The Challenges of Clickstream Data

While web browsing, every user’s activity on the internet are being recorded. This technique is what we call “Clickstream” and it allows businesses to know the “steps” that customers usually take on their website. It can be defined as a sequence of events that represent the visitor's actions on the website or as the electronic record of Internet usage collected by web servers.

According to Albert, Bill, Tedesco, Donna and Tullis, T. (2010), Clickstream Data is a detailed log of how participants navigate on a website during a task. It usually includes the pages visited, time spent on each page, how they arrived on the page, and where they went next. From an accumulated view, clickstream data provide insights into how easily the site is navigated, what pages are causing the greatest confusion, and what pages are critical in reaching the desired destination.

Moreover, clickstream data can assist businesses to recognise each consumer as a single person, creating a profile based on the collection of data points. This allows companies to understand the journey that leads customers to their needs, as well as providing visibility over the competitors’ customer journeys, as this data became essential for businesses to stay competitive and analyse consumers' behaviour when connected to Web Analytics. 

Challenges in the Clickstream Data

Clickstream data contains many ambiguities when it comes to identifying visitor origins, visitor sessions, as well as visitor identities. Browser caches and proxy servers make these identifications more challenging. Data Collection and Business Requirements Identifications are other challenges when it comes to this tool.

A shortcoming of Log Files - Log file can not identify individual people, as it registers the computer IP address instead of the visitor. Thus, presumptions to determine the “user sessions” might be wrong.

Real-time Analysis - Usually used for user profiling, real-time analysis demands to track the moves of a visitor right after entering the website. When you know the group of users that a specific visitor belongs, it is possible to permit the website to make a fast decision, such as the kind of recommendations that can be provided. As predicting accurately is hard, once you made a wrong recommendation, it is more likely that the company will have some loss. 

Privacy - Another major concern is user privacy while web browsing.

References 

Bucklin, R.E. and Sismeiro, C., 2009. Click here for Internet insight: Advances in clickstream data analysis in marketing. Journal of Interactive Marketing, 23(1), pp.35-48.

Albert, B., Tedesco, D. and Tullis T. (2010). Beyond The Usability Lab: Conducting Large-scale User Experience Studies. Morgan Kauffmann.

Sciencedirect.com. 2020. Clickstream Data - An Overview | Sciencedirect Topics. [online] Available at: <https://www.sciencedirect.com/topics/computer-science/clickstream-data> [Accessed 14 June 2020]. 

Castro, V., 2020. Using Behavioral Data To Measure Netflix’S Reach. [online] Netquest.com. Available at: <https://www.netquest.com/blog/en/comparison-of-netflixs-reach-in-the-united-states-spain-and-the-uk> [Accessed 14 June 2020].