Applying Big Data Analytics to Clickstream Data

If you are a retailer, how well do you know your products and how well do you know your customers?  You may know which products are most popular based on their purchase history because you keep records of those transactions.  But do you know which of your products are the most and least viewed?  Do you know what is driving traffic to certain products and what type of customers are most interested in those products?  Are you able to provide intelligent and meaningful product recommendations to your customers and increase potential sales revenues?  Gaining insight into this type of information is becoming increasingly more valuable to online retailers to gain an invaluable edge over the competition.

In this blog, I will discuss how you can utilize Talend Platform for Big Data to simplify a full-scale analysis of clickstream data, which is a recorded series of clicks within a website, to glean valuable insight into customer trends and behaviors.

Download >> Get Talend’s New Big Data Sandbox Here

What is Clickstream Data?

Clickstream data is nothing new.  It has been recorded and analyzed for years to track and understand an individual’s online behavior.  Recently, analysis of clickstream data has become increasingly more popular in the online retail space.  But the common problem many companies face with clickstream analysis is the sheer volume of data makes it almost impossible to process through standard ETL methods in a timely fashion.  While Hadoop and MapReduce make the analysis much more feasible, there is still a very sharp learning curve to the technology.   With the use of Talend Platform for Big Data, now you can build quick and simple jobs that use native Hadoop and MapReduce Technology to analyze these enormous datasets within minutes, and produce impressive graphical dashboards to present to Executive Team Members who are making critical business decisions that drive the success of the company.  All of this can be done through Talend’s easy-to-use graphical interface and without a single line of MapReduce code being written.

In this example we demonstrate using native MapReduce to enrich a dataset and aggregate the results for different web-based dashboards. 

Data-Driven Retail, Right Now

When you download and try the new Talend Big Data Sandbox you will get hands-on experience with a simple Clickstream analysis job that demonstrates the value such analysis can bring to the success of your company.  In a matter of minutes, you will know which product categories are the most popular and which are the least popular across the country and within each state.  Allowing you to pinpoint exactly where your focus should be.

Clickstream analysis is the perfect example of the benefits of using Hadoop and MapReduce to make sense out of what would otherwise seem to be a mass of meaningless data.  And Talend Platform for Big Data will simplify your transition into Big Data Analysis by making sense out of Hadoop and MapReduce. You may be thinking you can’t afford this type of analysis, but in today’s data-driven retail economy, I would suggest you can’t afford to be without it. To take it a step further, in an upcoming blog, I will be discussing how you can further use this clickstream data to produce real-time, intelligent recommendations to customers for increased sales potential.

Download your own Sandbox here and get your Big Data project started instantly using our step-by-step cookbook and video.

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isarivelan
my laptop config 4gb ram, intel i3. i can able to work with talend big data sandbox?

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my laptop config 4gb ram, intel i3. i can able to work with talend big data sandbox?

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