Page 216 - Building Big Data Applications

216 Use cases from industry vendors

in-memory database combines customer profile, buying behavior, sentiment and shopping
trends based on a variety of cross-industry data sources with millisecond latencyepowering
analytics at the speed of thought.
The new platform is now playing a key role in their multiple industry big data initiative.
They are able to develop a full 360-degree profile of each customer, using multiple di-
mensions of customer attributes to describe their behavior, such as cross channel behavior,
CRM/demographic/behavioral/geographic data, brand sentiment, social media behavior, and
purchasing behavior via e-commerce, e-wallets, and loyalty programs. Lippo Group can now
correlate all customer information and transactions to understand their profile and prefer-
ences in order to interact with them in a personalized way. They can also associate household
members’ activities and preferences as consolidated profiles to deliver family-based
personalized offers and improve their service experiences.
By having these types of 360 degree profiles, Lippo Group can improve overall customer
experience, conversion rates, campaign take-up rates, inventory/product life cycle manage-
ment, and future purchasing predictions.
The Technology Behind the Curtain
The underlying technology consists of a Hadoop big data cluster and an analytics layer
on Kinetica. In the images below, you can see the evolution in the technology stack that took
place to bring Lippo Group’s analytics to the next generation:

Before:

Lippo Group’s legacy analytic consisted of Impala, Hive, and HBase