Two types of search engine traffic

We can break search engine traffic into two types: research and bookmark.

• Research is pretty straightforward; a visitor was looking for a solution to a problem: “I want a new pair of shoes from a company that cares about people.” They use keywords like, “shoe company that donates shoes” and they discover a new company.
• Search engines as bookmark traffic is much different. “I know the product/company I want, but I am not sure I remember how to get to their website.” These are two very different kinds of search intentions but unfortunately web analytics systems have no way to differentiate the two.

The attribution problem

Attribution is giving credit to the traffic source that a visitor used before making a purchase or some other event that we value. With all of the major web analytics solutions they have decided that the last source of traffic is the one that should get the credit.

In Google Analytics, when someone visits your website from a referring source, Google Analytics’ JavaScript sets a cookie on the visitor’s machine with information about the referring source. Each time that visitor returns, the cookie gets overwritten with new referrer information. The only time a traffic source doesn’t get overwritten is when the visitor types the URL directly into the web browser or if they use a bookmark. This is considered direct traffic and isn’t seen as attributing to the purchase. Most of the time this makes perfect sense, but when visitors use search engines as a bookmark it skews our data.

Using our previous example of Jason and Tom’s shoes, Google analytics attributes the purchase with the organic search result and no credit goes to the ad. Clearly Jason’s intent when visiting Google was to get to Toms.com. The ad that brought him to the website during his research phase doesn’t get any of the credit.

If this kind of “search engines as bookmark” traffic is really just a different kind of direct traffic, then why not report it as such? This will prevent your those brand name keywords from getting credit for the sale and make sure your ads get the credit they deserve.

A simple solution

If you’re using Google Analytics you can easily modify the JavaScript code to treat organic brand name traffic as direct traffic. Locate your Google Analytics JavaScript code. If you are using the new code, the first portion will look something like this:

var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-123456-7']);
_gaq.push(['_trackPageview']);

Just before, “_gaq.push(['_trackPageview']);” you will want to add, “_gaq.push(['_addIgnoredOrganic', 'keyword']);”, for each brand name keyword you want treated as direct traffic.

var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-123456-7']);
_gaq.push(['_addIgnoredOrganic', 'keyword']); // if referrer is organic do not override referrer
_gaq.push(['_trackPageview']);

Now search engine traffic, where the visitor is using your brand names, will be treated as direct traffic by Google Analytics and will not overwrite any previous source information.

With 90+ standard reports, advanced segmentation, custom reporting, and plenty of other amazing enterprise features, I’m not breaking any new ground here by saying that Google Analytics is a great web analytics solution. It has always bothered me though, that without live tracking it can be difficult to troubleshoot, diagnose problems, confirm that you properly set up your eCommerce conversion tracking or some other custom JavaScript implementation. Waiting 8-12 hours to see if data is still being collected, or if your “test transaction” is being reflected in your reports is no way to work in an enterprise environment.

The solution is to use an HTTP proxy debugger

An HTTP proxy (HTTP Monitor) sits between the internet and your web browser. It is able to record and display all of the data that is sent and received between your web browser / client and the server. This makes it easy to see exactly what information is being sent to Google Analytics, so you can quickly diagnose and fix problems.

In my example I am going to use a web debugging application called Charles, you can download a free-trial from their website. There are plenty of other HTTP debugger applications you can use I just happen to use Charles.

1. Launch your application, You may be prompted to give it privileges on your computer.
2. In your web browser visit the page that you contain your Google Analytics code.
3. If you look in the HTTP debugging application you will see all of the HTTP requests that were made by the page. In the list you will see http://www.google-analytics.com
4. In Chrles you can click on the arrow to reveal the two HTTP request that the page made. The first request was made to by the Google Analytics JavaScript file and load it into your system memory. You can look through the window on the right to see the status file. A response code of 200 means that the JavaScript file was loaded successfully into your browsers memory. So far so good.
5. The next item in the list is that data string that was sent to Google analytics as a response to you visiting the page. There is a lot of data here but if you break it up by the “&” it is easier to find what you are looking for:
   • http://www.google-analytics.com/__utm.gif
   • ?utmwv=4.3.1
   • &utmn=1482837383
   • &utmhn=www.freshclicks.net
   • &utmcs=UTF-8 – the encoding charset of the content
   • &utmsr=1280×800 – screen resolution of the visitors monitor
   • &utmsc=24-bit
   • &utmul=en-us – browsers language setting
   • &utmje=1
   • &utmfl=10.0%20r22
   • &utmdt=Fresh%20Clicks%3A%20Analytics%20and%20eMarketing%20Strategies%20%C2%BB%20MailChimp%20Review%3A%20Email%20Marketing%20Provider – Name of the site and Page title
   • &utmr=-
   • &utmp=/download/emailWhitepaper.pdf – tracks downloads as virtual pageviews
   • &utmhid=1822260590 – unique id to track this user in Google Analytics
   • &utmr=0
   • &utmp=/2009/04/06/email-marketing/mailchimp-review-email-marketing-provider/
   • &utmac=UA-475241-7 – The Google analytics code associated with your account
   • &utmcc=__utma%3D144287458.1535030466.1246519340.1246519340.1246519340.1%3B%2B__utmz%3D144287458.1246519342.1.1.utmcsr%3D(direct)%7Cutmccn%3D(direct)%7Cutmcmd%3D(none)%3B – This last bit is information about the cookies that have been set. You can see that UTMZ is responsible for seting the campaign information about the source of the traffic.

   I couldn’t identify all of the variables it was collecting so if you happen to know any of them send me a note via twitter@LaryStucker so that i can update this page.

As you can see in this example, it is easy to use web Proxy debuggers to determine if Google Analytics is being executed properly and if Google’s servers are receiving the proper information.

If you found this information helpful, have questions or want to mention one of the other HTTP proxy degugging solutions please leave a comment or message on twitter @LaryStucker

Problem

Unless you can get your visitors to identify themselves (fill out a form, sign up for a service, etc.), their visit is going to go completely undetected; however, it doesn’t have to.

Solution

Within Google Analytics, there is a report called “Network Location”. ¬† It reports on which internet service providers your visitors are using. ¬†This report allows you to track the internet service provider (ISP) domains to which the user resolves. The domain is determined by the internet service that owns the user’s internet protocol (IP) identifier. At first this doesn’t sound like it will be of much use in determining which companies are visiting your website except for the fact that most businesses own their IP address.¬† So, what you see in this report is both generic ISP traffic (AT&T networks, Verizon internet services inc., road runner holdco llc, etc.) along with schools, businesses, and government agencies.

If you¬†using Google Analytics¬†then you already have “Network Location” reports, but like most reports you should probably create an automated processes for reviewing the results.

Setting up daily Network Location reports

When it comes to tracking corporate activity on your website, you should try to look at the results on a daily basis.¬† Knowing Apple came to your website a month ago isn’t going to do anything to help your sales team today.

1. Log into your Google Analytics
2. Click on the  button
3. Click on Network Properties and then on the Network Location link.
4. Change the date range to yesterday only and click “apply”.
5. Click the “Ave. Time on Site” column so that the results are sorted by the visitors who spent the most time first. (I choose “Ave. Time on Site” because it is the easiest to indicate interest level in these kind of reports.)
6. Click the email icon just above the “Network Location” title.
7. Click the Schedule tab and fill out the information. Make sure to change the Date range to “Daily(sent each morning)”¬†and make sure that “Include date comparison” is not checked.
8. Click the “Schedule” button and you are done!

You will start receiving your daily Network Location reports via your email.

Here is an example excerpt from a Network Location report:

Hmmm...why is Apple coming to my website?

If you found this article helpful, interesting, or you want to add your two cents, please leave a comment below!

You can see areas where they have changed code and stopped web site functions in order to improve website retension:

/* Commenting out to try to fix exit and bounce rates in Google Analytics */

What I find most encouraging is that our new president seems to have surrounded himself with smart people.¬† Including people who know how to leverage technology like Google’s Website Optimizer and Analytics¬†to¬†improve their campaign, while at the same time keeping down their overhead.

What Web Metrics should you start measuring today and why?

• Visitors: What is the average number of visits to your website?
• Conversions: Conversion can mean many different things depending on your business. A Free trial download, the sale of a product, and the completion of a contact form are all types of conversions that have value to your business. You should know the average number of conversions and the number of conversions per visitor to your site.
  FORMULA: # of Conversions/ # of Visitors = Conversion rate%
• Most popular pages on your site: What content on your website is attracting the most views? How has this changed over time? I have recently seen a secondary product’s landing page surpass a company’s flagship product in popularity well before the Executives finally realized that the market has changed and they should change their marketing focus.
• Top referring sites/mediums: How are visitors coming to your website? Which search engines, forums, articles, paid ads, or email are driving visits and conversions to your site?
• Top keywords: What keywords are visitors using to find your site? What keywords do visitors use that convert into sales/ leads/ contacts? What keywords don’t you see? Sometimes the most telling keywords are the ones that you don’t see. If you sell air filters for Chevy trucks and you have zero visits to your site for the Keywords “Chevy air filters”, you have some serious Keywords and Pay-Per-Click optimization to do!
  
• Average visit time and average number of pages per visit (this is also known as engagement): When someone arrives at your website, how engaging is the content? Do they stick around and visit multiple pages? This can vary greatly by referrer and keywords visitors use to arrive at the site as well, so make sure that you keep a close eye on your primary keywords and referrers. Also keep an eye out for new sources of traffic that have a higher engagement level than your site average.
  
• Bounce rate: The opposite of engagement – this is a measurement of the visitors that left the site as soon as the page loaded. This is going to happen, so don’t get to discouraged by the numbers. Depending on your industry your bounce rate should stay under 50%. Anything higher than that may mean that your site is either optimized for the wrong keywords or you are targeting the wrong markets.
• Geographic and language settings: Where in the world is all of this traffic coming from? Of course, if your product or industry has international appeal you would want to know which countries and what languages your visitors speak, but even local business should be looking at this information. For example, when we started looking at the traffic from regions where a local contractor actually serviced, we noticed that 75% of those visitors had their language setting set to Spanish, but the website was only in English. Obviously, it became a high priority for that contractor to offer a Spanish version of his site.

For each of these metrics, you should know if the numbers are increasing or decreasing? Is this a seasonal trend or is this a part of some other market force?

How often should you check/ report on your web metrics?

It can be very addicting to check these metrics constantly and you have to be careful not to spend all of your time poring over the different variables. So, the question that I am often asked is how often should you check your web metrics? Daily, weekly, monthly? The typical answer I give is as often as you can take action based on the results. If you started a new Pay-Per-Click campaign, you probably want to watch the results on a daily basis at first to make sure that it is performing properly. If you spot any anomalies, you can catch them right away and take corrective actions.

Well, that should be enough to get you started. If you have any questions or you found this article useful, please leave a comment!

Web analytics can answer all of those questions, and it can show you how effective your marketing efforts are by visitor language.

I will be using Google Analytics, but you can use most analytics tools to easily look at visits and purchases by the language setting of the visitor’s browsers.

Click on: Visitors-> Language

Gather the following information:

• Total number of visits to the site
• Number of visits by Top 10 languages
• Total number of Sales on the site (if you are not running an eCommerce site then you can also look at number of conversions)
• Number of sales by those top 10 languages

Quality index Reports:

Quality index reports are a top level measurement designed to show how well a particular metric is performing when compared to the site as a whole.

The formula is: Quality index = % Goal Conversions from metric X / % visits from metric X

• 1.00 = metric X is equal with site average
• >1.00 = metric X is less likely to convert
• <1.00 = metric X more likely to convert

So for our Internationalization KPI (Key Performance Indicator) we will look at how well each language performed when compared to the website. Anything over 1.0 means that it performed that much better than the site average.

Quality index by Top Languages

• English-US: 1.67
• Chinese: 0.01
• French: 0.74
• German: 1.12
• Russian: 0.05
• Spanish: 0.55
• Japanese: 0.70
• Taiwanese: 0.12
• Portuguese: 0.04
• Italian: 0.32

One thing we notice right away is that are second largest source of traffic by language (Chinese) is performing terribly. This also turns out to be a great opportunity for our current situation as well. Chinese speakers are obviously coming to the site looking for our products but the site isn’t currently catering to Chinese speakers. I would put them first on the list of our internationalization project followed by either Russian or French. French speakers are coming in much higher volumes then the Russians and optimizing their user experience would probably have better results.

This is a great metric to track over time especially when looking for new international markets to enter.

Please let me know if you find these kinds of articles helpful to achieving your web analytic goals.