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Digital analytics – What is it? (Part 2 of Web Analytics Series)

In the last article, we have explored the importance of data and how to keep that in a context. (You can find the post link here). In the new world of big data and analytics, having this understanding will simplify our work life. In this post, I try to cover one of part of data analytics – Digital analytics. 

A simple Google search for the term ‘Digital analytics’ is retuning 60 Million results and a search for ‘Web analytics’ is retuning 270 Million results. When compared the top 10 searches for both, not a single website is the same. This is a simple example of confusion that is associated with digital analytics in the current market. Many theories and more concepts flow in and out every day on this topic. In my viewpoint, digital analytics, web analytics, on-line analytics all are different names for the same concept.

So let’s keep this simple.

The Web Analytics Association defines web analytics as the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimising web usage. Though web analytics cover the entire internet data in its definition, general audience understanding  has been mostly restricted to ‘website’ analytics due to the wide spread popularity of Google Analytics which was fuelled by the demand for accountability of digital marketing initiatives at the same time period due to restrictions on the marketing budgets.

Digital analytics is a marketing-centric practice, which helps us to gain better return on investment (ROI) for digital channels that are used by marketing departments. This process does not stop at collecting and reporting the data, but it is meant to provide the optimised recommendations for marketing teams to best use their resources. Depending on the objective of the campaign, it helps to provide the type of channels or publishers or group of audience that need to be targeted. Once the user is familiar with the marketing message, the data should guide us to lay the easy path for user to take the desired action. All this can happen only when the understanding of data is met.

For the discussion purposes, digital marketing analytics can be divided into two parts

1) On-site web analytics
2) Off-site web analytics 

1) Onsite web analytics: Onsite analytics is the process of analysing and optimising the digital data collected AFTER a user has entered the designated site. It is also known as site-side analytics and constitutes the later part of the consumer journey i.e. content engagement and conversion on the site. Typical metrics that are used are - page views, time spent on site, visits, visitors, bounce rate, conversion rate etc. Complete list of available metrics and standard definitions are available on WAA site. 

2) Off-site web analytics: Offsite analytics is the process of analysing and optimising the digital data collected BEFORE a user has entered the site. This is also known as media analytics which covers reach channels. Display, search, social, e-mail etc. form this part of media analytics. It includes measurement from channel reach to creative’s performance and clicks to share of voice, buzz to sentiment. Over all this consists all the information about the user interaction of brand on internet as a whole. Paid media analytics forms the greater part of offsite web analytics, so collecting and analysing this data should be the first step in achieving higher ROI and greater efficiency. 
This division of analytics has been blurred in the recent months as the tool vendors started producing multi-channels analytics and attribution models. However, a common understanding and standardisation of the industry is yet to be reached. From an organisation point of view, either its onsite or offsite analytics, both need to have same objectives measured via Key Performance Indicators (KPIs). These have to be defined and set before any related activity is planned. This requires a process-oriented approach which can be achieved only by having a framework in place. This framework has to be taken into consideration of an organisations vision, goals and help them to achieve the targeted data driven organisation. As can be understood, this will be a customised process as per organisations.

In these series of web analytics articles, we will ponder over the details on how to set up this approach. Watch this space to get updated. 

Please leave your comments or feedback or thoughts. 

(Edited by Ankit Bhatnagar)


Gayathri Choda

Gayathri Choda is  Head of Analytics at Mediamind. She has 6 years of experience across digital analytics, marketing strategy development. Before joining Mediamind, Gayathri worked with Wunderman (WPP), Singapore as Insights and Optimization lead for SEAP countries. Her clientele includes Microsoft, Nokia, Xbox, Time group, JP Morgan etc.