Cross Domain Tracking in Google Analytics

GATC trackers only work on main and sub-domains you other domains must be added manually.

For example:  You have a School.ca website,  with a class registration on WebAdvisor-school.ca

Marketing campaigns will bring users to landing pages but the actual registration happens on Webadvisor website.

To understand a users journey, you need to share sessions across all domains or user from landing pages will be recorded as referral.

 

Here is a good sample of how to set this up in Google tag manger

 

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Conversion Tracking in Google Analytics with Goal and Funnels

Conversion tracking or Outcome analysis is a technique to quantify website’s target objectives and fulfilment

there are two types of conversion on a website:

  • macro conversion: wen visitors makes actual purchase
  • micro conversion: steps that get users closer to macro conversions

In Ga, Macro conversion are being measured with Ecommerce Tracking and Micro conversions with Goals

Using Goals, you will be able to measure number of conversion, and conversion rates on your website

You can also identify performance of your marketing efforts by correlating the goals to your marketing campaigns.

Key Concepts of Conversion Tracking

  1. Goals are a view level configuration in Google analytics
  2. to create a goal, normally no coding is required
  3. you can create up to 20 goals per view
  4. goals are grouped in 4 sets, each set contains 5 goals: its is just a grouping and has no impact whatsoever on Goals settings, configurations or data recording.

There are 4our major Goal types:

  1. Destination- a specific location  loads- thank you page ( you can define the path you expect the visitors to go through to a specific conversion.
  2. Duration- Visits that lasts a specific amount of time or long- long session period
  3. Pages/Screens epr visit- A visitor views a specific number of pages or screens- user interacted with your site a lot
  4. Event- an action defined as an event is trigger – users clicked on newsletter signup for example.

To setup goals,  Identify your conversion achievements on your website based on your KPI’s.

Goals can be viewed in your conversion reporgts

 

 

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Content Experiment in Google Analytics

A/B testing is a type of testing where two versions of a web page ( version A and version B), are compared against each other to determine which on performs the best.

Performance is normally measured within context of conversion, like generating highest conversion rate.

To Run the test, traffic will be split randomly and evenly between the variations of the page.

A multivariate test also compares multiple versions of a page at once, by testing all possible combinations of variations at the same time, included components on a page.

A/B testing is important because:

  • You can test ideas, It helps you determine which layout design has a chance to give you better performance when there is competition
  • you can determine your customers decision making process
  • You can test ideas improve conversions.

Popular testing tools:

  • Google Analytics content Experiment
  • google optimize
  • Optimizely
  • SiteSpects
  • adobe test and target
  • visual website optimizer
  • Crazy egg

 

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Web Data Types

Every online market should develop a passion for qualitative and quantitative analytics,  this is how the sausage gets made!  No matter what size your business is if you’re not basing your decisions on clean data you should buy a magic 8 ball and hope for the best.

 

Tell me more

While quantitative data describes what happens on your website, qualitative describes why it happens.

Quantitative Data – Looking at the actual numbers.  These numbers are usually based off metrics like clicks, page loads and reported after the fact. The most accurate data on your users.  This also included metrics like conversion funnels, traffic channels

Qualitative Data – subjective guessing on why people are doing certain things on your site.  Why did they abandon their cart?  You can gather this info by user interviews, focus groups, card sorting, eye-tracking, usability testing

Why would you use Qualitative data?  Maybe there business cases unknown that might help your advertising campaigns in the future.

Tools like Google Analytics, Omniture, WebTrends, and Yahoo! Web Analytics generate quantitative, or clickstream, data. … Qualitative data comes from different sources, like user interviews and usability tests. But the easiest way to get qualitative data is through surveys.

Some useful tools (other then google analytics) to figure out the why what and how:

Qualaroo,

Kissmetrics

Typeform

Crazy Egg

YesInsights

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