Problems

It was a very helpful funnel that provided some insights in the way people went through an ordering process. But there were also some huge problems with this funnel:

• People going from step 2 to step 1 to step 3 and then converted were simply counted as going from 1 to 2 to 3 to the thank-you page.

• People going from step 1 to step 3 and then converted were added to step 2 to simply 'fix' the funnels' numbers.
• The "required step" option only works in the funnel view for a goal and not for that goal in other reports. The funnel could look as if it had 100 conversions whether the site had 1000 conversions for the same goal.
• If people went from step 1 to 2 to 1 to 2 to 1 to 2 and converted they were counted once for each step.
• Segmentation on funnels wasn't possible, the only way to create something like that is by using horizontal funnels

The second mentioned 'fix' was also a problem if you have a funnel were the second step is optional. You would suspect to see people exit in step 1 to return in step 3 rather than being counted in step 2 were they have never been. Therefore optional steps are almost impossible to analyse in the old funnels.

New funnels called Goal Flows

But now we have Goal Flows *insert magical music*! First, take a look at this screenshot I took:

It's a typical funnel with 5+ steps in it. And I want to highlight 2 cool things you can see here (marked purple):

1. You see the purple arrow above step 2? That line represents the people that skipped step 2 in this funnel. So in stead of adding them to step 2 they go around step 2. It could be a registration step that people can skip if they want to order as a guest, for example.

2. The second arrow after step 5 shows you the people that went back to step 4. Perhaps they wanted to change some things before continuing to step 6, we were never able to see that before.

This new visualization gives you a much better insight in the way people move through your funnels. The steps can also be segmented to see if some groups are behaving different than suspected. And if you want to zoom in on a specific step to analyse exit behavior for that step you can easily choose "Explore traffic through here":

Tips

A few simple tips I want to give:

• If you set up a new funnel be sure you include optional steps, they are presented in a nice way

• Segment your funnel for several browsers or resolutions to see if some stay behind in CTR, that could indicate a usability or script error
• Analyse each step and zoom in to get an idea about what is happening there
• Test, test, test

What do you think? Anyone got some really cool insights to share?

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But, there is a big but. A lot of outbound link tracking is done like this:

<a href="http://andrescholten.net" onclick="trackClick(this)">Nice site</a>

And this is what happens when you click on this outbound link:

1. The onclick is executed first
2. The trackClick function generates an IMG element with a URL that points to the Web Analytics vendor
3. The onclick function is handled and the browser starts with the href part

And then the race starts:

• The tracking pixel is requested from the Web Analytics vendor
• The browser kills all activity and opens the URL in the href attribute

But we can't tell which one is first. A small delay on the Web Analytics vendor side is deadly for the tracking, often the pixel request is killed by the browser. You can see this in a simple tool that shows you all activity in your browser. Because Yoasts' post is was the trigger to blog this I will use his site as an example.

Take a look at his Clicky outbound link tracking post. It has an outbound link in the first sentence. And this happens when I'm clicking it:

The first two lines are the main Clicky script with all tracking functionality and the basic pageview measurement. The third line is the outbound link tracking: in this case the tracking is send. The line is red because the browser stops waiting for the response, but that isn't necessary for the tracking. Sometimes this line isn't generated and no tracking is done...

A solution

In the post title I mentioned 70%, but that's merely a guess based on what I have seen in cases where I solved this. After implementing a little timeout before the link opens we saw a lot more outgoing links being measured. I already mentioned the solution: a little timeout to give the tracing some time to execute before the link opens.

But there are a few caveats using this technique:

• Using "window.open" triggers the popup blocker of Internet Explorer 9+. That's because the link is opened with a script in stead of a user initiated click. We have to use location.href to prevent that from happening.

• Using "location.href" doesn't pass on referrer information in Internet Explorer 6, 7 and 8. External site won't see traffic coming from you.

This is de jQuery code I use right now to track outgoing links:

if(typeof jQuery == 'function')
{
  jQuery(function ()
  {
    jQuery('a[href^="http"]').click(function (e)
    {
      var url = this.toString();
      if (url.indexOf(document.domain) == -1)
      {
        _gaq.push(['_trackEvent', 'clickouts', jQuery(this).attr('href').replace(/https?:\/\/(.*)/,"$1")]);
        var target = jQuery(this).attr('target');
        if (target == "") { target = "_self"; }
        setTimeout(function()
        {
          var a = document.createElement("a");
          if ((!a.click) || ((jQuery.browser.msie) && (parseInt(jQuery.browser.version) > 8))) {
            location.href = url; // for chrome and IE9+, target is lost
          } else {
            a.setAttribute("href", url);
            a.setAttribute("target", target);
            a.style.display = "none";
            aElm = document.body.appendChild(a);
            aElm.click(); //  for IE6,7,8 to pass on referrer
          }
        }, 50); // 50ms should be enough timeout
      }
      e.preventDefault();
    });
  });
};

Is this the best way to track outgoing links? For what I've seen this is one of the best and most reliable approaches. But I'm happy to receive additions that makes it even better.

Ps. In this example I used Google Analytics to track outgoing links, but you can change that part to whatever tracking you want.

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In the old Google Analytics there was the "&limit=10000" parameter that you could add to the export URL. In the new interface you can select the amount of rows below the table:

And after everything is loaded you can export those 500 with the usual export button.

The all new and improved method

Today I invented (copied) the code that is needed to export more than 500 rows without showing 10.000 rows on your screen first (as explained here). Create a bookmark and set this as the URL:

javascript:function post_andre(params){var form = document.createElement("form"); form.setAttribute("method","post"); form.setAttribute("action","exportReport"); for(var key in params){var hiddenField = document.createElement("input"); hiddenField.setAttribute("type","hidden"); hiddenField.setAttribute("name",key); hiddenField.setAttribute("value",params[key]); form.appendChild(hiddenField);} document.body.appendChild(form);form.submit();}var rowcount=prompt("Amount of rows (10-10000):","100"); hashes=unescape(location.hash).split("/"); date0=hashes[3].substr(hashes[3].indexOf(".date00")+8,8); date1=hashes[3].substr(hashes[3].indexOf(".date01")+8,8); post_andre({'_.date00':date0, '_.date01':date1, 'explorer-table.rowStart':'0', 'explorer-table.rowCount':rowcount+'', 'id':hashes[1], 'ds':hashes[2], 'ef':'TSV', 'exportUrl':location.href});

When you click on the bookmark it will ask you how many rows you want, and the download starts rightaway.

Notes: for now only the TSV format works, and it's only tested in Firefox and Chrome on several reports. No guarantees

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For instance: I track page load times the same way Google Analytics does, but in an unsampled way (Google only meausures 10%). To do that I fire an event immediately after the trackPageview, but I do that in another profile with a different UA-XXXX-Y number so it won't affect my bouncerates. But now we have an extra parameter:

_trackEvent(category, action, opt_label, opt_value, opt_noninteraction)

If you set this opt_noninteraction (boolean) to true it wil not affect bouncerates!!! That makes it possible to:

• Measure page load times without affecting bouncerate
• Measure banner rotations on a homepage without affecting bouncerate
• Measure mouse coordinates to create heatmaps without affecting bouncerate
• Etc.

Awesome. Don't you think? It saves me a lot of profiles because I can track all events in 1 profile now.

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Why does this suck?

• If Google really had a clear focus on a user's privacy they also wouldn't send the keyword along with an AdWords click (as Yoast tweets). Right now only half of the results are privacy-protected and the other (paid) half not.

• Google claims it will not affect a lot of users, that could be right on average. But for some sites a lot of their target groups are logged in to their Google Analytics, Google Reader, Youtube, Gmail, etc. All those visitors will also be logged in on the search results, and that could mean serious loss of information about the used keywords.

What are the alternatives? The data provided by the Google Webmaster Tools is way off (as Roy tweets), and I agree. I guess we have to rely more on the trends we see based on our actions. But as most SEO's know: diving deep into the data is a must to get a good grip on improvement. It's not all about trends. Also some behavioral targeting tools won't work a 100% anymore if you want to target specific keyword groups.

There's one advantage: if you search secure through a WiFi connection it's harder for bad persons to be able to retrieve what you where searching for.

What do you think about these changes? Positive, negative? I have a feeling that this change is for other reasons than they claim.

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How does it work

In the toolbars of all my browsers I have this little button:

When I click on it when I'm on a page that is running a live test this popup shows up:

By altering the combination I can put myself in another variant of the test. Just refresh the page and the chosen combination will show up.

How to create this button

Create a new bookmark called "VWO Variant Switcher" or whatever name you find suitable. Then edit the URL the bookmark is pointing to:

And change it to:

javascript:var%20names="Combinations%20in%20test:\r\n\r\n"; if(typeof%20_vwo_exp_ids=="object"){for(x%20in%20_vwo_exp[_vwo_exp_ids[0]].comb_n) {names=names+x+"%20=%20"+_vwo_exp[_vwo_exp_ids[0]].comb_n[x]+"\r\n"; }};function%20readCookie(name){var%20nameEQ=name+"="; var%20ca=document.cookie.split(';'); for(var%20i=0;i<ca.length;i++){var%20c=ca[i]; while(c.charAt(0)=='%20')c=c.substring(1,c.length); if(c.indexOf(nameEQ)==0)return%20c.substring(nameEQ.length,c.length); };return%20null;}; if(typeof%20_vis_opt_experiment_id!="undefined"){var%20id=_vis_opt_experiment_id; var%20cv=unescape(readCookie("_vis_opt_exp_"+id+"_combi")); txt=prompt(names+"\r\n\r\nChoose%20combination:",cv); if(txt!=null){_vis_opt_createCookie("_vis_opt_exp_"+id+"_combi",txt,100); }}else{alert("No%20live%20experiment%20on%20this%20page.");}; void(0);

That's all. Enjoy testing and viewing.

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To give a clear understanding about the differences I want to show you this image:

This image shows all steps from the beginning of a request for a page to the end. The timing of all these steps are stored in a global javascript object called "performance". And with a simple script you can read out all these timings to calculate the load time. This comes directly from the Navigation Timing specification of the W3C.

The green line is the timing I measure in the above mentioned article, that means: only the time from when the HTML starts loading until the onload event happens.

The red line is the timing Google uses to measure page load time in Google Analytics. A much more trustworthy number because it includes server response times. But Google only uses a sample of this data to calculate page load times.

The best way is a bit of both: the more trustworthy measurement method of Google but without the sampling. That can be done with a simple addition to the Google Analytics tracking script:

if (typeof performance == "object")
{
  var loadtiming = parseInt(performance.timing.loadEventStart – performance.timing.fetchStart);
  if ((loadtiming > 0) && (loadtiming < 40))
  {
    _gaq.push(['timer._setAccount', 'UA-XXXXXX-X'], ['timer._trackPageview'], ['timer._trackEvent','w3c-navigationtiming',location.pathname,,loadtiming]);
  }
}


You can execute this code after the onload so visitors won't be slowed down and be sure to use a NEW Google Analytics profile, and not your main profile, it will ruin bouncerate measurements. The loadEvenStart and fetchStart are also the ones Google used in their Google Analytics trackPageLoadTime functions.

Now there's only a small disadvantage with this script: not all browser are supporting this new "performance" object, right now only Google Chrome supports it. But as Site Speed is becoming more and more important I suspect that other browsers will add it soon.

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The older browsers and slower connection types have a negative impact on page load times. So they should show us numbers for people with a slower user experience.

I created a spreadsheet and downloaded the data from lots of clients into this sheet. I segmented them by connection type and browser and calculated the average revenue per visitor. These numbers are based on 206.778.873 visits that did €4.540.594.926,86 on revenue. That makes an average of €4.97 per visit.

The browsers

We all know that Internet Explorer has 3 versions that have improved a lot in time: IE6, IE7 and IE8. And all three of them are still responsible for a lot of visits, although IE6 is losing fast lately. I created three groups and the results are:

Amazing isn't it? The value per visit goes from €3,59 to €5,45 (a 50% improvement). So please force your customers to update their browsers so they are willing to spend more....or do we have to speed up our sites

The connections

The connection speed is also a major factor in the user experience. A slow dialup connection doesn't make you happy when surfing around a shop that has uncompressed 8MB images online to show their products. Let's see if this is also represented in the numbers:

The difference is not as big as the browsers show, but there's still enough impact.

Both combined

I combined both browsers and connections so see if for example IE6 + Dialup would be the worst performing couple, and yes:

From left to right the browsers and connections in the order as you would expect. Especially IE6 has a big impact on the numbers, but dialup is not te be ignored also.

And now?

You have the data.
You can calculate the numbers.
You can create a business case.
Start optimizing your site!

The load time of your pages has impact on SEO, AdWords Quality Score, the conversion percentage, server load, pages-per-visit, etc, etc. You can't afford to have a slow site.

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"Fixed a bug in Custom Variables that caused some values to be encoded in reports."

Spaces (and other characters) were reported as "%20". So if my name was in a customvar it would look like this:

andre%20scholten

But as of may 18th it's being reported as:

andre scholten

The advantage is that you get cleaner reports with nicer values, but your graph for certain customvars will look like this:

The traffic for the old ones drop, and new customvars will rise. So don't be scared when you miss a specific customvar, just look for the cleaned-up version

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But as of the new update we have an extra option. If you right-click on a Flash object you see this new option called "Global Settings" that brings you to this menu:

In the middle are three radioboxes that allow you to block all Flash cookies if you want. And there's a "Delete All" option that makes it easy to delete them.

It's a good thing to give users more control over these Flash cookies, often they are used to create non-removable cookies. Clever webdevelopers are able to create scripts that can restore removed browser cookies by copying the Flash cookies to a normal cookie. This is also called respawning cookies or zombie cookies (because a deleted browser cookie is back again on browser reload). And this is kind of a privacy thing, because users are not able to decide themselves which sites may track them.

Happy deleting

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The script I'm going to explain will track page load time and page render time per individual URL. I know some other articles that describe a comparing technique but I really think the way I use it gives you more insights (at least for smaller sites).

Sitespeed tracking is important

I don't have to tell you how important it is to know how visitors experience your site. Sluggish sites will cost you money in the end. Site speed is a minor SEO ranking factor and fast sites tend to have more pageviews per visit and a higher conversion rate.

First the technical part

To get the right numbers in your Google Analytics account you have to add some extra scripts. First a script that tracks the starttime of the page loading proces:

<script type="text/javascript">loadtimer=new Date();</script>

Put this code directly after the <head> tag. Then put the next line just before the </head>:

<script type="text/javascript">rendertimer=new Date();</script>

And last but not least the event tracking code that can be everywhere in your code:

<script type="text/javascript">
window.onload = function()
{
_gaq.push(['timer._setAccount', 'UA-XXXXX-2'], ['timer._trackPageview']);
_gaq.push(['timer._trackEvent', 'loadtime', location.href, , parseInt(new Date() - loadtimer)]);
_gaq.push(['timer._trackEvent', 'time-to-render', location.href, , parseInt(rendertimer - loadtimer)]);
}
</script>

Please use a brand new profile with a different UA number for this script. If you use the same UA number as your regular Google Analytics script this script will mess up your data.

I used the simple "window.onload" as an example here. But in most cases you would use a more robust method for adding something to the onload event of your document.

The results

By adding this script you can see the actual time that it takes for a visitor to completely load a page. This is more reliabe than a n=1 measurement that a tool like WebPageTest can do (no bad words about that tool, it gives you a lot of other useful insights):

If you go to the "event" report you will see two new categories: "loadtime" and "time-to-render". The first one shows you the time it took to completely load the page. The second one is the time people stared at a blank page. If that time is to high you also need to do some updates. If you click on one of those categories you will get the screenshot shown above. The column "Avg. Value" gives you the time it on average took to load a page.

What you can do also is an analysis of the loadtimes per browser, campaign, keyword or country:

I now know my site is slow in the United States, India and China, just look at the numbers. So, if you are worldwide oriented this could be a really important report.

Google Analytics events as goals

It's possible to set an event as a goal in Google Analytics. I created this one to keep track of slow page load times:

Every time someone hits a page that takes longer than 5 seconds to load it will trigger this goal. My target is to keep this number as low as possible

Additional comment:
The described technique only measures the load time after the server has send the first byte (TTFB = Time To First Byte). Make sure you also look at the process before that first byte. Aaron gave some more explanation in the comments.

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First of all: what is Site Speed

The speed of a site is the time it takes from the moment a user navigates to your site (for example through a link) until the site is fully loaded and usable. But there are many factors in this period that helps keeping the visitor patient enough to wait for a full load. The first moment is the moment when the browser begins rendering a site: until that moment people have to look at a white screen where nothing happens. Then the site starts to appear on the screen bit by bit until he is usable. And the last stage is where all the images are loaded to make the site look complete.

The tools to analyse Site Speed

You need a good set of tools to see how your site is doing and what the greatest bottlenecks are during loading. I will describe a group of tools and their pro's and cons. Important things to consider is your target audience: worldwide or several countries, and which browser are they using. You want to test your site on both these areas.

Webpagetest

The first tool I want to mention is Webpagetest.org. This tool allows you to do an analysis of the load time of your site from a list of locations all over the world. The reports are detailed and tell you exactly how the different elements of the tested page load. It shows a waterfall, an optimization checklist, the Google Page Speed scores (see more details further below), screenshots during loading, first-view and repeat-view load times, etc. Really an extensive list of point so you can start working on your site.

And yes, the load time of my site is 5 seconds for the first view, but that has mainly to do with the Time To First Byte. Thats's the time it takes for the server to create a page, do some database stuff, etc before he sends out the first byte. After that the site loads within 1-2 seconds, as you can see in the repeat view numbers.

Loads.in

Relatively new in the field is Loads.in. This tool makes it easy to test your site quickly from different locations and multiple browsers. It also stores the tests (see mine) on a public URL to see improvements over time. It has a waterfall to see the order of the elements that are loading. Great tool for fast analysis and visual attractive pages you can use to convince clients

Pingdom

A few weeks ago I saw the online tool from Pingdom. It says it measures load times of your website, but this tool doesn't work as a browser. And to have a good indication about scripts that are doing stuff you really need a tool that renders the page so it actually can see what is happening (thanks to Aaron Peters for telling me this).

Page speed

Google launched a tool of their own: Google Page Speed. It's an extension to the well known Firebug Firefox Extension. The advantage of this tool is that it works in your own browser, so you don't have to depend on online tools. What the tool does is giving you an extensive list of points that need some attention:

Each point shows the elements that can be optimized along with a link to a help page that gives you more explanation about the subject.

Yslow

Yahoo also created a tool (YSlow) that can analyse your site performance on a huge list of things. The tool works in Firebug also and is basically the same as Google's Page Speed, although they mention some other points. It can never hurt to create a report with this tool also.

GTmetrix

If you don't have the availability over a Firefox browser than you can use this online GTmetrix tool that will do the Google Page Speed and Yahoo YSlow analysis for you. It returns with both optimization lists and huge grades that can break your day

Next to the grades they provide a waterfall as we saw before.

Google Webmaster Tools

Recently Google put an extra report in the "labs" section of the Google Webmaster Tools called "Site Performance". It shows a graph with the time it takes for users to fully load a page in your site. The line is the average for all users (that have a Google Toolbar) on all pages of your site. Mines looks like this right now:

I launched my new site a few weeks ago, and during the last weeks I improved the performance step by step. I expect the line to go further down in the next days. Almost always the improvements I do to a site are reflected in this graph: so yes, performance tuning works.

They also have other graphs in the "Diagnostics" -> "Crawl stats" screen, but they will tell you how fast Google could download a page. That's good to know, but a fast server doesn't mean a fast site.

Google Analytics

Last but not least: what Google can do with their toolbar, you can do with your Google Analytics account. Add some extra code and track the load time of all your visitors. Great advantage of having them in Google Analytics is that you can segment by browser or country. There are some existing articles that describe the load time tracking with pageviews or customvars, but I still prefer my own solution to track load times with event tracking:

Free extra tip

In the past I improved a lot of sites to get them faster and faster. And almost each time one of the bigger factors in load time was external content. That could mean "Tweet this" or "Like that" buttons, ads, etc. If you want to improve load times of your site: have a look at the external content that you are loading and decide whether it's really necessary to have it or not. And if it's really necessary, try to load that content after your site is loaded. I did the same with the "Tweet this" buttons on my site: if you have a good look at the site when it is loading you will see that the buttons appear after everything else is loaded. Another great tips is to reduce the amount of HTTP requests as Yoast described.

What are you using?

Do you have tools that can add something to the mentioned ones? Which tools do you prefer?

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The first guess for most people would be to create this report with the Google Analytics Custom Report function:

It gives you nice looking numbers about the amount of visits for the specific pages:

But hey, guess what, this is:

It's a long story about Google's data model and their way of data processing, but you're not looking at the number you thought you where. When you create this Custom Report, Google shows you the amount of visits where that specific page was the first page the visitors saw. Also known as the landingpage. Let me show you a new report:

And the outcomes:

Look, it's magic, both columns show (almost) the same numbers which proves my point.

My advice

Do not ever use the metric "visits" for the dimension "page". Google should make it impossible for people to create this report, it will cause anger, disappointment and distrust

How to split visits per page or subfolder?

There are only 2 good ways to do this properly: Create a segment for a group of pages or subfolders. That segment will exactly tell you in how many visits people saw the specified pages. And yes: the content reports will also show other non-specified pages, because people visited those too during the visits on the pages you specified.

The second solution can help you with that: create new profiles that will only track the specified pages or subfolders you included in the profile filters. The huge disadvantage is that it only works from now on. And it's good for tracking a few subfolders, and not every single marketing campaign, because you are limited to 100 profiles max.

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You want to analyze a bunch of data but because of that sign you know it will be sampled (incomplete) data. So, what is "sampling" exactly and how can you prevent it.

What is sampling

After Google Analytics gathered the raw unaggregated data that is being tracked by the tracking script it processes it to understandable and useful visit data. And with that visit data all available standard reports are pre-calculated and stored. That means for example that if you try to get the "Top Content" report, Google Analytics can show it to you in seconds because most of the calculations are already done.

But if you want to get some data that is not pre-calculated, and Google Analytics has to search for it in the stored visit data, you could hit the sampling trigger. As you can imagine, this is a very heavy process that costs a lot of resources. Google has decided that if you are searching for data in more than 500.000 visits or 1.000.000 lines of data it will sample the data to save time. That means that only 500.000 visits or 1.000.000 dimensions are used to create the report you're asking for, and Google Analytics will provide you with a certain range:

That range indicates the lower and upper boundary of where the truth lies with a statistical significance that has a significance level of 5%. That means it's for 95% sure the presented range is correct.

How to prevent sampling

If you really want to use unsampled data in your reports while segmenting: make sure you select a date range that has less than 500.000 visits in it. If you want to analyze a larger date range: export the numbers of the two (ore more) date ranges to Excel and combine them there.

Another solution is to create multiple profiles that track a smaller part of your site. Within those profiles you won't hit the 500.000 limit as soon as the main profile.

The other sampling threshold regarding the 1.000.000 max dimensions is not reached very often. In most cases the top content report is the first one to hit that limit. Google will only retrieve 1.000.000 URL's for a specific period. That means, 1.000.000 divided by the days in your selected date range. For example: 2 months will give you 1.000.000/60 = 16667 unique URL's. So it could be that the URL you where looking for is not in the report. The solution is to select a date range where the amount of unique URL's in less than 1.000.000.

Final word

I know, the solutions are not the ones you really want, and with huge accounts they are useless. But in many cases exporting per proper date range selection is a good solution.

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How does the tracking work

Google Analytics uses pixel tracking technology to send data to the Google servers. That means that the GATC (Google Analytics Tracking Script) will put a little image on the page that is being tracked. The URL of this image looks like this:

http://www.google-analytics.com/__utm.gif?utmwv=4.8.6d &utmn=123456789 &utmhn=andrescholten.net &utme=8(2!echteresolutie)9(2!1600-750)11(2!1) &utmcs=UTF-8 &utmsr=1600x900 &utmsc=32-bit &utmul=nl &utmje=1 &utmfl=10.1%20r103 &utmdt=Andr%C3%A9%20Scholten%20about%20SEO %2C%20Site%20Speed%20and%20Google%20Analytics%20%E2%80%A2%20Andr%C3 %A9%20Scholten &utmhid=0123456789 &utmr=- &utmp=%2F &utmac=UA-XXXXX-1 &utmcc=__utma%3D96932303.227455505.1294957259.1296151377.1296158590.15%3B%2B __utmz%3D96932303.1296082197.13.7.utmcsr%3Dgoogle%7Cutmccn%3D(organic)%7Cutmcmd %3Dorganic%7Cutmctr%3Dandre%20scholten &aip=1 &utmu=qSEAAAAAAAAQ

This utm.gif image will be fetched from the Google server and now Google can see by it's parameters what is being tracked. The same happens with the event tracking and ecommerce scripts. Each event will generate a call to this image, and each ecommerce transaction will call this image once for the transaction and once per individual item.

Now you know this you also know how to see if an implementation works: watch for the utm.gif calls. To do this you need a tool:

Tool 1: Firefox extension Live HTTP Headers

Firefox has a great extension called Live HTTP Headers. Once you installed you can open the tool to get a view at everything that is being send between Firefox and the internet:

And with a little configuration effort the tool is set to only track Google Analytics calls:

The first tab in the tool will show you all calls with the utm.gif in it. The big advantage of this tool above the next mentioned, is that it also shows the details of tracking that is send over secure (HTTPS) connections.

Tool 2: Fiddler2

Fiddler2 is a more robust tool that is capable of tracking all traffic between your PC and the internet. That means it can do checks for Firefox, Opera, Chrome, Internet Explorer, etc. And as we all know: they can all behave different regarding the more challenging implementations. The tool will show you the Google Analytics tracking pixel like this:

Tool 3: Google Analytics Tracking Code Debugger

That last one I want to mention (but certainly not the least) is a tool developed by Google self. It's an extension for Google Chrome that will show a lot of information about what the tracking code is doing on your page. It checks the code for errors and it will break down every single piece of information in readable parts. In my opinion the best tool for the job:

What to analyse?

With the mentioned tools you can see the entire utm.gif request with all the parameters being send. The most important parameters to keep an eye on are:

• utmp: after this parameters is the URL that is being measured
• utmcc: this long parameter contains all cookie info, check if the source (it's after the "utmcsr" part) stays the same until a visitor converts, if not, something is broken and the conversions will be attributed to another source.

A full list of all the other parameters can be found on this page. The parameters for events and ecommerce transaction are somewhat different, but you will be able to analyze them soon enough.

Useful? Have some other tools to mention? Let me know in the comments.

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A visitor lands on the homepage, he than goes to the French subfolder (what is a virtual folder because the entire site is working with AJAX). And than he decides to read some Dutch texts to have a good laugh about the weird language. On both pages he prints out the text he found there, what is being measured with Google Analytics' event tracking system.

Nothing strange now right?

Well, when I created the French profile with a specific "Include request URL" filter on it:

But the Event Tracking report stayed empty? As a Google Analytics technology nerd I wanted to get to the bottom of this.

To which pages are events attached?

The first question I needed to find out is to which pages the events are attached to. If you take a good look at the request that is being send to Google you will see this:

http://www.google-analytics.com/__utm.gif?utmwv=4.8.8&utmn=12345678&utmhn=www.example.com&utmt=event&utme=5(Print*Print-Page)&utmcs=UTF-8&utmsr=1600x900&utmsc=24-bit&utmul=nl&utmje=1&utmfl=10.1%20r102&utmdt=Example&utmhid=0123456789&utmr=-&utmp=%2F&utmac=UA-XXXXXX-1&utmcc=[cut-cookie-values]&utmu=7DMAg

In the UTME parameter are the event values: the category and the action. And as you can see: in the UTMP parameter is the URL that was in the browsers' address bar (%2F stands for /). Not the last virtual pageview URL, not the last real URL, but the actual URL in the address bar.

So the conclusion is: if you want to filter events, you need to filter the pages they were fired from. And if you're working with virtual pageviews you definitely have a problem.

Side-effects

It could be that your site reports 100 URL's in the Top Content report. But there could also be an extra 100 'hidden' URL's that weren't tracked with a trackPageview but did fire a trackEvent. You can find these url's in the Event reports:

Click on the 'Page' item and see which URL's are attached to the events. It could be that these URL's are not in the Top Content report at all. If I created a filter that would only include these URL's it could be that the profile would show 0 pageviews and 100 visits.

Is there a solution?

Well, not really. In most cases a filter on the right folder will work perfectly. Because most events are fired after a trackPageview call that used the URL from the address bar. But if you have a Flash/AJAX site, or some Game/Campaignsite that only uses events on special URL's you need to work out a proper solution.

In my opinion Google should attach events to the last URL that was being send with the trackPageview command. What are your thoughts?

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For people who don't know me, and there are a lot of them I once wrote some blogs on my friend Yoast his site. They were about tracking SEO rankings with Google Analytics. And it was reasonably succesful, I almost got a Semmy for it. Other cool thing is my Search Submit© tool, you must absolutely check it out.

The site still needs some work, some speed tweaks and some translation. The most popular Dutch articles will be translated to new English ones, the rest will stay in Dutch. And I already have some cool new posts queued up, ready to hit the RSS scrapers

So, what do you think? Do you like the new design and the new logo?

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Aan de ene kant is het werken in een team aan een online marketing strategie voor erg grote klanten uitdagend en interessant. Maar aan de andere is het zelf ontplooien en bedenken/uitwerken van nieuwe diensten ook een toffe bezigheid. Vanaf heden ga ik dat combineren door deels voor Traffic4u en deels voor mezelf te werken.

Wat ga je dan doen?

De focus van de dienstverlening zal liggen op:

• SEO
• Site speed (laad je site snel genoeg?)
• Google Analytics
• Trainingen organiseren over bovenstaande onderwerpen

En daarnaast zullen andere interessante gebieden en ontwikkelingen in de gaten gehouden worden. Het bloggen wordt weer geïntensiveerd, ik heb nog een aantal gave onderwerpen op de plank liggen. En er zou ook nog wel eens een website hier en daar live kunnen gaan.

En je site?

Ja ja, ik weet het, Joost schreef er al over, een goed design is belangrijk. En daarom ben ik nu al hard aan een nieuw design inclusief nieuw logo aan het werken. Binnenkort dus een complete overhaul. En last but not least, while I'm in the right language now: the site will be continued in English. My Dutch readers are capable of reading English, but the rest of the world seem to have a problem with the Dutch language. So, a new language and a new domain, soon to be published. But as all marketers know: first get your SEO migration plan right before you launch a new site

Tot slot

Tja, waar begin je dan? Met het aanbieden van hulp.

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Allereerst de benodigdheden (het is net een knutselwerkje):

• Een Google Analytics account vol data

• Een AdWords campagne van een tijdje (maand tot enkele maanden) oud
• Excel (of een soortgelijk pakket)
• Een handige plain tekst editor (Notepad++)
• Voor grote campagnes een snelle pc (rekenkracht in Excel)

Dan de theorie

Deze keywordanalyse gaat eigenlijk om het ombouwen van deze tabel:

Naar deze:

Waarom? Zo kun je in dit voorbeeld heel snel zien dat de zoekopdrachten met het woord "weekendje" erg waardevol zijn. Ook zou je op deze manier heel snel woorden kunnen opsporen die helemaal niet bijdragen aan de omzet: deze kun je vervolgens weer uitsluiten.

Stap 1: De zoekwoorden exporteren

Ga in Google Analytics naar het rapport "Keywords" onder "Traffic Sources" -> "AdWords":

Kies in dat rapport in het pulldown menu "Keyword" voor "Matched Search Query". We willen namelijk de ingetypte woorden hebben en niet de woorden waarop geadverteerd word:

Wanneer de tabel geladen is kun je tabel exporteren. klik bovenin het scherm op "Export" en klik met de rechtermuisknop op de "TSV" link. Kopieer de URL van de link en zet deze in de adresbalk. Type er vervolgens "&limit=10000" achter, dat is de manier om meer dan de standaard aantal rijen te exporteren.

Vervolgens kun je het bestand openen of downloaden. Kies voor de laatste, want het bestand is nog niet klaar voor Excel. Open vervolgens het TSV bestand in de tekst editor en voer 2 zoek-en-vervang acties uit:

• Zoek alle komma's (,) en vervang deze met niets ()

• Zoek alle punten (.) en vervang deze door komma's (,)
• Verwijder de eerste rijen tot aan waar de echte tabel begint

Nu is het bestand klaar om in Excel geopend te worden. Doe dat

Stap 2: de bewerkingen in Excel uitvoeren

Je hebt nu een Excel werkblad met daarin alle data (we noemen dat werkblad "Data"). Als het goed is gegaan is de data ook al mooi gepresenteerd in kolommen. Kopieer kolom A (de zoekwoorden) van werkblad "Data" naar de text editor. Daar doe je de volgende zoek en vervang actie:

• Zoek alle spaties ( ) en vervang deze met een break voor een nieuwe regel (\n):

Nu staan alle individuele woorden op een enkele regel. Kopieer deze woorden naar kolom A van een nieuw werkblad genaamd "Analyse" in Excel. Selecteer in dat werkblad kolom A en kies voor de volgende functie:

Hiermee worden alle dubbele woorden uit de kolom verwijderd en blijft er van elk woord maar 1 vermelding over. Ga terug naar werkblad "Data" en voeg daar 2 extra kolommen toe: "Bouncers" en "Pages". Deze kolommen moeten respectievelijk als formule bevatten: "=bouncerate*visits" en "=pages-visits*visits". Zo hebben we het absolute aantal bouncers en bekeken pagina's. Die zijn weer nodig in het werkblad "Analyse".

In werkblad "Analyse" kunnen we nu de extra kolommen gaan toevoegen. Eerst zoeken we het aantal visits per zoekwoord op. Dat gaat met de volgende formule die we in kolom B plaatsen:

=SOMMEN.ALS(Data!B:B; Data!A:A; Analyse!A2 & " *")+SOMMEN.ALS(Data!B:B; Data!A:A; "* " & Analyse!A2)+SOMMEN.ALS(Data!B:B; Data!A:A; Analyse!A2)+SOMMEN.ALS(Data!B:B; Data!A:A; "* " & Analyse!A2 & " *")

Kort gezegd zoekt deze formule in werkblad "Data" alle vermeldingen op van het zoekwoord uit kolom A van werkblad "Analyse" waar het zoekwoord geen onderdeel is van een langer woord. Dus bij het woord "goed" wordt "goedkoop" niet gematched maar "alles is goed gedaan" wel.

Van de rijen die matchen worden dan de waardes uit kolom B (de visits) opgeteld. Hetzelfde kun je doen om alle bouncers op te tellen:

=SOMMEN.ALS(Data!F:F; Data!A:A; Analyse!A2 & " *")+SOMMEN.ALS(Data!F:F; Data!A:A; "* " & Analyse!A2)+SOMMEN.ALS(Data!F:F; Data!A:A; Analyse!A2)+SOMMEN.ALS(Data!F:F; Data!A:A; "* " & Analyse!A2 & " *")

Zelfde formule, alleen worden nu de waardes uit kolom F (de bouncers) bij elkaar opgeteld. Zo kun je alle velden uit werkblad "Data" opvragen: revenue, time-on-site, enz.

De final touch

Het enige wat rest is in het nieuwe werkblad de kolom "bounce rate" aan te maken door het aantal bouncers door het aantal visits te delen.

Omdat het werkblad "Analyse" wel eens heel zwaar kan zijn bij grote aantallen zoekwoorden kun je voor het analyseren het beste een kopie maken. Je maakt een nieuw werkblad aan en kopieert werkblad "Analyse" daar naar toe. Bij het plakken kies je dan voor "Waarden plakken":

Zo ontstaat er een nieuw werkblad dat geen formules meer maar alleen waardes bevat. Hier kun je vervolgens je echte analyses op los laten. Welke woorden genereren veel omzet, welke niet. Waar zitten de bouncers, enz.

Een voorbeeld sheet

Ik kan me voorstellen dat het allemaal niet even duidelijk is. Ik heb daarom een voorbeeld sheet gemaakt met daarin de besproken tabbladen:

• Voorbeeld van keyword analyse in Excel

In de praktijk kom ik zo veel bijvoeglijke naamwoorden tegen die het erg goed doen. En zonder deze analyse was ik daar niet snel achter gekomen. Ook levert het vaak veel woorden op die uitgesloten moeten worden. Google's Extended Super Wide Huge Broad Matching algoritme wil nog wel eens voor rare zoekwoord matches zorgen.

In plaats van Excel en Notepad++ zijn er ook andere tools, maar die zullen wellicht niet alle opties aan boord hebben om de analyse op de beschreven manier te doen. Je zult dan creatief moeten zijn in het zoeken naar een andere oplossing.

Vragen? Leuk? handig? Hieronder

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Sitespeed testen

Dan een tool die door 1 van mijn commenters genoemd werd: GTmetrix. Deze tool laat je eenvoudig een site controleren door Google Page Speed en Yahoo !Slow. Daarnaast wordt een waterval getoond, dat is een visuele weergave van het inladen van alle onderdelen van de geteste site. Zo zie je eenvoudig waar de bottlenecks zitten. Het leuke is ook dat ze de scores van je site onthouden, en zo kun je goed bijhouden wat je inspanningen om je site te versnellen opleveren. Uiteraard mag naast deze tool niet de site van WebPagetest ontbreken, ook een erg goede tool.

Eenvoudig A/B of multivariate testen

Ben je flauw van de Google Website Optimizer omdat je voor elke test een bak scripts moet plaatsen terwijl je dan ook de kans loopt om je Google Analytics meting om zeep te helpen? Dan is het tijd om over te stappen naar de Visual Website Optimizer:

• 1 script plaatsen op alle pagina's en je hoeft nooit weer scripts te plaatsen.

• Met een paar kliks selecteer je testgebieden: titels, teksten, enz.
• Daarna on-the-fly een paar doelen instellen en je bent klaar om te testen.
• Tijdens de test meer doelen toevoegen of varianten uitschakelen.
• Direct gekoppeld met Google Analytics zodat je de resultaten per variant ook daar bij kunt houden.

Bekijk deze pagina + video voor een snelle indruk.

Simpel en zonder moeite een backup maken

Zet een bestand in een speciale folder, en dat bestand is direct gebackupped en gesynchroniseerd online en op alle andere pc's waar je Dropbox geïnstalleerd hebt. Zo kun je recente foto's en belangrijke documenten eenvoudig op diverse geografische lokaties backuppen. En met een speciale link kun je bestanden eenvoudig delen met anderen. Lui en toch recente backups willen hebben? Dropbox.

Referral linkjes?
Ja, als ik mensen bij Dropbox aanbreng krijg ik 500mb gratis ruimte er bij

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