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How To Get 100 Likes From 2 People

November 08 2010 // Analytics + Social Media // 9 Comments

The other day I wrote about the potential for inflated Like numbers. In particular, I was interested in how comments were factored into the Like total.  It was pretty clear that Likes and comments were not mutually exclusive. But were comments a count of unique contributors or simply a total count of comments.

The Like Experiment

So, I ran a small experiment using an old satirical blog post: LOLCats and Religion: A Dissertation.

This post originally had two shares but no Likes or comments. So I went ahead and Liked it and asked my colleague Jeremy Post to have a comment dialog on the item. In all, we generated 10 comments.

Facebook Comments

One of my concerns was that comments might not always relate to the item and interestingly enough we actually did switch topics during the dialog from LOLCats to Dune. Go figure. (Note to self fix image being attributed to blog posts.)

The Like Results

So what was the result? How many Likes did this old post rack up due to this comment stream? Sure enough, every comment is counted as a Like.

Facebook Like Numbers

A quick check using my Facebook Like Number Bookmarklet reveals how the number is calculated.

Facebook Like Count

So, did 13 others like this? No, it’s just two people having a conversation on a shared item. And that’s how you could get …

100 Likes from 2 People on 1 Item

Don’t Average CTR

November 08 2010 // Analytics + PPC + Rant + SEO // 6 Comments

One of the biggest errors I see (consistently) in SEO and PPC analysis is using Excel’s AVERAGE function on Click Through Rate (CTR). As I mentioned in my SEO Pivot Tables post, do not do this. Here’s why averaging CTR is dangerous.

Take the following set of 10 data points.

Don't Average Click Through Rate

If you SUM all of the Impressions and Clicks and then do the CTR calculation you arrive at 10.05%. If you AVERAGE the 10 CTR percentages you arrive at 6.14%.

If I change the Clicks for these 10 data points I can produce the opposite effect.

Don't Average CTR

And will you look at that, the average CTR is the same in both instances. Can you see how misleading average can be here?

Don’t Average Click Through Rate

For years, I’ve used a structured Excel quiz in my hiring process that tests just this issue. In my experience upwards of 50% of applicants fail the quiz. If you’re pulling down data into Excel for PPC or SEO, make sure you don’t fall into this trap.

Facebook Like Number Bookmarklets

November 05 2010 // Analytics + SEO + Social Media // 2 Comments

Want to know the Facebook Like statistics for the page you’re on? No problem.

Facebook Like Number Bookmarklets

Using the old REST API you can find out the Facebook Like statistics for any page. For easy access, simply drag these two links to your bookmark bar.

FB Stats: Current Page

FB Stats: Home Page

The Current Page bookmarklet will provide Like statistics for the page you’re on. So, if you were on the ReadWriteWeb article about Facebook Places Deals you can click on this bookmarklet and be provided with the Like statistics for that page.

Facebook Like Bookmarklet

The Home Page bookmarklet will provide Like statistics for the home page for the site you’re on. Please note that this is not showing the aggregate Like statistics for the entire site, but just that of the home page.

Like Number Use Cases

Why are these bookmarklets useful apart from abject curiosity?

First off, you can determine the true number of Likes. Second, they provide competitive intelligence and potential insight into Facebook’s search algorithm (aka Facebook SEO). Do pages with a higher distribution of comments get a higher weight? I’m not sure.

This is one way to begin understanding the ways in which pages enter the Open Graph and how they are treated based on Like activity.

Impact of Google Instant

October 01 2010 // Analytics + SEO // 2 Comments

Everyone wants to know how Google Instant is changing search.

There’s been some great analysis on whether Google Instant has changed keyword length. While auto complete could certainly have an impact on query behavior, the impact so far seems to be negligible.

I’ve been more interested in whether Google Instant would change assessment behavior. I theorized that Google Instant might result in more clicks above the fold because users would become focused on watching – and assessing – search results as they typed.

Google Instant Rank Analysis

Each week I measure the amount of traffic produced by each rank via Google Analytics. Using this data across two large sites from different verticals, I’m able to compare traffic by rank the week prior to Google Instant’s launch versus the most recent week.

Google Instant Traffic by Rank

The distribution of traffic by rank certainly seems different. But there’s a good deal of noise in pulling this data.

First, while the volume of searches is high the number of data sources is low.

Second, the number of terms driving traffic at each rank and the query volume for those terms may have changed. (However, a quick analysis shows that the number of terms doesn’t have a bearing on the data.)

Lastly, the Google Analytics rank hack only captures a certain percentage of traffic where the ‘cd’ parameter is passed. Historically that was about 20% to 25% of search results. However, just prior to the launch of Google Instant that percentage shot up to ~40%. The subsequent weeks of decline in ‘ranked’ traffic don’t map to overall traffic patters, so I believe the amount of traffic with a ‘cd’ parameter has likely decreased.

Long story short, the variation by rank is the signal, not the actual changes in rank.

Google Instant Click Distribution

Has Google Instant changed the distribution of clicks by rank? If above the fold ranks are getting a higher distribution of clicks, SEO is not dead – its become more important than ever.

But what about the odd behavior of those with a rank of 1 or 2? Could paid search or Onebox presentations be sucking away traffic from the first and second positions?

Google Webmaster Tools should be able to provide some additional insight. Yet, as I was performing the analysis I came to realize that the search queries report in Google Webmaster Tools has less coverage (5% to 15%) then the Google Analytics rank hack (20% to 40%).

Furthermore, the coverage in Google Webmaster Tools is weighted by rank, with (far) higher visibility for higher ranks. I’m not sure analysis on lower ranks is reliable given the thin data set. However, I do see appreciable declines in CTR for both the first and second positions. This seems to support the data gleaned from Google Analytics.

Above The Fold SEO

If the distribution of clicks is changing, being above the fold could become increasingly important. Earlier this year Jakob Nielsen conducted a study that showed that users spend 80% of their time and attention above the fold.

Eye Tracking Page Distribution

Lets be clear, the prerequisite is that the user scrolls. Does Google Instant disrupt the natural inclination to scroll? I say yes, and I think the preliminary data points in that direction.

Eye tracking studies have already shown the difference in assessing informational versus transactional queries. I’d like to see these studies performed using Google Instant to determine if those patterns have changed.

Baring that, I’d like to expand my data set and appeal to others who have Google Analytics rank data to perform the same analysis. Do it yourself and post the results or send me the data and I’ll aggregate it with my current data set.

Either way, I believe it’s important to understand how search behavior may be changing and adapt accordingly.

Google Analytics Default Profile

September 24 2010 // Analytics + SEO // Comment

If you’ve used Google Analytics for any stretch of time, you probably have a number of different Google Analytics profiles for your website. For instance, you might should be tracking keyword rank in a Google Analytics profile.

Different profiles can be handy but often the one you use the most isn’t the default profile. Each time you log-in to Google Analytics it defaults to a profile based on an alphabetic sort. This is annoying and, sadly, Google hasn’t launched a new ‘select-as-default-profile’ feature. Instead, there’s a very simple and easy hack.

Google Analytics Default Profile Hack

First, click on Analytics Settings in your Google Analytics account.

Google Analytics Settings

From there, find the profile you want to be the default profile. Next to that profile, on the far right under the Actions column you should see an Edit option.

Edit or Delete Profile

If you don’t see these actions, you don’t have the rights to make this change. Find someone with Administrator access or have them grant you that access. If you do see these actions, click Edit. Then you’ll want to edit the main website profile information. The Edit link is located at the upper right side.

Edit Google Analytics Profile

Now all you have to do is type an underscore at the beginning of your profile name. The example uses a domain entry, but it could just as easily be something like _My Website Name.

Underscore Your Profile

Then click Save and you’re done. Don’t worry, this will NOT impact the tracking on this profile. No data or history will be lost.

The underscore profile will now be the default profile since it’s first alphabetically. It’s certainly not the only way to do this, but this 1 minute hack can make your daily use of Google Analytics just a bit easier.

Google Instant Analysis

September 09 2010 // Analytics + PPC + SEO // 2 Comments

Google Instant delivers a new search experience, both in how users enter searches and how those searches are presented. What does it mean for the search industry?

Google Instant

Did Google Instant Kill SEO?

No! A thousand times no. Those making these claims are either being purposefully provocative or are … simply misinformed (see how nice I can be) about SEO. What makes SEO interesting is that it continually evolves. Google Instant is simply another evolution of search and those who adapt will flourish and those who don’t will fall behind. Pick a side.

Is Google Instant an Algorithm Change?

No! Google Instant does not impact search rankings. It is not an algorithm change. However, it may have an impact on traffic as search behavior changes. So lets look at exactly what Google Instant is and why it could be a major shift for SEO.

Google Instant vs Facebook Typeahead

Facebook Typeahead Search

Before we go into the details, let me take a brief detour. I believe Google Instant was developed, in large part, because of a continuous effort to provide users with a better search experience. However, I also think that Google Instant was influenced by the work Facebook has been doing with Typeahead Search, which has been presenting results in the same way for about a year.

Remember, the Open Graph is just another way to build a search index and one day soon you’ll go to Facebook and that small search box will suddenly be twice as large and presenting more results from outside the walled garden than inside.

The era of Facebook SEO is just around the corner and Google knows it.

Search Speed

At the launch event, Google stated that the average time to type a search was 9 seconds and the time to evaluate the results was 12 seconds. Google Instant seems aimed at reducing both of these metrics.

The time to type has clearly been reduced as Google delivers results on a letter-by-letter basis. However, the evaluation time may also be reduced as users become used to scanning the ever changing search results, watching them go from ‘wrong’ to ‘right’.

If you pay attention to UX (and you should) you know that users scan web content. Google Instant seems poised to take advantage of this behavior.

The Fold

Users will be evaluating the quality of searches as they type. The speed in which Google delivers these results means the evaluation will likely take place above the fold. Will users become more focused on above the fold results, even when they land on the ‘right’ search result? If so, this is compounded by the extra space taken up by Google Instant’s set of five auto-complete suggestions.

If the evaluation time decreases and the focus is on results above the fold, a greater emphasis would be placed on achieving top rankings and having a result that stands out. In other words, SEO becomes even more important.

Auto Complete

Google’s auto-complete feature becomes a much more powerful part of SEO. Today, the algorithm behind search engine results is refined on a daily basis. Gone are the ‘Google Dance’ days in which a monthly algorithm change created havoc on search results.

However, the auto-complete algorithm is not updated with that type of frequency. Some SEOs (myself included) target auto-complete suggestions (formerly know as Google Suggests) for optimization. While some of the suggestions change, most of them do not – and if they do, they do so infrequently. When they do change, you feel the impact – immediately.

The increased reliance on auto-complete and infrequent updates to those suggestions could result in a new type of Google Dance.

The auto-complete algorithm seems loosely based on search volume, location and recency with a heavy emphasis on volume. Google Instant creates a secondary SEO algorithm. It’s not just about those 10 blue links, it’s about those 5 auto-complete suggestions too.

We simply don’t know how often Google will change auto-complete suggestions, how they’ll change the criteria for those suggestions nor how quickly SEOs will find ways to influence and game those suggestions. Auto-complete gives Google quite a bit of power to direct user queries.

Google Analytics

Initial reports seem to indicate that the keyword returned to Google Analytics will be the auto-complete suggestion term that produced the click. This reduces the visibility into the actual typed search that triggered the click. This may inhibit the ability to infer the actual intent of those queries, or to determine if the auto-complete suggestion is creating non-qualified traffic.

While seemingly innocuous at first glace, I believe the lack of visibility is dangerous. Thankfully, a parameter (‘oq’) in the URL string has been identified that should provide the ‘original query’ string. If you’re already tracking rank through Google Analytics, setting up the Google Instant tracking shouldn’t be too hard. Experimentation on the exact output is necessary to ensure you’re able to leverage the data.

I’ll post my own Google Instant Analytics Hack after I find the right configuration.

Paid Search

Google Instant dynamically displays both organic and paid search results as you type. While the threshold for booking a paid search result as an impression is 3 seconds, many believe (myself included) that the number of impressions will increase.

This could have a dampening effect on clickthrough rates (CTR) which is the primary way Quality Score (QS) is measured. A lower QS leads to higher CPCs and impression thresholds. It remains unclear how Google will handle this potential scenario and whether more scanable paid search results will be more effective.

And if a change in search behavior does come to pass, does that change the distribution of clicks between paid and organic? The cynic in me says Google wouldn’t have launched Google Instant unless the impact on paid search revenues was thought to be neutral or positive.

Search Behavior

Google Instant makes hitting the return or enter button nearly obsolete. This simple action (or lack thereof) may change search behavior. There will be no delimiter – no time in which to enter, evaluate and iterate. Instead, evaluation and iteration take place almost simultaneously.

Users will ‘flip’ through results by typing, until they find the results they want. The speed also reduces the hesitation to try another search, particularly since searches are dynamically shown as you type or delete.

Ben Gomes (Google Distinguished Engineer) did state during the launch announcement that Google Instant resulted in more search queries.

Search may become less about a single search and more about a series of iterative searches. As such, SEOs may need to understand how to either interrupt or attract a click during that series of searches or understand how to optimize for the last search in that iterative process.

The Long-Tail

Google Instant should have an impact on the long-tail, but what exactly that impact will be depends on how search behavior evolves. In the short-term, I believe the number of words per query will rise as users take advantage of the auto-complete suggestions and iterations. The ability to drill-down to more refined queries should go up. We’ll see an expanding mid-tail.

Google SIdewalk Ends

However, what happens when you get to the end of auto-complete suggestions? Will users keep on typing and ultimately hit return? Or will they begin to view the lack of auto-complete suggestions as a sign they’ve gone too far, that they’ve reached the end of the sidewalk? Will they simply delete and try to iterate the search within the auto-complete suggestions?

We’ll have to wait and see.

Google Instant Analysis

Google Instant will not kill SEO.

Google Instant is not an algorithm change.

Google Instant looks eerily familiar to Facebook Typeahead Search.

Google Instant reduces the time it takes to type a query.

Google Instant may impact traffic as search behavior changes.

Google Instant may reduce the time users spend evaluating each SERP, putting a greater emphasis on having a scanable and eye-catching result.

Google Instant pushes all results down the page because of the five auto-complete suggestions.

Google Instant may make ranking above the fold more important as users become focused on evaluating results as they type.

Google Instant makes auto-complete suggestions extremely powerful, creating a secondary algorithm that can have serious traffic implications.

Google Instant could reduce the visibility of true search queries unless you configure Google Analytics to capture this data.

Google Instant will change the distribution of search terms on the tail.

Google Instant may increase paid search impressions which could negatively impact CTR and Quality Score, resulting in odd CPC cost and performance.

Google Instant is addictive.

SEO Pivot Tables

July 23 2010 // Analytics + SEO // 9 Comments

In my last post I covered SEO Excel functions. In this post I’m going to cover something even more valuable to SEO – pivot tables. Excel defines a PivotTable as follows:

A PivotTable report is an interactive table that combines and compares large amounts of data. You can rotate its rows and columns to see different summaries of the source data, and you can display the details for areas of interest.

Use a PivotTable report when you want to analyze related totals, especially when you have a long list of figures to sum and you want to compare several facts about each figure. Because a PivotTable report is interactive, you can change the view of the data to see more details or calculate different summaries, such as counts or averages.

What does a pivot table really do? A pivot table lets you slice and dice a big set of data.

Top Queries Pivot Table

Instead of using dummy data I’m going to show how to generate a pivot table report using the new Google Webmaster Top Queries report. I’ll be using Excel 2008 for Mac which is different (probably more difficult) than the PC version.

Obviously we need to the Search queries report in Google Webmaster Tools.

Webmaster Tools Top Queries

At the bottom of this report you can download the table.

Download Top Queries

What’s really nice is that it will actually download all of the data, not just the 100 queries on the page but all (4,010 in this case) queries. Other Google products could benefit from this feature. I’m looking at you Google Analytics.

The Data Table

What you download is a big CSV file. (CSV stands for Comma Separated Values if you’re interested.) It will look like this when you open it.

Google Top Queries Report Download

It’s certainly interesting but reading it line by line isn’t very useful or efficient. There are plenty of things you can do to make it easier to digest. You could sort it (by Impressions) or filter it (by Avg. position) but a pivot table can really make sense of the complex.

Before I go on I’m going to Save As, rename the file and change the file type to Excel. This is just a safeguard and good general practice.

Select The Data

Next, you’ll want to select the data you want to include in your pivot table. This doesn’t mean just the rows or columns you want. Instead, you’re going to select the entire set of data you just downloaded. Selecting it is actually really easy.

Click on the top left cell of the data. In this case it’s going to be cell A3 with the text ‘Query’ in it. Then hold shift-ctrl and tap the right arrow once (but don’t let go just yet). When you do this all the relevant columns in the entire top row should be highlighted.

Highlight Using Keyboard Shortcut

Keep holding shift-ctrl keys down and then tap the down arrow once. When you do this all the rows in the data table should be highlighted.

Shortcut to Selecting Excel Data Table

The shift-ctrl-arrow or shift-apple-arrow shortcut selects everything until it hits a blank cell. It’s a nifty time-saving shortcut for any Excel work.

Create The Pivot Table

At this point you can let go and, with the entire data table highlighted, select PivotTable Report from the Data menu.

Create Pivot Table

This will launch the PivotTable Wizard.

Pivot Table Wizard Step 1 of 3

Since you’ve already selected the data (which is what you’d do in step 2) you can actually skip steps 2 and 3 and just click Finish. When you do, a new Excel tab is created and you’re staring at an empty pivot table.

New Pivot Table

In my experience this is where most people get scared off. It’s like Excel is taunting you – demanding you to drop fields and data. It looks more daunting than it is and you can always undo or even create a brand new pivot table. As in nearly all things, trial and error is a great teacher.

It’s probably easier to show you how to do this rather than explain what each part means in the abstract. So lets create a pivot table that shows the total number of impressions, clicks and click through rate (CTR) by position. That would be handy, right?

Insert Pivot Table Fields

First you’ll want to drag the Avg. position field button to the row area. If you don’t see those field buttons, just click anywhere in the pivot table and they’ll magically appear.

SEO Pivot Table How To

In this instance there are no columns so we’ll move swiftly on to data.

SEO Pivot Table How To

Drag the Impressions button into the data area.

SEO Pivot Table How To

The result will look like this.

SEO Pivot Table How To

It looks wrong, I know! But be patient, we’ll fix that in short order. Next drag the Clicks into the data area.

SEO Pivot Table How To

The result will now look like this.

SEO Pivot Table How To

Change Field Settings

You don’t want to count impressions or clicks you want to sum impressions and clicks. To do this click on the first Count of Impressions cell (B4 in this case), then click the PivotTable button and select Field Settings.

SEO Pivot Table How To

After you do this you’ll be able to change the field from a count to a sum.

SEO Pivot Table How To

Click on Sum and then click OK.

SEO Pivot Table How To

Now we’ve finally got the right metric and you’re seeing the total number of impressions by position. Simply repeat the same process for Clicks so that you have both Sum of Impressions and Sum of Clicks.

Create a Calculated Field

You might now be tempted to drag CTR into the data area. Don’t! Averaging a set of percentages will not give you the results you want. Instead you need to create a calculated field. Click the PivotTable button, then select Formulas -> Calculated Field… from the drop down menu.

SEO Pivot Table How To

Now you get to create a Calculate Field. Again, much easier than it sounds.

SEO Pivot Table How To

You’ll first give this calculated field a name. The name CTR is already taken so I’m going to name it CTR by Position. Then create the calculation by typing in functions, highlighting and inserting fields. This is what it should look like before you (1) click the Add button and the (2) click OK.

SEO Pivot Table How To

Formatting Fields

Now you’re got the total number of Impressions, Clicks and CTR by position. But the formatting on the CTR is annoying. So lets change that. Click on the first Sum of Position CTR cell (B6 in this case), then click the PivotTable button and select Field Settings.

SEO Pivot Table How To

This brings you to a two pane process where you will (1) click Number… and (2) select Percentage from the Category menu and (3) click OK which takes you back to the first window where you will (4) click OK again.

SEO Pivot Table How To

At the end of all that you get a fairly easy to read table that shows impressions, clicks and CTR by position.

SEO Pivot Table How To

Filtering Pivot Tables

What if you wanted to just see the data for a specific position? No problem. Drag the Avg. position field from the row area into the page area.

SEO Pivot Table How To

Once the pivot table changes, you can then select the position you want to see using the drop down filter.

SEO Pivot Table How To

I’m going to select 1.7 as my position. At that point I might want to see what actual terms drove traffic at that position. To do that, drag the Query button to the column area. (You didn’t think we’d ignore the column area completely, did you?)

SEO Pivot Table How To

Now I get to see what terms drove traffic at the 1.7 rank and how effective each term was at that position.

SEO Pivot Table How To

Yes, my used books blog is getting a fair amount of traffic on the term ‘dr. evil’. (Image optimization works folks.)

Hopefully, you can envision another pivot table with Query as rows, search engines as columns and keyword rank as data. That’s a nice little table to have in your back pocket.

Hide Pivot Table Items

Still with me? I’m going to do a few other things that you might find useful. I’m going to drag query out of the column area, and drag Avg. position back into the row area so we’re back to the formatted pivot table first created. Then I’m going to click on the Avg. position cell (A3 ) and select Field Settings.

SEO Pivot Table How To

This will bring up a slightly different Field Settings window where you can hide certain items. (FYI – from here you can also click Advanced and change the sort order of your pivot table.)

SEO Pivot Table How To

I’m going to hide any position higher than 10 and then click OK. The result is a much more manageable table.

SEO Pivot Table How To

Pivot Table Charts

Now I want to see which of these positions drove the most clicks. I’m going to delete the Sum of Impressions and Sum of Position CTR fields. To do this, Click on the corresponding cell in the pivot table (B4) and then navigate to Field Settings and then click Delete.

SEO Pivot Table How To

Do the same thing for both Sum of Impressions and Sum of Position CTR and you’re left with a table that shows the clicks by position.

SEO Pivot Table How To

Now it’s time to make a chart. First you need to select the entire table by clicking the PivotTable button and using the Select menu to … select the Entire Table.

SEO Pivot Table How To

Now create a chart like you normally would.

SEO Pivot Table How To

And after a bit of tweaking here and there you can produce a presentation quality chart.

SEO Pivot Table Chart

In this instance you might be surprised to see where most of the clicks come from. It might make sense for me to review the terms at 2.8 and see if I could move them up a spot to grab a higher share of clicks.

Refreshing Pivot Table Data

Now for extra credit. I mentioned in my SEO Excel Functions post the need to round numbers. In this instance, perhaps I just want to see things by whole number rank.

Lets go back to the actual data table and create a column next to Avg. Position. I’ll name it Rounded Position and then use the ROUND function to change it to a whole number.

SEO Pivot Table How To

Now I’ll copy that all the way down the column. To do this quickly just double click the small box in the lower right hand corner of that cell.

SEO Pivot Table How To

Now select the entire column starting below the title by using the shift-ctrl-down arrow. Then copy and paste values over the data in the Avg. position column. You’re basically overwriting the decimal rank data with whole number rank data.

Alternatively you could insert a column into your data table (between D and E so it’s inside the original table range) and then paste values (including the header row) into that new column. By doing this you aren’t overwriting data. Instead you’re going to add an additional field to your pivot table.

If you choose this route you’d have to swap the Avg. position with Rounded Position in your pivot table and go though the hide items process again. Either way, the idea is to refresh the data in a pivot table.

So lets go back to our pivot table sheet and click the exclamation point.

SEO Pivot Table How To

Voila! Now you’ve got a super easy to use table that shows clicks by whole number rank.

SEO Pivot Table How To

Every SEO likes a good chart, right? The chart data should have updated automatically too. So with a small tweak you can produce another one.

SEO Pivot Table How To

Amazingly enough there is more I could go through, but …  I think that’s enough for now.

SEO Pivot Tables

If you’re doing SEO for any amount of time you’ll see the value of using a pivot table. They help you make sense of large sets of data, allowing you to accelerate your analysis and provide actionable insights. Hopefully this real data exercise was instructive and valuable. If it was, please give it a Sphinn.

Let me know if you have any questions, comments or pivot table tips and tricks of your own.

Track Keyword Rank in Google Analytics

April 21 2010 // Analytics + SEO // 23 Comments

In February, Matt Cutts referenced a parameter in AJAX based Google search results that would let you track the rank of that result. Sure enough, it’s there and with just a little bit of know how you can track keyword rank in Google Analytics.

Tracking Rank in Google Analytics

At first glance you might think that tracking keyword rank would be tough to implement, but it’s really not. Here’s an easy step-by-step guide to capturing keyword rank in Google Analytics.

Create a New Google Analytics Profile

Simply click on Analytics Settings within Google Analytics. You must be a Google Analytics administrator to do this.

Google Analytics Settings

At the bottom, find and click on Add Website Profile.

create new profile

You want to Add a Profile for an existing domain and then select the domain and enter a Profile Name. I suggest something easy and descriptive like “Google Rank”.

create new google profile

When you’re done you’ll see a new profile appear in your Analytics Settings list. Don’t worry if you see a yellow triangle with an exclamation point in the Status column. The tracking for a new profile takes a bit of time to populate. As long as the current tracking for that domain is working, this will take care of itself.

Create Profile Filters

Click the Edit link next to your new profile so you can create three filters. The first ensures this profile will only report organic traffic.

analytics organic filter

The second ensures this profile will only report Google traffic.

analytics google filter

The third one is a bit more complicated and involves capturing the keyword rank using a regular expression in an Advanced Filter.

google analytics keyword rank filter

If the picture isn’t clear enough you want to enter: (\?|&)cd=([0-9]+)

All the regular expression is doing is looking for that special parameter (?cd= or &cd=) in the URL and then capturing the number (aka rank) after the cd= and using it in the User Defined field. You might be able to get away with just &cd=([0-9]+) but smart folks like Yoast are using both. I did a quick test and captured that data ($A1) and found 100% of it to be the ampersand (&). That said, I recommend covering your bases and match on both.

Remember to be sure to use $A2 since the number 2 refers to the second parenthesis where you’re capturing rank. If you’re interested (like I was) the advanced filters help on Google isn’t a bad read and this regex cheat sheet is a nice reference as well.

That’s it! Really, you’re done.

Wait and Review Your Keyword Ranking Reports

google keyword ranking report

You’ll have to wait a day for the data to be collected since filters are not retroactive.

Wake up the next day and visit your new Google Rank profile. You’ll need to navigate to the User Defined section under Visitors. Once you click User Defined you’ll hopefully see a clean keyword ranking report. The (not set) value at the top indicates that no rank was captured, most likely because it was not an AJAX search result.

Now, there are other ways to configure these filters to combine keyword and rank, or exclude non-AJAX URLs. I’ve chosen to do it this way because I find it easier to view and more flexible in creating additional filters and custom reports. That’s not to say that you couldn’t create yet another profile to try different filter variations. Don’t be afraid to try (and break) things until you figure it out.

In my next post I’ll show you some ways to configure ranking reports and gain additional keyword insight.

How To See Google Analytics Traffic Faster

February 01 2010 // Analytics + SEO // Comment

Sometimes you want to see your Google Analytics traffic faster. Whether you’re obsessive, impatient, troubleshooting or benchmarking, you might find yourself frustrated with the 3-4 hour time lag, particularly if it’s a site with a decent amount of traffic.

Stop Waiting for Google Analytics Traffic

Here’s a quick and easy tip to see your Google Analytics traffic faster. (Remember, this only works if you’re looking at intraday traffic.)

Go to the Visitors > Visitor Trending > Visits report in Google Analytics. Then make sure you’re looking at the graph by hour. The report will look something like this.

Google Analytics Traffic Graph

Now, in the far right select the Advanced Segments drop down and choose one of the default segments. My favorite is Non-paid Search Traffic. Then deselect All Visits so only Non-paid Search Traffic is checked. The result? You get a peek at a few more hours of traffic.

Google Analytics Non-Paid Search Graph

You can leave All Visits on to see the difference between the two if you’re really interested. For me, it’s all about looking at the day’s traffic in comparison to the same day last week. Using the same report with All Visits you get something like this.

Google Analytics All Visits Comparison Graph

Look at just Non-paid Search Traffic and you get to see those most recent hours. This is the report if you’re serious about SEO.

Google Analytics Non Paid Search Graph Comparison

You can use any of the default advanced segments and can usually use any custom advanced segment that produces enough traffic. So stop refreshing your dashboard stats again and again without success. Instead, follows these few steps and get ahead of the curve.

Twitter and Google … Analytics

May 08 2009 // Analytics + Social Media + Technology // 2 Comments

Twitter is using Google Analytics

Earlier this month Twitter launched new HTML versions of their Follower and Direct Message emails. Upon clicking through one of these newly designed emails you’ll notice that the links all contain Google Analytics parameters.

Twitter and Google Analytics

For those of you without the best eyesight, the URL contains the normal utm_ parameters. In this case Twitter is using source=follow, medium=email and campaign=twitter20080331162631.

What is twitter20080331162631?

It is not a user id since a Google search for twitter20080330062631 shows results for more than one user. The first part looks like a date, but March 31, 2008 seems like an odd choice for something just released. Any ideas?

Why is Twitter using Google Analytics?

The obvious answer is Twitter wants more accurate or easily accessible metrics. But why select Google Analytics? Sure it’s free but Twitter isn’t hurting for money, are they? Twitter could use any number of other solutions.

Many believe Twitter is a Google competitor and/or acquisition target which makes using Google Analytics more intriguing.

Wouldn’t Twitter be just a little bit paranoid that Google would peek at the Google Analytics data to gain insight into their business? Sure it’s not supposed to happen but … why take the chance?

Or is Twitter using Google Analytics to provide due diligence data to Google for a potential acquisition? Google certainly wouldn’t doubt numbers generated by their own product. Is this part of the rumored negotiations taking place between Google and Twitter?

Google Killer or Google Accomplice

Outside of the conspiracy theories, Twitter’s usage of Google Analytics further cements them as the leader in the analytics space, surpassing competitors such as Omniture and Coremetrics.

PowerPoint decks at conferences are peppered with Google Analytics graphs and screen captures. In a difficult economic environment it becomes more and more difficult to rationalize using a paid product when a free product has a similar feature set.

Twitter isn’t a Google killer. Instead it’s helping Google to kill web analytics providers.