Web Analytics

So you’ve created an online business. You’ve successfully attracted customers to your site and are now receiving a respectable number of hits on the site each month. You could be forgiven for thinking that the hard part of setting up an e-commerce site is over; that you can now sit back, relax and watch the sales roll in.

In part there is some truth. One of the hardest aspects of setting up an online business is gaining customer attraction (Hubspot.com, 2017). If no one visits your site, you won’t make any sales and the business will fold. The hard work however, is not yet over.

Once customers are being driven to your site, understanding how they interact with the site is critical in order to understand whether customers are engaging with the site, which aspects of the site are successful and which need improving. This is where web analytics plays its vital role.

Web analytics in its broadest term can be described as the goal of understanding the online experience so that it can be improved (Peterson, 2004, p.5). Through data collection, analysis can be performed providing insight into how the consumer reacts to the website whether this be negative or positive. Change can then be implemented to improve aspects of the site with the goal being improved customer engagement and subsequently increased sales. Web analytics therefore creates a cyclical process of continuous improvement. Once an improvement is implemented web analytics ‘determine the degree to which those improvements have been successful and generate new ideas for improvement’, (Loftus, 2012).

Data can be gathered through use of a plug in, such as google analytics. I opted to use this specific plug in on my website due to its reputation as the best free web analytic tool available as stated by (Jantsch, 2012) and (Walgrove, 2016). 

The screenshot below is taken from the google analytics produced for Flash + Dazzle and shows customer behaviour on the website.

google analytics 2

The data shows a variety of information such as: how long customers spent on each page visited, what percentage of customers have exited on the landing page (known as the bounce rate), which pages are most visited and so on. Patterns and trends can be identified using this data, paving the way for improvement as discussed.

Examples of ways in which the data can be used would include analysis of a high bounce rate (Suresh, 2015). This means that customers aren’t engaging with the landing page and are exiting without exploring the site further. This is a serious issue and action would need to be taken to improve the page to entice customers to move past the landing page into the website. A further example would be customers successfully navigating through the site, but the site having a high exit rate on the product pages. This could indicate that the customers don’t feel that they have been provided with enough information to buy, and again, action would need to be taken to improve this aspect to convert the customers into sales.

Although these examples are focused on the negative data, improvements can also stem from positive data. Web pages with particularly high engagement rates, and or pages where customers are spending a considerable amount of time could be deemed successful. These pages could then be replicated within other areas of the site in order to improve success rates of other pages.

Customer behaviour and interaction however, is just one aspect of analysis. Other areas of analysis shown on the left hand menu bar can also be used to increase understanding. For example, the audience section provides demographic information which can be utilised to ascertain whether the correct target market is being attracted. This can be incredibly insightful as if the incorrect target market is being driven to the site, they may not be likely to engage with or buy from it.

google analytics 1

Data analytics can also provide insight into which keywords have driven customers to the site allowing the most attractive keywords to be focused on and utilised throughout the site. Volume of visitors can be tracked as well as identification of referral sources.

Suresh (2015) asserts that whilst data analytics can show what pages require attention, it is not able to pin point what part of the page needs improving. For instance, a high bounce rate as previously mentioned indicates that the landing page is in need of improvement. This however is as far as the insight extends. Use of heat mapping provides a visual representation of customer behaviour and can visually tell you in an instant, how customers are engaging with your page.


This understanding allows a more focused change initiative to be undertaken and ensures that parts of the page that customers like and engage with, aren’t altered causing detriment to the site.

In summary, access to visual and data analytics can substantially improve efficiency, customer retention within the site, aid sales conversion and lay the foundation for new marketing strategy. Web analytics therefore are critically important to the shaping and success of an online business.



Hubspot.com. (2017). 2017 Marketing Statistics, Trends & Data – The Ultimate List of Marketing Stats. [online] Available at: https://www.hubspot.com/marketing-statistics [Accessed 2 May 2017].

Jantsch, J. (2012). The 10 Smartest Web Analytics Tools. [online] American Express – OPEN Forum. Available at: https://www.americanexpress.com/us/small-business/openforum/articles/the-10-smartest-web-analytics-tools/ [Accessed 30 Apr. 2017].

Loftus, W. (2012). Demonstrating Success: Web Analytics and Continuous Improvement. Journal of Web Librarianship, [online] 6(1), pp.45-55. Available at: http://www.tandfonline.com.proxy.worc.ac.uk/doi/full/10.1080/19322909.2012.651416 [Accessed 30 Apr. 2017].

Peterson, E. (2004). Web analytics demystified. 1st ed. Portland, Or: Celilo Group Media [u.a.].

Suresh, S. (2015). 5 Ways Website Heat Maps Help You Read Visitors’ Minds. [online] VWO Blog. Available at: https://vwo.com/blog/5-ways-heat-maps-and-visual-analytics-help-conversions/ [Accessed 1 May 2017].

Walgrove, A. (2016). The Top 10 Free Content Analytics Tools. [online] The Content Strategist. Available at: https://contently.com/strategist/2016/08/02/the-top-10-free-content-analytics-tools/ [Accessed 30 Apr. 2017].


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