SQL for Marketing Analysis – All Google Analytics Analysts Should Know

Marketers and Marketing Analysts generally depend on the tools or IT department to help them pull the data for marketing purposes. There comes a time when they can’t just wait around for IT to help them data pulls and manipulations.  They have to know how to do it on their own. This course is for those marketers who would like to know how to use SQL to conduct their marketing analysis.

The course uses MYSQL to show how SQL works but all the leanings and syntax are applicable to other databases as well.  Sign up for SQL for Marketers and Marketing Analysts

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5 Online Google Analytics Courses You Might Like

Few Online Courses to Learn Google Analytics

I came across few online courses on Google Analytics that might help you as you are learning or improving your Google Analytics skills.  I have not personally not gone trhough these courses so can’t vouch for how good they are but I have used the reviews of others, who have taken these courses, to rank them.

If you have an online course that you teach or love, then send me the link to include it in this list.

    1. Google Analytics for Beginners – Learn to use Google Analytics for uncovering actionable data and growing your business online.
    2. The Complete Google Analytics Course For Beginners - Learn Google analytics and its strategies to increase the traffic and sales of your business
    3. Google Analytics Mastery – Sky rocket marketing results through the power of data analysis and Google Analytics!
    4. Google Analytics 2015: Turn Data Into Strategic Decisions – Google Analytics: Grow your business by setting goals, tracking marketing analytics & performing business analysis
    5. Google Analytics Fundamentals – Learn the fundamentals of Google Analytics including core concepts, the interface, using reports and customization.687474703a2f2f7777772e6461696d746f2e636f6d2f77702d636f6e74656e742f75706c6f6164732f323031332f31312f676f6f676c652d616e616c79746963732e706e67

 

6 Reasons Why Your Google Analytics Reports Might Be Wrong

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  1. Missing Tags – This is the most common error of wrong data.  This generally happens when new pages are added or the exiting pages are redesigned/recoded and the developer forgets to include the tags.  Make sure all of your pages are tagged with Google Analytics code.  You can use a tool like GAChecker, to verify if the Google Analytics tags are missing on any pages of your site.
  2. Mistagged Pages – Incorrect implementation or double tagging leads to wrong data in Google Analytics.  Double tagging results in increased page views and a low bounce rate. If you bounce rate is lower than 20% then that’s the first thing you should check.
  3. Location of GA Tags – Placing the tag towards the bottom of the page could result in no data particularly for the users with slow connections or pages that are slow to load.  This happens when a user tries to loads a page and clicks on another link before the first page is loaded. Since the Google Analytics tag is towards the bottom of the page, it might not get a chance to execute.  To avoid this issue, put your Google Analytics JavaScript in the <head> section of the page.
  4. Incorrect Filters – Wrong Filters can mess up the data and distort the view.  Always create an unfiltered view so that you have correct data to fall back on.
  5. Tags Not Firing Properly – This can happen when your page(s) have JavaScript errors.  A JavaScript error on any part of the page can result in an error in Google Analytics code. Verify the JavaScripts on your site to make sure there are no errors.
  6. Sampling – Sampling happens on highly trafficked site. Sampling in Google Analytics is the practice of selecting a subset of data from your traffic and reporting on the trends available in that sample set.  For most purposes, this might not be a non-issue however it can be of concern in eCommerce sites where sampling can (will) result in wrong sales figures.   You can get more information about GA sampling on “How Sampling Works“.

How to Filter out Bots and Spiders from Google Analytics

A common misconception is that Google Analytics or any other JavaScript based Web Analytics solution filters out Spiders and Bots automatically.  This was true till few years ago because most of the spiders and bots were not capable of executing JavaScript and hence were never captured by JavaScript based Web Analytics solutions. As shown in 4 reasons why your bounce rate might be wrong, these days bots and spiders can execute JavaScript and hence are showing up in your Web Analytics reports.

Google Analytics has released a new feature that will let you filter out known spiders and bots.  Here are few things to keep in mind

  1. The data will only filter spiders and bots from the day you enable this setting. It won’t be allied to the data already processed.
  2. Since this will filter out bots, you might notice a drop in your visits, page views etc.

 

Here are the steps to filter out Spiders and Bots

  1. Go to the Admin section of your Google Analytics report
  2. Click  “View” section and choose the right report view
  3. Click  on “ View Settings” (see image 1 below)
  4. Check the box under “Bot Filtering” which says “Exclude all hits from known bots and spiders” (see image 2 below)
  5. Click “Save” button at bottom and you are done.

 

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5 Reasons Why You Should Use Google Experiments

Google Experiments is an A/B testing tool that is available within Google Analytics interface.  This post is not about what A/B testing is, why you should conduct A/B tests and what other tools are available but really to make a case for using Google Analytics as your testing platform.  I am not getting paid to write this or have any affiliation with Google. This post is in response to a question I received from a reader of my blog.

  1. Free –There is absolutely no cost for the Tool. You can’t beat Free, it is a great way to start with A/B testing and learn about how testing works. I strongly recommend that you try this tool before moving to more sophisticated paid tools. Additionally, if you are just trying to make a case for Testing within your organization then cost does become a barrier and this tools removes that barrier.
  2. Easy To Setup – Easy to use wizard allows you to choose the pages to test and setup test parameters.
  3. Easy Implementation – Once you are done with setting up (point 2 above) the page(s) you want to test, you have to implement some code on your site.  It may sound daunting but that code is very easy to implement. Google provide you the code after your setup is done and all you have to do is stick that on your pages.  Since you already have Google Analytics installed, you are already half way through. Easy setup makes it easy for you to cross the IT/development team barrier.
  4. Setting up Objective– If you have already defined the Goals in Google Analytics, you can use them as the objective of your test. During your setup you can pick a goal that you have already defined in Google Analytics as your desired optimization objective. If you have not defined them already then you can quickly define them while setting up your test.
  5. Segments – Many tools just gives you the final results based on the data of entire population or based on some predefined segments.  In case of Google Experiments, you can pick Segments that you have defined in Google Analytics and see how each variation is performing for each of your segment. Since not all segments behave in similar fashion this kind of analysis helps you drive even more conversion by understanding which variation of your pages(s) work better for which segments.

Keep in mind that no matter how good your conversions are, there is always a room for improvement and A/B testing helps you with it. As Bryan Eisenberg would say, Always Be Testing.

This post was originally posted on http://anilbatra.com/analytics/2013/11/5-reasons-to-use-google-experiments/

How to View Click Map of a Page in Google Analytics

Click maps are a great way to visually see where visitors are clicking on a page. Google Analytics provides click map under Content –> In-Page Analytics (See below).

Click on In-Page Analytics and the first page that you will see is your site’s home page. To view a different page, either click on a link on the home page (still within In Page Analytics) or select a page from drop down available on top left (see below).

Other options

  • Select click, goal value or a goal to display on click map and also a threshold from the drop down next to it.
  • Show Bubbles – this shows the orange bubbles and the numbers that you see in the report. This is the default view, when you first land on the page.
  • Show Colors – this options add another visual to the way you view click map, it is sort of heat map of clicks.
  •  Browser Size – This options show what percent of your visitors who see the area displayed in your report. By choosing this option you get a slider that allows you to slide and choose percent of visitors. As you choose the visitor percent, the page resizes to show the area of the page, those percent of visitors see.

How to View the Visitor Flow of Specific Pages in Google Analytics

Open Visitor Flow Report Under “Audience” menu open in “Standard Reports”. See below.  This view will give you the visitor flow for the complete site.

Left click on the page that you want the visitor flow for and select “Explore traffic through here” from the menu.

Now you have the visitor flow for that page (see below)

How to Create a Filter to Tidy up Email Referrals

Roll up Yahoo Mail, Hotmail referrals

If you send marketing emails without campaign tagging or an external company e-mail your sites links to its users that have Yahoo Mail or Hotmail, users will arrive at your site via one of the many Yahoo or Hotmail servers. So searching for mail.live.com in your referral report gives you hundreds of referrers which are actually one and the same referral link.

 

 

You tend to get referrals like above ( ”xy342w.mail.live.com”). You can roll these together so you can see hotmail referrals grouped together by making changes inside Google Analytics so that reports are clearer and easier to breakdown.

 

Login to Google Analytics; select your profile you wish to roll up this data. Select Admin > Profiles > Filters

 

 

The next step is to create a New Filter.

These Filter you need to create will be a custom filter that will look at campaign sources and replace/rename the string with something that rolls them up into an easy to view source.

Filter type: Custom Filter > Search and Replace

The filter field that will be searched will be the Campaign Source and in order to ensure that all possible variables of the email source are collected a regular expression will be needed.

Filter Field > Campaign Source

Search String > “A Regular Expression”

sn144w.snt113.mail.live.com will need the following regular expression

^.*mail\.live\.co.$

Replace String with the name you wish to roll it to. I have chosen livemail.

Select Save.

Example below.

Windows Hotmail/Livemail:

 

 

This is a guest post contributed by James Cornwall

About James Cornwall

As Digital Analyst at 4Ps Marketing, James is responsible for the recently launched analytics department. After studying Civil Engineering at CITY University, James has undertaken a career in ecommerce and digital marketing. He is Google Adwords and Analytics Certified, and in his spare time is a keen hockey player. Ask James a Question: Follow on Twitter – @jamesc_4ps LinkedIn – http://uk.linkedin.com/in/james-cornwall/

Why is the Operating System Report not showing iPhone and iPad visits?

If you recently looked at Operating System Report under Browser & OS Report in or Mobile Devices Report in Google Analytics then you must be wondering what happened to your traffic from iPhone and iPad? Why are you not seeing any more traffic from these devices?

Starting May 30th Google Analytics has consolidated both iPhone and iPad into iOS in the Operating System Report. (See the graph below). iOS is the operating system used by both iPhone and iPad and hence the change to correctly reflect the operating system.
So next time you run your report keep this change in mind.

Google Website Optimizer Moves to Google Analytics – Experiments under Content Section

Google Analytics and Google Website Optimizer have merged. Now Google Website Optimizer, a free A/B and Multi-variate testing tool, is available in Google Analytics via Experiments link under Content Section (see image below).

You can create and manage all your tests within Google Analytics without going to Google Website Optimizer site.

Functionality Difference between Experiments and Google Website Optimizer

  1. Easy Implementation – Since you already have Google Analytics on your site, now you will need one script to put on the original version, rest of the work will be done by standard Google analytics script.
  2. No Multivariate Testing Anymore – There is no option to run MVT and only allows A/B testing in the “Experiments”

 

The last day you’ll be able to access Google Website Optimizer will be August 1st, 2012

We will add more posts as we uncover new functionality in Experiments.