyword report as shown here:

   

   Note: To produce a keyword report, the source must be labeled as [organic] by Google Analytics.

2. Once you've created the keyword report, export it into Excel, which should give you something like this. Note that I've added some column head colors, and that I've replaced actual keywords with "Keyword 1," etc., to protect client privacy:

   

3. So now we know that Keyword 1 converted 1.53% of the time, over 652 visits. But how many raw conversions is that? It's a simple calculation, and we'll add it into the first available column to the right. The following shot gives the formula:

   

   This forumla simply takes the number of visits from each keyword and multiplies by the conversion percentage, then divides by 100 to account for the percent. Note: This specific formula works only if the existing columns appear as shown here. You'll need to change the [-1] or [-3] as necessary if you have more or fewer columns in your spreadsheet.
   

I'm a little surprised that the raw number of conversions isn't already a part of the keyword report. It's valuable data and would be easy to add to the programming. Fortunately, unlike some full referring URL strings, conversion-by-keyword data is available with only a few clicks.

How to Calculate Keyword-Based Conversion Numbers in Google Analytics
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December 12, 2006

Finding Referring URLs with Google Analytics - Sort Of

About a month ago, I was very happy to see the official Google Analytics blog come out with a post about finding the exact referring URL. It's one of the reports I use most regularly, and it has always surprised me that it's buried so deeply in the menu structure of Google Analytics. I was nearly giddy when I saw what the post was going to discuss, but then disappointed, because it didn't address my bigger concern, which I'll discuss further down.

A little background: Google Analytics makes it very easy to see which domains are referring traffic to your site. But finding specific referring pages within those domains is a little trickier - thus the post from the Analytics blog.

The following shot shows how to find specific referring pages within a specified domain. Here, I'm drilling down to see the specific page(s) at Sitepoint that sent traffic to our site:

That post solved only part of the problem. Google Analytics still does a poor job of showing the exact referring URL when it contains a dynamic string. vBulletin PHP pages are a good example. The following shot shows what happens when I click the Content selection in the menu above:

As you can see, Google Analytics doesn't report any dynamic arguments after the page name. This is a problem, because just seeing this page name does almost no good at all. Tens of thousands of Sitepoint pages begin with this filename. What I need is for the report to show this:

/forums/showthread.php?t=419917

instead of simply this:

/forums/showthread.php

A current thread at the Google Analytics Help group page is called Wishlist. I've posted here, requesting this feature. But there are many, many, many instances of similar requests that have gone unrequited. If you think this feature is important, I urge you to add your thoughts to the Wishlist thread.

Finding Referring URLs with Google Analytics - Sort Of
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October 25, 2006

A Cure For The Summer Time Traffic Blues

“Well I'm gonna raise a fuss
And I'm gonna raise a holler
About workin' all summer
Just tryin' to earn a dollar�?
Eddie Cochran, “Summertime Blues�?

There ain’t no cure for the Summertime blues?

One of the clients I work with has some seasonality to their business and traffic to their web site either levels out or dips during the summer months. This summer was not any different, traffic-wise. Their search traffic numbers in the Spring months averaged 482,000 visits per month while their Summer average was 410,000 monthly visitors.

That doesn’t sound like it’s on the road to cure anything right?

A deeper trek into their analytics, though, raises the eyebrows. Their conversion rate during the higher traffic Spring months from visitors coming to their site from search engines was .825% which calculates out to approximately $13,918 in online sales per month. Their conversion rate during the “Summertime blues�? months was 1.23% which is 45% higher than the Spring and calculates out to $17,538 in monthly online revenue.

Nothing like an increase in revenue to melt those blues away. But still, the higher revenue isn’t the real cure nor is the higher conversion rate.

The cure is in the answer to the question: Why is their conversion rate 45% higher?

The Cure

I have a fever, and the only prescription is a higher quality web site visitor.

I love best practices SEO.

Higher quality visitors are a direct byproduct of improved search positions for SEO-targeted keywords and phrases.

It’s no surprise to also see that this client had a Summertime increase of over 200 positions at Google for their optimized phrases.

A Cure For The Summer Time Traffic Blues
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October 19, 2006

Using Google Analytics Bounce Rates to Gauge Site Stickiness

Buried deep in the guts of Google Analytics is a report called "Entrance Bounce Rates." It's off the beaten path of "Referring Source" and "Total Visits," so it doesn't always get a lot of attention. But it offers valuable information about visitors' habits on your site. Here's how to access the report:

The Entrance Bounce Rates report shows you a list of "entrance" URLs for your site (those URLs that people used to enter the site, whether via a search engine, third-party link, etc.) and the percentage of visitors who left your site after viewing only that page. Thus, if your bounce rate for a page is 100%, that means each person who entered the site on that page viewed that page only, then left the site. Like golf, the lower the number, the better.

If you don't know what to look for, the numbers can be confusing, or worse, useless. But when you filter the data by content area, things begin to make sense. For instance, if we wanted to measure bounce rates on this site for articles written in 2005, we need only enter that folder in the filter box, hit the plus sign, and we have our data.

The filter button is a toggle. When you press the green plus sign once, it becomes a red minus sign. If you press this, it enables you to see the bounce rates for every page except those in the filtered directory:

So comparing the stickiness of the articles written in 2005 vs. those written in 2006 happens in only a few seconds. Use this method across multiple categories of your site to see the rates in your case studies, executive bios, pages within a certain product or service area, and so on. If people leave one area of the site more frequently than they do in others, why is that? Did you offer a call to action there? Did you give them further opportunity to find out more?

Answering these questions requires some time and perhaps some tough content decisions, but it's an effective way to gauge the effectiveness of certain segments of your content - and in turn, create a more compelling, sticky, and (ideally) profitable site.

Using Google Analytics Bounce Rates to Gauge Site Stickiness
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