I do believe that bounce rate is a great starting metrics when you are trying to optimize your site but be careful and make sure that you are measuring the true bounce rate. Below are the three factors that lead to the misreporting of the bounce rates
Links to external sites – Many sites have links to the external sites such as sponsors, micro sites etc. Considering those external links as exits will count visits as bounces even though the visitors are doing exactly what you want them to do (e.g. click on those links that you provided them). See below a screen shot from First Tech Credit Union, there are few external link s contributing to the bounces.
Online Ads – If you serve ads on your site you are providing links to external sites. Visitors who land on your site, see an ad that grabs their attention are going to click on it (isn’t that what you want so that you can command higher rates for the ads?). It is not really a bounce because visitors are taking the action that you want them to take. See the screenshot from Techcruch which is full of ads and I bet this page (and other article pages) has a very high bounce rate.
Destination Pages – Pages that provide the information that the visitors are looking for is what I call destination pages. Usually you will see the visitors arriving from bookmark or search to the internal pages on your site that provide the visitors with the information that the visitors are looking for. Since those pages serve the visitors’ need you are likely to see high bounce rates on those pages. Those bounce are not bad. Some might argue that you should try to drive visitors into the other sections of the site but I can bet that in most of the cases you won’t see significant drop in bounce rate no matter how hard you try. Below is an example of a page on First Tech Credit Union that could have a very high bounce rate. I arrived at this page by searching for the “Phone number for First Tech in Redmond”. When I arrived on this page I got what I was looking for and I bounced.
Are you considering these factors when analyzing the bounce rates on your site? Questions? Comments?
I have referred to 1st party and 3rd party data in a lot of blog posts. Based on the queries I get, both via email and in the classes I teach, it is time to clarify what various data sources mean.
1st Party Data
1st party data is the data that you (brand/publisher/retailer) have collected about your visitors, customers, shoppers etc. You own the data outright and all the rights to it. You can use it for any purpose you want based on the agreements with your visitors, customers, shoppers etc. as specified in your data collection and use policies. Some examples of 1st party data are:
Site registration data – name, email, address, gender etc.
Visitors behavior data on your site – time of visits, minutes spent, products looked at, source of visits etc.
Shoppers/customers purchase data – products purchased, transaction amounts, coupons used etc.
Email data – emails sent, opened, clicked etc.
It is most widely used data for the marketing purposes. Generally, you use the 1st party data for customer retention using email marketing, retargeting and onsite personalization.
2nd Party Data
2nd party data is the data that is collected by some other company and shared with you(brand/publisher/retailer), in other words it is their first party data. A strategic data sharing partnership between two brands/publishers can help both of them grow their customer base and monetize that customer base.
You can generally use 2nd party data to:
Augment the data you already have about your customers (or visitors) – for example, if you do not collect “Household Income” during customer registration/signup data but have a need for that data you can partner with another brand that collects that data to get that data to enhance user profile. Another example is Google Adwords sending the keyword/campaign data to enhance behavioral data collected on the site.
Add a list of new customers – for example, if you are hotel booking site, you can have a partnership with airline to share information about customers who recently booked. If a customer books a flight, then you can use the data from partner to reach those customers and offer them hotels. Similarly, the airline partner can reach the customers who have booked hotel on your site.
3rd Party Data
3rd party data is the data collected and aggregated by someone other than the 1st party (data collector). In other words, the data aggregator doesn’t directly collect the data from customers/shoppers/visitors but have relationships with several companies/sources that collect the 1st party data. Some examples of the 3rd party data provider are BlueKai, Acxiom and i-behavior. These data providers aggregate the data from different sources to build a comprehensive profile of a customer/person. These enhanced profile let you understand a visitor/shopper more than what a 1st party or 2nd party data sets can provide.
For example, if you are a Financial institution, it will be very helpful for you to know which of your customers travel frequently, this will help you offer them a credit card that provides added travel rewards and benefits. This is where 3rd party data becomes useful that can provide such information based on data collected from various data sources such as hotel booking sites, airlines, location based data on several other places, other credit card providers etc
So you have learned how to use Google Tag Manager. Now you are ready to learn some advanced use cases beyond basic Google Analytics, AdWords or Facebook pixel tracking. I have launched a new course “Google Tag Manager Advanced Applications“
I have been in Digital Marketing and Analytics for over 15 years. I have trained people from diverse backgrounds and have converted them into high performing Digital Marketers and Analysts. I understand both the technology and marketing side of business. I have dealt with many analytics technologies way before Google Tag manager existed and know the inner working of Digital Analytics.
In addition, I have developed various course and taught students from all over the world. I am online instructor for University of British Columbia (Canada), University of Washington (USA), Bellevue College (USA) and Digital Analytics Association.
Web Analytics and Digital Analytics are quite often used interchangeably. I have been asked, by my students and some clients, about the difference in these two, so I decided to write this short post to clarify the terms.
As you can see from the Google Trends graph, Google searches for “Digital Analytics” were nonexistent till Web Analytics Association changed its name to Digital Analytics Association. Since then the term “Digital Analytics” has started to pick up.
In early days of internet, companies started to analyze website data such as users, visitors, visits, page views etc. and the term used to describe this analysis was called “ Web Analytics”.
Then came other forms of online (digital channels) such as email, search, social, mobile etc. and increasingly Digital Analytics folks were including this data and analysis of all these channels to provide a complete view of the “Digital” channels, marketing and customers. To fully include the scope of work of “Web Analysts” a new term “Digital Analytics” was coined.
“Web Analytics” companies like WebTrends, Omniture (now Adobe), Google Analytics etc. also started including data from other online channels and transformed from Web Analytics tools to Digital Analytics tools.
When I was on the board of “Web Analytics Association” from 2009 – 2011, we had several discussions regarding the name of the association. The general consensus was that our members were doing much more than traditional “Web Analytics” and association needs to change the name and scope to include the changing role of “Web Analytics”. Association finally changed the name to “Digital Analytics Association” on March 5th, 2012.
So back to the original question – What is the difference between Web Analytics and Digital Analytics?
Web Analytics is analysis of the website data.
Digital Analytics includes analysis of data from all digital channels that includes websites. Data from search, display advertising, social, email, mobile etc. is included to provide a complete view of the digital marketing and customers.
Though usage of Digital Analytics is picking up, “Web Analytics” is still searched more often than “Digital Analytics” as shown in the following Google Trends chart
The following video is part of the full course that is available on