There is a predefined dimension in Google Analytics called ‘Hour‘.

This dimension reports hour of the day in the form of two digits ranging from 00 -23.

Here 00 means 12 am, 01 means 1 am, 02 means 2 am…… and 23 means 11 pm.

You can often see this dimension in action in the ‘Adwords hour of the day‘ report:

Through this dimension you can determine when people visited your website, when they interacted with your website and when they converted.

So if you know the hours of the day when people are more likely to convert, you can bid more aggressively during those hours in case of PPC.

For any time sensitive marketing campaign (like newsletter campaigns, TV & Radio campaigns), the ‘hour’ dimension provides valuable insight.

However the problem with ‘hour’ dimension is that it reports the hours in the time zone configured for your Google Analytics account and does not report the hours in the local time zone of your website users:

What that means is that if a user convert on your website at 12 PST (Pacific Standard Time) and the time zone configured for your GA account is BST (British Summer Time) than GA will report that the user converted at 20 BST (or 8 pm BST).

This is because 12 PST = 20 BST as there is 8 hours time difference between PST and BST time zones:

So if you are getting traffic and conversions from multiple time zones (quite common if your market is international or you operate from a country which has got multiple time zones like US, Canada, Russia, China, Australia etc) then you can’t rely on the ‘hour’ dimension for analysis and reporting.

In this article, you will learn to measure and report on the:

#1 Actual hour of the day (which is based on a user’s local time)

#2 User’s local time zone (which Google Analytics does not report by default).

#3 Time of the day like morning, evening, etc which is based on a user’s local time & which GA does not report by default

#4 Current Date and time (including time zone) from users’ system settings

In order to produce this report, we would create a couple of custom dimensions and use the custom data import feature.

Setting up Custom Dimensions

There are 5 stages of creating and using custom dimensions in GA. They are:

#1 Planning – at this stage, you decide the type of data you are going to collect and how you are going to collect the data (i.e. functionality) via custom dimensions.

#2 Configuration – at this stage, custom dimensions are defined via Google Analytics property settings

#3 Collection – at this stage, the values of custom dimensions are sent to Google Analytics from your implementation.

#4 Processing –  at this stage the value of custom dimensions are processed according to their configuration values (like scope) and reporting view filters.

#5 Reporting – at this stage the values of custom dimensions become available in the GA reports.

Planning

In order to get ‘Actual hour of the day’, ‘User’s local time zone’, ‘Time of the day’ and ‘Current Date and time’ data, I need to create following 4 custom dimensions with session level scope:

#1 Visit Date and Time – This custom dimension will retrieve current date, time and time zone from date and time settings of a user’s computer .

#2 Visit Hour – This custom dimension retrieves only the hour of the day from date and time settings of a user’s computer.

#3 Time Zone – This custom dimension retrieves only time zone from date and time settings of a user’s computer.

#4 Time of the day – This custom dimension retrieves ‘Time of the day’ which is based on a user’s local time. The ‘Time of the day’ dimension can have following values:

1. Morning (5.01 am to 12 pm)
2. Afternoon (12.01 pm to 5 pm)
3. Evening (5.01 pm to 8 pm)
4. Night (8.01 pm to 5 am)

Since time of the day data can not be retrieved from date and time settings of a user’s computer, we will have to import this data into GA via Custom data import and then join this data with actual hour of the day:

In this way GA will be able to compute and report on the ‘time of the day’ dimension.

Configuration

Create following 4 custom dimensions in Google Analytics:

Make sure that you set the dimension scope to ‘Session’ because we are doing all the date and time calculations at the session level.

If you are very new to creating custom dimensions in GA then read this article: https://support.google.com/analytics/answer/2709829?hl=en#set_up_custom_dimensions 

Collection

#1 ‘Visit Date and Time’ Custom Dimension

The example code for this dimension would be:

Modify this example code like the one below:

var dimensionValue =new Date();
ga(‘set’, ‘dimension1’, dimensionValue);

Here Date() is a JavaScript object which is used to retrieve current date and time (including time zone) from user’s system settings. We create this object by using the ‘new’ operator. For example:

new Date();

 

#2 ‘Visit Hour’ Custom Dimension

The example code for this dimension would be:

var dimensionValue = ‘SOME_DIMENSION_VALUE’;
ga(‘set’, ‘dimension2’, dimensionValue);

Modify this example code like the one below:

var dimensionValue2 = new Date().getHours();
ga(‘set’, ‘dimension2’, dimensionValue2);

Here Date().getHours() retrieves the hour of the day (0 – 23) part from the current date and time settings of a user’s computer.

 

#3 ‘Time Zone’ Custom Dimension

The example code for this dimension would be:

var dimensionValue = ‘SOME_DIMENSION_VALUE’;
ga(‘set’, ‘dimension3’, dimensionValue);

Modify this example code like the one below:

function getTimeZone() {
return /\((.*)\)/.exec(new Date().toString())[1];
}

var dimensionValue3 = getTimeZone();
ga(‘set’, ‘dimension3’, dimensionValue3);

Here the function ‘getTimeZone() retrieves the time zone part of the current date and time settings of a user’s computer.

 

#4 ‘Time of the Day’ Custom Dimension

The example code for this dimension would be:

var dimensionValue = ‘SOME_DIMENSION_VALUE’;
ga(‘set’, ‘dimension4’, dimensionValue);

But we won’t modify this example code to collect ‘time of the day’ data.

Instead we will import this data directly into GA via custom data import so that it is available to GA during processing stage.

Follow the steps below in order to compute and report the values of ‘time of the day’ dimension in GA:

Step-1: Go the ‘Admin’ section of your view and then click on ‘Data Import’ link under ‘Property’ section:

Step-2: Click on ‘+ New Data Set’ button and then select ‘Custom Data’ as data set type:

Step-3: Click on the ‘Next Step’ button, Enter the name of the new data set and then select the views that will make use of the data in the data set.

Step-4: Click on the ‘Next Step’ button and define your data set schema like the one below:

Step-5: Set ‘Overwrite Hit data’ setting to ‘Yes’ and then click on the ‘Get Schema’ button:

Step-6: Click on the ‘Download schema template’ button and then click on the ‘done’ button twice. The schema template is in the form of a CSV file. Open this file and then add all of the custom data to this file:

 

Here,

ga:dimension2 => Hour of the day

ga:dimension4 => Time of the day

Step-7: Upload the CSV file you created to Google Analytics by clicking on the ‘manage uploads’ link and then on the ‘Upload file’ button as shown below:

This action will import custom data to your GA property.

Combine the implementation code for the three custom dimensions (‘visit date and time’, ‘visit hour’ and ‘Time Zone’) like the one below:

var dimensionValue =new Date();
ga(‘set’, ‘dimension1’, dimensionValue);

var dimensionValue2 = new Date().getHours();
ga(‘set’, ‘dimension2’, dimensionValue2);

function getTimeZone() {
return /\((.*)\)/.exec(new Date().toString())[1];
}
var dimensionValue3 = getTimeZone();
ga(‘set’, ‘dimension3’, dimensionValue3);

Add these lines of code to your Google Analytics tracking code, immediately above the ‘ga(‘send’, ‘pageview’);’

So your final Google Analytics tracking code will look like the one below:

Processing

At this stage, GA will process the value of custom dimensions according to their configuration values, view filters and the imported custom data. You don’t need to do anything at this stage.

Reporting

At this stage the values of custom dimensions become available in the GA reports.

However to see these values, you would need to create custom reports and select these custom dimensions like the one below:

Another article you will find useful: How to correctly install enhanced ecommerce via Product Data Import

Other articles on specialized tracking in Google Analytics

1. Ecommerce Tracking in Google Analytics – Tutorial
2. Event Tracking via Google Tag Manager – Tutorial
3. Event Tracking in Google Analytics – Tutorial
4. Guide to Google Analytics Store Visits Tracking
5. Offline Conversion Tracking in Google Analytics – Tutorial
6. Implementing E-Commerce Tracking via Google Tag Manager
7. Tracking Virtual Pageviews in Google Tag Manager – Tutorial
8. YouTube Video tracking via Google Tag Manager
9. How to Use Keyword Hero to Reveal Not Provided Keywords in Google Analytics
10. Virtual pageviews in Google Analytics – Tutorial
11. Google Analytics and YouTube Integration Tutorial
12. Google Analytics for Facebook Tutorial
13. Google Analytics Cross Domain Tracking Explained Like Never Before
14. Using multiple Google Analytics tracking codes on web pages
15. The one thing that you don’t know about PayPal.com and the referral exclusion list
16. Calculated Metrics in Google Analytics – Tutorial
17. Creating your own Google Analytics Tag Auditing System
18. Tracking Site Search without Query Parameter in Google Tag Manager
19. Tracking true referrals in Google Analytics when using PayPal and other payment gateways
20. Phone Call Tracking in Google Analytics and Beyond
21. Learn to Track Qualified and Won Leads in Google Analytics
22. Introduction to Postbacks in Google Analytics
23. Google Analytics Recurring Revenue and Subscriptions Tracking Tutorial
24. How to track the impact of cookie consent on website traffic in Google Analytics
25. Tracking Offline Conversions in Google Ads
26. Implementing Scroll Tracking via Google Tag Manager
27. Scroll Tracking via Scroll Depth Trigger in Google Tag Manager
28. Site Search Tracking In Google Analytics Without Query Parameters
29. Video Tracking via YouTube Video Trigger In Google Tag Manager
30. How to Correctly Measure Conversion Date & Time in Google Analytics
31. Google Analytics Social Tracking – Twitter, Facebook, Google Plus and LinkedIn
32. Google Analytics Cross Domain Tracking (ga.js)
33. Tracking Twitter and Linkedin Social Interactions in Google Analytics
34. Creating Content Group in Google Analytics via tracking code using gtag.js
35. Tracking Site Search in Google Analytics with Query Parameters
36. Understanding site search tracking in Google Analytics
37. Creating and Using Site Search Funnel in Google Analytics
38. Learn to Setup Facebook Pixel Tracking via Google Tag Manager
39. Setting up & Tracking AMP Pages in Google Analytics
40. Setting up Sales Funnel across websites in Google Analytics
41. Regular Expressions (Regex) for Google Analytics & Google Tag Manager – Tutorial