How does Clickstream Analytics help improve an e-commerce portal’s performance?
What is Clickstream Analytics?
A clickstream records the users’ clicks while he/she browses the Web. It helps us study the behavior of online customers on e-commerce websites. On drawing behavioral insights using the clickstream, you can derive information on how to improve targetted aspects of the online shopping portal. Clickstream data can tell an e-commerce site owner about which products the customer is interested in (browsing/ adding to a wishlist/ cart), the product categories the visitor is majorly interested in , and the effect of the prices, ratings, and other relevant information on the users’ buying decisions. Since, a clickstream is a list of all the pages viewed by a visitor, presented in the same order that the pages were viewed in, it can be used to derive greater insights on the website’s performance.
The aggregated information derived from analyzing clickstreams in conjunction with basic demographic/ customer profile information can give you a wealth of insights on your website. The various customer tendencies are often measured by some standard metrics like their visit durations, search terms, ISPs, countries, browsers, etc. The process can enable you to know what your visitors are thinking. Hence, the three major questions site-owners get answered by using clickstream analysis for their websites are:
- What is the most efficient path for a site visitor to research a product, and eventually buy it? ( most efficient route for the maximum Conversion rate)
- What products do visitors tend to buy together, and what are they most likely to buy in the future? (Product bundling and consecutive marketing campaigns)
- Where should I spend resources on fixing or enhancing the user experience on my website? (Wensite optimization)
How do you use clickstream analytics for your website?
There are various tools that can analyze your clickpaths for you. Most technologies work on the same principle to parse large amounts of unstructured events into log files. These log files are then used to derive patterns and trends on customer-tendencies. Most tools have 2 basic elements to their structure:
- Mapper: Mappers extract logs on user details, like the ID and the final event executed by the user (viewed, purchased or queried)
- Reducer: The users’ session is then recorded and organized by a reducer. Moreover, the outputs are compressed into files that are further processed and sorted into files that can be analyzed.
Although the infrastructure of all tools used for clickstream analytics will be similar with a few changes in some places, choosing the right tool according to your budget and software requirements is necessary.
Algoscale’s Clickstream Data Analytics solution helped them in creating granular customer segments on the basis of the routes traced by their clicks. This approach helped our client to identify the most optimal buying paths and patterns of their consumers. The methodology used was based on technologies like Python, Java, Hadoop and SQL which helped a major product e-commerce portal in the US to reduce the bounce rate on their website by 20%. This process was based on a 3-step approach: Load, Refine and Analyze, Visualize which ensured that the results so obtained were easy to understand and actionable.