Conversion of Abandoned Cart, Browse and Search Prospects using Next Generation Big Data Analytics

advancedanalytics

Client challenges

Project scope

Our client is an American retail giant with a promising e-commerce business. However, stiff competition and the slow maturity of the e-com industry led to a steady sales decline. The client planned a three-year, $5 million turnaround strategy that relies heavily on e-commerce, mobile web technology and predictive marketing analytics to achieve the goal of becoming the ‘most engaged’ retailer in America. One of the ways to do this was to increase the rate of cart abandonment conversions. The business objective was to win back customers using advanced analytics that would approach them with a personalized timely email on a daily basis to help sort out the problems that might have led them to discontinue browsing activity or abandon their shopping carts.

Solution

Tackling Cart & Browse Abandonment

Datametica proposed a solution for the Cart Abandonment and Browse Abandonment use cases.

Approach

Defining processes and structures

Datametica proposed a solution for the Cart Abandonment and Browse Abandonment use cases. We worked out the following broad approach to tackle the challenges:

  • Define process to identify customer and enrich customer mapping dataset
  • Define a process and the business rules for generating a file (in the Big Data system) using the available Clickstream data, by identifying Cart Abandonment and Browse Abandonment use cases
  • Define the structure (list of fields) of the target file to be delivered to the Marketing team
  • Define any dependency, assumption and constraints available

Benefits

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Personalized email

Personalized timely email using advanced analytics on a daily basis

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Cart conversion

A three-time increase in conversion of cart abandonment cases

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Browse conversion

A five-time increase in conversion of browse abandonment cases

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Revenue increase

There is a proven month-on-month increase in revenue by million dollars

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Tools / Technologies
  • Sqoop
  • Hive
  • Pig
  • HBase
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