Google Introduces Weighted Sort

If you want to fine tune your website in an effort to increase sales you absolutely must pay attention to what your website analytics is telling you. In short, you must know where your problem spots are if you are going to be able to correct them.

Now, there are a number of website metrics that should be focused on in an effort to uncover problems. One of them is your bounce rate — both website wide, and on individual pages throughout the site.

Now, don’t confuse bounce rates with exit rates. The two represent different items. A bounce rate can be defined as follows:

Bounce rate represents the percentage of initial visitors to a site who “bounce” away to a different site, rather than continue on to other pages within the same site. Or in other another way of saying it is the percentage of visits where the visitor enters and exits at the same page without visiting any other pages on the site in between.

It goes without saying that ideally you want your bounce rate as low as possible.

To determine where you have problems associated with bounce rate it is best to drill down on a per page level and determine which pages produce the highest bounce rate. Until now, doing this worked similar to the following: you locate the content sections of your site within analytics, you click the bounce rate column to sort from highest bounce rate to lowest, you are presented with a list of pages from 100% bounce rate to lowest and then you start to scan / scroll / analyze those returned based on what is really important and indicates a problem area.

The initial results returned using this method are useless. You get pages with 100% bounce rate that really don’t indicate a problem spot and for the most part are only listed at the top because of their ‘100%’ measurement. Now, you might be asking how can a page with a 100% bounce rate not be a problem. I’ll provide you with a brief example of this very concept.

One visitor arrives at a page deep within the site (we’ll say the contact page) and then bounces leaving analytics with a 100% bounce rate. One thousand visitors arrive at the home page and 500 bounce leaving a 50% bounce rate for the home page. Although the visitor who arrived at the contact us page resulted in a 100% bounce rate, the more important bounce rate to pay attention to is the bounce rate of the home page. Why? More visitors arrived at the home page than the contact page and thus, the ‘weight’ of the bounce for the home page is more of an indicator of a problem point on the site. Think of it as working with a “larger data sample.”

Having provided this example it now becomes clear that the past sorting method offered by Google Analytics did little to quickly provide the information needed to help make decisions fast. Yes, you could get to it, but even after sorting you had to wade through pages of information to really find those pages that should get attention.

All that has changed with the addition of weighted sort in Google Analytics. Weighted sort enables you to now drill down on previously useless sort results based on the ‘weight’ each page (in this example) has over others on the site. This provides more relevant results faster and thus makes it easier to determine where to focus your attention when attempting to improve your website.

You can read more about the new feature and how to use it here:

http://analytics.blogspot.com/2010/08/introducing-weighted-sort.html

80 Google Website Optimizer Tests for Ecommerce Sites

For those of you have have not seen these yet I thought I’d post links to two very nice articles on what you can do to utilize the power of Google’s Website Optimizer.

Google’s Website optimizer is a powerful tool that enables you to increase the conversion of your website using testing methods such as Multivariate and traditional A/B split testing. When setup and utilized correctly, Website Optimizer gives you the ability to discover what really works to turn visitors into sales (or just about any other action you are seeking from your audience). No more guessing.

For any of you have have already tried your hand at “manual” split testing, you know it can be tedious, time consuming, and down right tough to keep track of all the possible combination’s that are put together for any given test. That process is made much simpler with the use of Website Optimizer.

The instructions for setting up optimizer are easy to follow and do a great job for even newbies on helping them get up and running (although if your cart requires programming to integrate the code into the pages you may need the help of your technical team).

One article circulated last year and was titled 55 Google Website Optimizer Tips and Tricks.

The other surfaced February 23 of this year as a “sequel” to that original post and it is titled 25 Google Website Optimizer Tips for Better Product Pages.

Together these articles combine to provide a total of 80 different tests you should consider running on your site. I highly recommend reading them and keeping them on your bookmarked list for future reference.

Tracking Google Product Search Traffic in Google Analytics

I recently had a member ask me this question and after some research found a number of answers. All were interesting.

The question we are looking to find an answer to is “how can we track traffic arriving from Google’s Product Search separately from all other traffic within Google Analytics?” For those of you not familiar with it, Google’s Product Search provides product based results on items that are loaded through Google Base accounts.

Here are two main options I found for accomplishing this.

The first option is a quick way to use filters in GA to segment the traffic. This option might be best for sites that have a lot of product linked urls listed in Google Product Search. The second method uses url tagging (we talked about this in recent posts) and can be arrived at two different ways and although works, might not be the best if you have a lot of urls to change.

Option 1 (Use GA Filters):

Using filters can help alleviate the need to tag many urls. We can setup a filter within GA that segments the data we are already receiving and breaks out the portion of traffic that comes from Product Search. Here’s how:

When you perform a search on Google, you’ll see that your results page has a URL that looks something like the following:

http://www.google.com/search?hl=en&q=product+search&aq=f&aqi=&aql=&oq=&gs_rfai=

The key point to note here is that when performing a search from the Google Search Engine all searches start with the following string:

http://www.google.com/search?

However, when you perform a search from Google Products the url looks something like this:

http://www.google.com/products?hl=en&q=product%20search&um=1&ie=UTF-8&sa=N&tab=wf

The key point to note here is that when performing a search from the Google Product Engine all searches start with the following string:

http://www.google.com/products?

Knowing this we can setup a filter using the Referrer field to differentiate between the two and then use the Source field from within Analytics to view the data based on referrer.

Field A in our filter looks for a Referrer like one of the Google URLs shown above. Field B limits the data returned to only organic searches (AdWords ads can appear on the Google Product Search pages also, and we don’t want to mess up that reporting). The Output To section actually changes (or rewrites) the Source to “google base” instead of just “google”.

Here is what it would then look like in reporting:

Option 2 (Use URL Tagging):

Method 1:
If you don’t have a lot of URLs to tag and want to do option 2 then you might be able to get away with the information presented here:
http://www.google.com/support/merchants/bin/answer.py?hl=en&answer=160634

Method 2:

If however you have lot of product URLs to tag and want a better way of doing it then the following might be a better option.

This method uses the same concept I had introduced in previous post on using Google’s URL Builder to for tagging.

In this method though we tag the URLs with:

?utm_source=google&utm_medium=base&utm_campaign=products

The components that are going to let us get segmented reporting on the traffic from Product Search within Google Analytics are source=google and medium=base.

When you go this route your reports will be broken down as follows:

Here are the steps to follow for tagging your URLs:

We are going to use the native Excel format for the feed to address the tagging.

1. Download your product feed and open it with Excel

2.Insert two columns to the right of the column that contains your product URL (column header should be “link”)

3. Write your tracking code into the cell to the right of the URL (see below):

4. In the next cell to the right the one you just inserted, write the following formula, substituting cell numbers if appropriate:

=CONCATENATE(B2,C2)

You should see a result similar to the screenshot below showing the two cells merged together:

5. Copy the cell formula all the way down to cover all of your products so that all of them having the tracking added.

6. Highlight all of your product URLs (in the third column of the spreadsheet) which now have the tracking code added, and then copy and paste them into Notepad

7. Delete the columns you’ve just created so that you only have the ones you started with.

8. Paste in all of your new URLs over the top of the old ones – you have to do this in order to get the spreadsheet back in a format to be uploaded – the extra columns will be rejected.

9. Upload revised feed to Google

10. After a day or two, log into Analytics and go to traffic sources. You should be seeing traffic from Google / Base showing.

5 Steps to View Your Facebook Fan Page Stats in Google Analytics

If you’ve had a Facebook Fan Page set up for any amount of time, you may have noticed a little thing called Facebook Insights. This “tool” is reportedly Facebook’s answer to analytics.

Most SEO and social media consultants will feel compelled to tell you that Insights offers very little insight. Aside from who has commented on your updates and the age, gender and geographical breakdown of your fans, there isn’t much other insight Insights can provide.

Almost makes you wish there was a way to use Google Analytics to see how your Facebook Fan Page is doing doesn’t it?

I’m happy to report, after finding a hack produced by the folks at Webdigi, a London-based Web Development company, there is a way to set up your GA account to retrieve Facebook stats.

Here’s how:

1. Assuming you already have a Google Analytics Account, set up a new website profile, titling the new profile “Facebook,” “Facebook/URL” or something you’ll know is your Facebook analytics. Be sure to find and copy the UA code provided once you set up the new profile. (the code will look something like UA-#######-#)
2. Because Facebook allows for limited Javascript (whereas Google Analytics required a more robust use of Javascript), you’ll need to create an image of each Facebook page you want to track. Luckily, Webdigi has a Google Analytics link generator for Facebook pages (http://ga.webdigi.co.uk/) available for free use (thus far, this is the only tool available that I can find that does this sort of link generation for Facebook to GA).
3. Copy the entire Webdigi code provided into the part of the Fan Page you are tracking. (For instance, if you want to track your coupon tab, discount tab and special offers tab you’ll need a separate code for each page.) You’ll need to paste the code in an FBML on that page, below whatever HTML you may have used in the FBML (see image).



4. To track your Facebook Fan Page Wall, you’ll need to create an FBML page which can be transferred into a box that appears on the left hand side of your wall. One of the best ways to do this is to post a list of resources or links, embedding the Webdigi below your HTML.
5. Google Analytics will take approximately 24 hours to confirm your code and begin to report results. Once the checkmark appears next to the name you’ve designated for your Facebook Google Analytics, you will be able to measure metrics above and beyond what Facebook Insights provides.

Using Google Analytics to Track Email Campaigns

In past articles I talked about using Google’s URL builder to track traffic from paid search channels outside Adwords (like MSN and Yahoo for example.)

In this article I thought I’d quickly show you how you can apply that same technique toward tracking of email campaigns as visitors have asked this as well.

Remember, generally Google Analytics looks for a few basic values in each link (yes you can track more items, but these are the basics.) The three basic pieces of information Google looks for in links is the campaign source, campaign medium and campaign name. The actual Google variable representations are listed below as a refresher but I have included some text that will help you from the email perspective.

1. Campaign Source (utm_source). This identifies the name of your email marketing system, such as ConstantContact. If you don’t use a thirds party email marketing system, you can label your campaign source something general like ‘Email Marketing’.

2. Campaign Medium (utm_medium). This identifies the campaign instrument used. In the case of email marketing, your medium is ‘email’.

3. Campaign Name (utm_campaign). This identifies the name of your campaign. The Campaign Name helps you differentiate between various campaigns or unique messages within each. Most Email Marketers use their message subject line or other identifying value for this parameter.

Here’s what the URL Builder might look like with those three variables filled in for an Email campaign:

Viewing Email Campaign Results

Once you have built your url and inserted it into the proper location within your email, tracking will automatically begin. With the tracking results you can find out a number of things including: which links were most popular with your recipients, when they visited your website, how long they stayed and where they navigated following arrival.

With this information you can refine your future email marketing to gain better results.

How to view campaign results in Analytics:

1. Log into your Google Analytics account.

2. Click ‘Traffic Sources’ from your Dashboard.

3. View your ‘Top Traffic Sources’ or click ‘View Full Report’ to see all traffic sources.

4. Locate and click the link identifying your email marketing Campaign Source. In our example above, your Campaign Source is your email marketing product, i.e. ConstantContact, or ‘Email Marketing’.

On your Campaign Source page, Google Analytics provides details on the number of visitors generated by your campaign, the number of pages they visited, average time on your website, percent of new visitors to your website and the average bounce rate.

Campaign managers can also drill-down using the segments drop-down menu. This provides even greater detail on individual campaigns, keywords, geographic regions, browser types, operating systems and visitor activity, like the most popular landing and exit pages. Each results page provides the means to drill-down even further and fine-tune your data.

Here is what the top level report might look like when segmented by ‘Source’ in Google Analytics:

Here is what the top level report might look like when segmented by ‘Medium’ in Google Analytics:

Here is what the top level report might look like when segmented by ‘Campaign’ in Google Analytics:

To get more detailed information on each you can further filter, segment, etc… and even drill down by clicking the link to the page you want to see more information on.

Now, if you haven’t had the ability to do so already, you can get better metrics from your email campaigns within Google Analytics.

Got any other ideas for email tracking with GA? Post your ideas below. I’d like to hear them.

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