Your Web / Mobile page looks great. But the next big question is how do you move your prospects customers on to bigger things – like clicking on ‘Call to Action’ (CTA) buttons, submitting a form or completing a purchase?
With more granular and segmented data, it’s now easier to analyze, visualize and ultimately change how visitors behave on your website.
This is what we do best – deriving insights from large data sources such as web logs. By combining web logs with more traditional customer / inventory/ advertising cost data, we can better understand customers and understand how to optimize future promotions and advertising. Through data analytics and it’s visualization through Tree Maps we demonstrate how an e-retailer can optimize buying paths to reduce bounce rate and ultimately improve conversion in long run.
WHAT IS CLICKSTREAM DATA
Clickstream data is an information trail a user leaves behind while visiting a website or your mobile App. It is typically captured in semi-structured website log files and capturing events.
These website log files contain data elements such as a date and time stamp, the visitor’s IP address, the URLs of the pages visited, and a user ID that uniquely identifies the user.
HOW DO WE USE CLICKSTREAM DATA
Our data science team refine and analyze clickstream data, over a period of time, using various tools and frameworks. They then answer business questions such as:
- 1. What is the most efficient path for a site visitor to research a product, and then buy it?
- 2. What products do visitors tend to buy together, and what are they most likely to buy in the future?
- 3. Where should I spend resources on fixing or enhancing the user experience on my website?