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Welcome to Josh Baker's Practical Advice for Optimizing Your Internet Marketing blog. Here you will find internet marketing optimization and online strategy articles full of tips, tricks, discussions, and thoughts to help you take your marketing and business to the next level of success.

bounce_rate_new_vs_returning_visitors

Bounce Rate by definition for a web page is the total number of visitors who enter your website through a particular page and then leave your site without viewing another page divided by the total number who visit that same page. Simplified, bounce rate is the percentage of people who enter your web site, visit only that single web page they entered on, and then leave – without viewing another page. The bounce rate of your high traffic or important web page’s is a highly actionable metric to know.

Although most web analytics tools make it simple to extract your websites or an individual web page’s bounce rate, looking at the bounce rate when presented in aggregate is definitely not as insightful or actionable as it could be and potentially lead to misinterpretation.

Let me explain – your bounce rate by default, without segmenting the data, is typically presenting a bounce rates determined from multiple visitor segments – both the good and the bad. Most likely then, you are then making possible inferences on that bounce rate to that page that could potentially affect all visitor segments – not just the ones that are bouncing.
…continue reading Segmenting Visitors for a Deeper Bounce Rate Insight

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Categories : Analytics
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Let’s Take a Simple Multiple Choice Test:

Question: Who is your site actually built for?blue_keyboard

Hint: It’s the same group of people that should be designing your website.

Choose your Answer:
A) Your Company (web design team, marketers, IT, etc)

B) The end user (i.e. your actual or potential customers)

If you chose B, you are correct! If you chose A, then you probably work for a company whose website isn’t effective as it could be and still wondering why.

If your company is like most companies, implemented ideas and then changes to your websites layout, design, navigation and other features are usually made based on internal decisions by HiPPOS (Highest Paid Persons Opinion). Decisions based on irrational factors such as your competitors site looks a certain way so “we should do it too”, Amazon does it, my ego wants it, and even “it looks prettier”.

A high-performing website is designed by your user’s interactions based around common website usability best practices and grown from there.

  • If your users can’t easily get to (or find) what they want, they can’t buy what you have.
  • If your web page, product presentation, whitepaper, etc., doesn’t provide the right value to them in their minds, they won’t be willing to exchange money, information-email address, phone number, and so on for it.

Luckily, your users are telling you how they want your site to work, look, or communicate every day in your analytics data. They tell you how they feel about the perceived value of your whitepapers when they fill out their personal information for it, or when they don’t. When you run a multivariate test, they are also telling you how they want your page to work (i.e. we convert more when your page looks like this!)

Your end user is telling you how to design your site, listen to them – they are the ones who you’re trying to convert to a lead or generate a sale from, not your co-workers. Now, why would you listen to anyone else?

photo by Darren Hester

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Categories : Optimization
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If you have one Google Analytics profile tracking multiple subdomains (or you want to do so); for example, one profile tracking:

http://www.MyCoolWebsite.com

http://blog.MyCoolWebsite.com

http://youlove.MyCoolWebsite.com

when you view your Google Analytics data in the profile that is tracking all 3 subdomains it won’t by default separate out the data for each actual subdomain. You’ll need to add some additional code to your tracking script and also set up an Advanced Filter.

If each of your subdomains has pages that are named the same, you will see the data reported as aggregate for all them under that page name, therefore the data for those page names will be inflated and not actionable. For example:

http://www.MyCoolWebsite.com/contact.html

http://blog.MyCoolWebsite.com/contact.html

http://youlove.MyCoolWebsite.com/contact.html

will all be rolled up under /contact.html and you will not know what the true data is for the contact.html page on each subdomain. Instead, you will have one entry of /contact.html displaying the data for all traffic to contact.html on all 3 of the subdomains. Not good!

What you will want to do is see it by subdomain so you can attribute the correct data to the correct subdomain.

Luckily, this is easily fixed!

If you already have your pages tagged with the Google Analytics tracking script, just add the line in bold to your existing Google Analytics code (replace MyCoolWebsite.com with the actual domain, not the entire subdomain and of course make sure all of the sites have the same profile tracking number (seen below as UA-xxxxxx-x, the x’s will be replaced by your own account number and profile number).

 If you haven’t added the Google Analytics tracking script to your pages add the entire code below – again with your own specific Google Analytics account number and the profile number, and your actual domain:

<script type=”text/javascript”>
var gaJsHost = ((“https:” == document.location.protocol) ? “https://ssl.” : “http://www.”);
document.write(unescape(“%3Cscript src=’” + gaJsHost + “google-analytics.com/ga.js’ type=’text/javascript’%3E%3C/script%3E”));
</script>

<script type=”text/javascript”>
var pageTracker = _gat._getTracker(“UA-xxxxxx-x”);
pageTracker._setDomainName(“MyCoolWebsite.com”);
pageTracker._initData();
pageTracker._trackPageview();
</script>

Next, you will need to set up an Advanced Filter, this will actually separate out the subdomains so that they will be reported separately under that profile:

The finished result is that instead of just 1 instance of /contact.html, you will see it reported in your reports with each subdomain added to /contact.html as follows:

www.MyCoolWebsite.com/contact.html
blog.MyCoolWebsite.com/contact.html
youlove.MyCoolWebsite.com/contact.html

Here is how to set up the Advanced Filter for Tracking and Separating out Subdomains:

  1. First log-in to Google Analytics.
  2. Select edit from the profile you created that will track all of the subdomains.
  3. Select edit in the Filters Applied to Profile section.
  4. Fill in the below information and Save.

First, here is the actual information for you to copy and paste, then below that is a screenshot of how it should look before you save and apply it to that profile.

Filter Type: Custom filter > Advanced
Field A: Hostname
Extract A: (.*)
Field B: Request URI
Extract B: (.*)
Output To: Request URI
Constructor: /$A1$B1

 

google analytics advanced filter for tracking and separating subdomains

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Categories : Analytics
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wishlist
I have just a few ideas that I would like to see Google Website Optimizer (GWO) provide to its users (or at least some that I wish for).  I am big on documentation so it would be great to see some internal documentation and reporting features in the admin along with some more testing ability. By no means is this a complete list, and I should say that I am very happy with GWO – but these ideas popped into my head and thought I would share them for your comments or suggestions as well:

  • Date selection for each test – be able to select a time range for a test in order to look at the results by a user selected time period. This is more for curiosities sake on my part.

 

  •  Ability to add notes to tests – it would useful to be able to make notes about tests within the test admin itself for each test. Many times we have multiple people looking at a test and I would like to leave comments and get responses within the test, not only for ease but for permanent documentation. 
 
  • Allow the testing of more sections and areas – currently you can only test 8 sections and 127 variations. At least let me have 12 sections please!

 

  • Set up auto-emailing of daily reports - how nice it would be to get a daily or twice-daily email report of the current results that I could set up.

 

I haven’t thought this one through completely yet, not sure it’s recommendable – but the idea intrigues me:

  • Turn off test during certain time periods and auto turn back on – Here me out on this one first. Let’s say you are a lead generation model, you already turn your PPC campaigns off on weekends, etc. – all due to the fact that you have determined that weekend leads are ineffective, of poor quality and not-cost effective for you to follow-up with. Maybe you are a B2B and the weekend leads mainly consist of consumers. What if you could optimize for your weekday visitors only by having it shut off on Friday nights and turn back on Monday morning?

 

photo by Incessant Flux

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Categories : Online Testing
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Three of my conversion optimization colleagues and I had a discussion online the other day that I had proposed about the common “sins” of online conversion testing we see or hear about often in organizations.  We came up with about 20 commons “sins” in about 7 minutes that we all agreed upon, and about 40 overall. Below you will find 8 of them in no particular order (with more to come in the future).

8 Common Sins of Online Conversion Testing that Organizations Let Happen:

  1. When running a multivariate test, after the test ends, not performing a head-to-head testing of the winning page combination and the control. The winning page combination is typically based on a prediction; a head-to-head test will further uncover the true results.
  2.  

  3. Having too many people involved in the testing process AFTER the test is given the “go ahead”. Everyone involved should have a purpose otherwise the process slows down.
  4.  

  5. Not believing that having no panels perform better than the control is still a win – just of a different kind; but only if you actually extract the knowledge hidden in your “loss”.
  6.  

  7. Not setting a concrete conversion goal – know what your test hypothesis is and understand how you will analyze the data ahead of time. Alternate lessons may be and should be learned from a test but it’s vital to know exactly what and why you are testing something in the first place.
  8.  

  9. Not allowing a test to run long-enough to accumulate enough conversions.
  10.  

  11. Not running the control panel (this happens often) at the same exact time as the test panels.
  12.  

  13. Letting personal opinions or biases override data in the results – the reason you test is because you really don’t know what will persuade your actual visitors best.
  14.  

  15. No Patience - ending tests too early, or not allowing the process to happen as it should.

 

As bad as these are, we all agreed we were still happy that organizations have the desire to test!

Have an online conversion testing or optimization sin that you want to share or get off your chest? Let me know in the comments section.

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